Showing papers in "Applied Medical Informatics in 2013"

Administer and collect medical questionnaires with Google documents: a simple, safe, and free system.

Abstract: Aim: Questionnaires are an invaluable resource for clinical trials. They serve to estimate disease burden and clinical parameters associated with a particular study. However, current researchers are tackling budget constraints, loss of funding opportunities, and rise of research associated fees. We aimed at exploring alternative avenues taking advantage of the free Google docs software for questionnaire administration. This presents an opportunity to reduce costs while simultaneously increasing efficiency and data fidelity. Material and Methods: Google documents were used as a platform to create online questionnaires that were automatically hosted via a unique URL. Password protected access to the URL link and a unique study ID gave patients around the clock access from anywhere in the world. Unique study ID ensured confidentially of all self-reported data. Patient responses were secured using a “Cloud” database where the data was automatically sorted, scaled and scored by custom Excel formulas. Researchers downloaded real-time questionnaire responses in multiple formats (e.g. excel) which was then analyzed with a statistical software of choice. Results: This simple workflow provided instant questionnaire scores that eliminated the use for paper-based responses and subsequent manual entry of data. Ease of access to online questionnaires provided convenience to patients leading to better response rates and increase in data fidelity. The system also allowed for real time monitoring of patient’s progress on completing questionnaires. Online questionnaires had 100% completion rate compared to paper-based questionnaires. Conclusions: Google docs can serve as an efficient and free platform to administer questionnaires to a clinical population without sacrificing quality, security, and fidelity of data.

Automatic Detection of Retinal Exudates using a Support Vector Machine

Abstract: Retinal exudates are among the preliminary signs of diabetic retinopathy, a major cause of vision loss in diabetic patients. Correct and efficient screening of exudates is very expensive in professional time and may cause human error. Nowadays, the digital retinal image is frequently used to follow-up and diagnoses eye diseases. Therefore, the retinal image is crucial and essential for experts to detect exudates. Unfortunately, it is a normal situation that retinal images in Thailand are poor quality images. In this paper, we present a series of experiments on feature selection and exudates classification using the support vector machine classifiers. The retinal images are segmented following key preprocessing steps, i.e., color normalization, contrast enhancement, noise removal and color space selection. On data sets of poor quality images, sensitivity, specificity and accuracy is 94.46%, 89.52% and 92.14%, respectively.

Evaluation of a Web-based Online Grant Application Review Solution

Abstract: This paper focuses on the evaluation of a web-based application used in grant application evaluations, software developed in our university, and underlines the need for simple solutions, based on recent technology, specifically tailored to one’s needs. We asked the reviewers to answer a short questionnaire, in order to assess their satisfaction with such a web-based grant application evaluation solution. All 20 reviewers accepted to answer the questionnaire, which contained 8 closed items (YES/NO answers) related to reviewer’s previous experience in evaluating grant applications, previous use of such software solutions and his familiarity in using computer systems. The presented web-based application, evaluated by the users, shown a high level of acceptance and those respondents stated that they are willing to use such a solution in the future.

Comparing Performance of Different Neural Networks for Early Detection of Cancer from Benign Hyperplasia of Prostate

Abstract: Prostate cancer is one of the most common types of cancer found in men. Presenting a classifier in order classifies between Prostate Cancer (PCa) and benign hyperplasia of prostate (BPH), has been great challenge among computer experts and medical specialists. There are a number of techniques proposed to perform such classification. Neural networks are one of the artificial intelligent techniques that have successful examples when applying to such problems. The increasing demand of Artificial Neural Network applications for predicting the disease shows better performance in the field of medical decision-making. This paper presents a comparison of neural network techniques for classification prostate neoplasia diseases. The classification performance obtained by four different types of neural networks for comparison are Back Propagation Neural Network (BPNN), General Regression Neural Network(GRNN), Probabilistic Neural Network (PNN) and Radial Basis Function Neural Network (RBFNN). Result of these evaluation show that the overall performance of RBFNN can be apply successfully for detecting and diagnosing the cancer from benign hyperplasia of prostate.

Diagnosis System for Diabetic Retinopathy to Prevent Vision Loss

Abstract: Aim : Diabetic Retinopathy (DR) is one of the major problems of diabetic patients. The diabetic patient is not aware of any symptom until it is too late for effective treatment. It is the leading cause of blindness. Diabetic retinopathy results in retinal disorders that include Microaneurysms (MA), soft exudates, hard exudates and intra-retinal vascular abnormalities. Methods : Soft Computing Neural Networks are used to detect and diagnose lesions or abnormalities associated with diabetic retinopathy which facilitate the Ophthalmologists in accurate diagnosis and early treatment to prevent vision loss in diabetic patients. Results : The result shows that the methodology used is well suited for the early diagnosis of the diabetic retinopathy disease. Conclusions : By evaluating the exudates and fovea region, and analyzing the relation between them, the severity of DR can be easily identified to prevent vision loss in diabetic patients.

Daily Intensive Care Unit Rounds: A Multidisciplinary perspective

Abstract: The distinctive nature of the workflow in the Intensive Care Unit (ICU), combined with the time sensitive nature and cognitive burden to the various providers make it an error prone environment. With the current proliferation of health information technology, it’s crucial to recognize and define the current practice needs to enable a successful integration of these technologies into the workflow. Our study aimed to define the objectives and tasks of ICU Multidisciplinary Rounds (MDR) activities and gain insight from different ICU providers regarding their perceived versus observed practice. We conducted a survey of healthcare providers in the Medical and Surgical ICU at Mayo Clinic, Rochester, MN.A total of 105 surveys were distributed and 75 were collected, yielding a response rate of 71.5%.72% of providers identified designing or developing a plan of care, 23% mentioned data gathering, 16% team consensus, 12% patient and family interaction and 11% education Members of multidisciplinary ICU teams most often identified the development of a care plan as the purpose of morning MDRs. Interruptions and resource utilization were identified as the main interferences to task completion, where limiting interruptions, workflow changes and technology were the suggested solutions

Application of Mobile Photography with Smartphone Cameras for Monitoring of Early Caries Appearance in the Course of Orthodontic Correction with Dental Brackets

Abstract: The objective of this research was observation of patients, who underwent orthodontic tooth alignment correction with dental brackets, for the detection of white spots, (early stage of caries) based on the digital photographs taken with a smartphone Sony Xperia S. Color reading was realized taking into account the adjustment of color features of a standard ceramic tile that was selected during the dental brackets installation period, the photo of which was taken simultaneously during the dynamic observation period. The color scale RGB was transformed into CIE L*a*b scale on the basis of correction of RGB components of smartphone image with correction coefficient, which was recalculated for tile surface RGB values. Consequent evaluation of lightness of suspected spots on the enamel served for the detection of white spots appearance. The expert appraisal showed sensitivity of proposed method between 88.7% and 96.2% and specificity between 68.4% and 84.2%. The positive predictive value was between 89.5% and 94.0%; and the negative predictive value was between 72.7% and 86.7%. Digital smartphone photo color corrected on the basis of comparison with tile surface permits to diagnose white spots appearance in patients with orthodontic tooth alignment correction.

Classification of Arrhythmias Using Linear Predictive Coefficients and Probabilistic Neural Network

Abstract: Cardiac arrhythmia, which means abnormality of heart rhythm, in fact refers to disorder in electrical conduction system of the heart. The aim of this paper is to present a classifier system based on Probabilistic Neural Networks in order to detect and classify abnormal heart rates, where besides its simplicity, has high resolution capability. The proposed algorithm has three stages. At first, the electrocardiogram signals impose into preprocessing block. After preprocessing and noise elimination, the exact position of R peak is detected by multi resolution wavelet analysis. In the next step, the extracted linear predictive coefficients (LPC) of QRS complex will enter in to the classification block as an input. A Support Vector Machine classifier is developed in parallel to verify and measure the PNN classifier’s success. The experiments were conducted on the ECG data from the MIT-BIH database to classify four kinds of abnormal waveforms and normal beats such as Normal sinus rhythm, Atrial premature contraction (APC), Right bundle branch block (RBBB) and Left bundle branch block (LBBB). The results show 92.9% accuracy and 93.17% sensitivity

Second order Statistical Texture Features from a New CSLBPGLCM for Ultrasound Kidney Images Retrieval

Abstract: Normal 0 false false false This work proposes a new method called Center Symmetric Local Binary Pattern Grey Level Co-occurrence Matrix (CSLBPGLCM) for the purpose of extracting second order statistical texture features in ultrasound kidney images. These features are then feed into ultrasound kidney images retrieval system for the point of medical applications. This new GLCM matrix combines the benefit of CSLBP and conventional GLCM. The main intention of this CSLBPGLCM is to reduce the number of grey levels in an image by not simply accumulating the grey levels but incorporating another statistical texture feature in it. The proposed approach is cautiously evaluated in ultrasound kidney images retrieval system and has been compared with conventional GLCM. It is experimentally proved that the proposed method increases the retrieval efficiency, accuracy and reduces the time complexity of ultrasound kidney images retrieval system by means of second order statistical texture features.

Effects of Music on Cardiac Functioning in Young Women and Men

Abstract: Purpose: Music not only improve quality of life but may also effect changes in heart rate. This study examined the effects of "Persian traditional music" on cardiac variability. For this purpose, heart rate signals of 62 college students (22 women and 40 men) attending Sahand university of technology were collected. Basic Methods: Time, frequency and nonlinear features (Mean, power spectrum and Lyapunov exponents) of heart rate signals were calculated during rest and music in two groups of healthy young college students: women and men. Main Results: The results show that mean heart rate signals in men group increased during music; however, it decreased in the same protocol in women group. Frequency analysis reveals that maximum power spectrum of heart rate signals is higher in the women's group than that of the men's group. In addition, mean Lyapunov exponents fluctuations are higher in the women's group than that of men's group in both conditions (during rest and music). Principal Conclusions: The current study of heart rate (HR) time series using linear and nonlinear techniques has shown significant differences between before and during the music, and thus could give additional insight into the underlying dynamics of HR and in the investigation of cardiac autonomic function during music in two genders. In addition, it is concluded that music period evoke different reflections of heart rate signals in women and men.

Quality Evaluation for Edge Detection of Chromosome G-band Images for Segmentation

Abstract: Edge detection of chromosome in G-band type image is an important preprocessing step in segmentation. A chromosome type G-band image is generally very noise and poor image quality, lack of contrast and hold in image. A lot of edge caused by chromosome can easily mislead the edge detection algorithm. Particularly, the chromosome overlapping and touching, then it is very difficult to get a clear edge of the femur head. These extraneous edge and noise make edge detection very difficult and challenging, which is not well solved. This paper presents analysis of evaluation chromosome G-band image edge detection. It has been appeared in literature that there are 4 different techniques, i.e. Canny, Laplacain, Robert's, and Sobel, on chromosome image type G-band. From our study, we found that Robert's give promising results in edge detection. A success rate of 97.69% has been achieved.

VIKOR method for diabetic nephropathy risk factors analysis.

Abstract: Diabetic kidney disease is an important complication of type 2 diabetes mellitus (T2DM) and has an economic impact in growth due to the increasing prevalence of T2DM. Identification of diabetic kidney disease risk factors is a priority for both the patient and the healthcare system. The aim of our study was to rank the risk factors using VIKOR method applied on a database with patients with T2DM. Data from 53 T2DM patients were analyzed with VIKOR method. 18 possible risk factors were taken in consideration as alternatives and four separate criteria of renal function: two for albumin excretion – quantified as urinary albumin/creatinine ratio (UACR) and two for GFR (glomerular filtration rate). In the top of the VIKOR method hierarchy was serum adiponectin followed by triglycerides, systolic blood pressure, duration of diabetes and age. Malondialdehyde and HDL-cholesterol influenced chronic kidney disease as protective factors (18 th , respective 17 th position in the hierarchy). VIKOR method brought new information about the similarity between the positions of some factors in the hierarchy.

A Preprocessing Algorithm for the CAD System of Mammograms Using the Active Contour Method

Abstract: Digital mammogram images can have different kinds of artifacts that affect the accuracy of the detection of tumor tissues in the automated computer-aided detection (CAD) system for mammograms. Preprocessing to remove such artifacts is an important step. In this paper, a preprocessing technique for digital mammograms is devised which removes labels, scanning artifacts and the pectoral muscle. First, it removes hurdles like labels, scanning and taping artifacts using an automated algorithm based on thresholding. Then, using the active contours and the proposed stopping algorithm it obtains the contour which contains the boundary of the pectoral muscle. Later, it extracts the pectoral muscle binary image from the contour. Finally, using the pectoral muscle binary image and the original mammogram image it obtains the desired image without any artifacts and the pectoral muscle. We tested the proposed algorithm on the mammograms from the mini-MIAS database and it worked very efficiently. It provided very effective and accurate results for pectoral muscle segmentation. It provided up to 97.84% accuracy, computed from well segmented results.

Glycemic Variability and Type 2 Diabetes Mellitus

Abstract: Aim : The purpose of the present study was to quantify glucose variability in type 2 diabetic patients and establishing relationship with cardiometabolic parameters and type of glucose-lowering treatment. Material and Methods : Continuous glucose monitoring (CGM) was used in 373 type 2 diabetic patients . Glycemic variability (GV) was evaluated by many indices based on CGM data such as mean amplitude of glycemic excursions (MAGE), standard deviation (SD), nMAGE (calculating MAGE from glucose monitoring data using the algorithm proposed by Baghurst) and mean interstitial glucose values (MG). Results : GV increases significantly from diet to insulin group (p=0.001) and from oral therapy to insulin therapy (p=0.001) by MAGE, SD and nMAGE indices and less powerful for MG (p=0.042 and 0.003 respectively). All GV indices are correlated with each other, the strong relationship being shown between MAGE, SD and nMAGE (p=0.0001). Conclusions : There exists a progressive alteration of GV from diet to insulin therapy in individuals with type 2 diabetes mellitus. The simple standard deviation of CGM (continuous glucose monitoring) readings appears to be the best practical pathway to quantify glucose variability.

Design of Dimensional Model for Clinical Data Storage and Analysis

Abstract: Current research in the field of Life and Medical Sciences is generating chunk of data on daily basis. It has thus become a necessity to find solutions for efficient storage of this data, trying to correlate and extract knowledge from it. Clinical data generated in Hospitals, Clinics & Diagnostics centers is falling under a similar paradigm. Patient's records in various hospitals are increasing at an exponential rate, thus adding to the problem of data management and storage. Major problem being faced corresponding to storage, is the varied dimensionality of the data, ranging from images to numerical form. Therefore there is a need for development of efficient data model which can handle this multi-dimensionality data issue and store the data with historical aspect. For the stated problem lying in facade of clinical informatics we propose a clinical dimensional model design which can be used for development of a clinical data mart. The model has been designed keeping in consideration temporal storage of patient's data with respect to all possible clinical parameters which can include both textual and image based data. Availability of said data for each patient can be then used for application of data mining techniques for finding the correlation of all the parameters at the level of individual and population.

Content Based Medical Image Retrieval for Histopathological, CT and MRI Images

Abstract: A content based approach is followed for medical images. The purpose of this study is to access the stability of these methods for medical image retrieval. The methods used in color based retrieval for histopathological images are color co-occurrence matrix (CCM) and histogram with meta features. For texture based retrieval GLCM (gray level co-occurrence matrix) and local binary pattern (LBP) were used. For shape based retrieval canny edge detection and otsu‘s method with multivariable threshold were used. Texture and shape based retrieval were implemented using MRI (magnetic resonance images). The most remarkable characteristics of the article are its content based approach for each medical imaging modality. Our efforts were focused on the initial visual search. From our experiment, histogram with meta features in color based retrieval for histopathological images shows a precision of 60 % and recall of 30 %. Whereas GLCM in texture based retrieval for MRI images shows a precision of 70 % and recall of 20 %. Shape based retrieval for MRI images shows a precision of 50% and recall of 25 %. The retrieval results shows that this simple approach is successful.

Enabling coordination within medical settings: case of a maternity ward

Abstract: Purpose: This study evaluates the planning process issues in healthcare institutions that can be considered as a high risk environment. Most recent healthcare research has focused on methods mainly based on communication, rather than collaboration supports. Material Methods: We followed then a collaborative-based planning approach which constitutes an evolution of planning environment toward new shared workspaces supporting collaboration. Our work led us first, to analyse the related tasks in an Algerian maternity ward in order to highlight the vital collaborative medical tasks that need to be modelled. Results: the paper summaries basic design concepts of our collaborative planning system that is designed to make group interaction support flexible for care coordination and continuity. Conclusion: after development and test of our collaborative planning system, we noticed that our collaborative and planning system can increase awareness and hence decrease coordination breakdowns, reduce costs of information collecting and sharing. All these factors constitute a crucial aspect of an efficient management of a hospital.

Acute Viral Hepatitis A – Clinical, Laboratory and Epidemiological Characteristics

Abstract: Background and Aims: Infection with hepatitis A virus is still one of the most common causes of hepatitis worldwide. The clinical manifestation of acute hepatitis A (AHA) in adults can vary greatly, ranging from asymptomatic infection to severe and fulminant hepatitis. The aim of this study was to describe the demographic, clinical characteristics, laboratory features and hospital outcome of adult patients with AHA over a consecutive period of 4 years within an area from Eastern European country. Methods: Two hundred and two adult patients diagnosed with AHA were retrospective, observational and analytic analized over a period of 4 years. Based on prothrombin time less than 50, the study group was stratified in medium (79.2%) and severe forms (20.8%). We investigated the clinical, laboratory and epidemiological features. Statistical analysis were applied to compare the medium and severe forms of AHA. Results: Most patients (72.7%) were younger than 40 years. The main symptoms included: dyspepsia (72.07%), jaundice (86.63%), asteno-adynamia (86.72%), and flu-like symptoms (53.46%). The hemorrhagic cutaneous-mucous manifestations (6.93%) associated with the severe forms of AHA (OR =12.19, 95%CI -3.59 - 41.3, p =0.001). We found statistically significant differences for PT (p <0.001), INR (p <0.001), TQ (p <0.001), ALAT (p <0.001), ASAT (p <0.001), ALP (p <0.001) and platelets (p =0.009) between severe and medium AHA forms. We found that TQ, INR, ALAT and ASAT have the highest diagnostic values, statistically significant (p <0.05 ) for severe AHA forms with AUC (0.99, 0.99, 0.72, 0.70) at values of sensitivity (95%, 90.5%, 89%, 95%) and specificity (98%, 99%, 88%,94%). Conclusions Medium severity AHA forms were found in most of the study group patients (79.2%). The severe AHA forms were associated with hemorrhagic cutaneous-mucous manifestations (OR =12.19, p =0.001). The univariate analysis proved a negatively statistically significant correlation between IP and ALAT, ASAT. The present study revealed that TQ, INR and ALAT have the highest diagnostic values and are statistically significant for severe AHA forms.

Variation of Anti-inflammatory Cytokines in Relationship with Menopause

Abstract: Aim. The aim of this study was to assess serum levels of the key anti-inflammatory cytokines in women of reproductive age and in pre and postmenopausal women. Material and Method. 175 women were enrolled and were divided into 5 groups (1 – Fertile women; 2 – Pre- and perimenopausal women; 3 – Postmenopausal women; 4 – Surgically-induced menopause; 5 – Chronic inflammation). Multiplex cytokine kits were used to evaluate serum levels of interleukin-4, -10 and -13. We determined the serum levels of follicle stimulating hormone, of luteinizing hormone, 17β-estradiol, progesterone, dehydroepiandrosterone and dehydroepiandrosterone sulfate using sandwich ELISA. Results. IL-4, IL-10 and IL-17 present a statistically significant decrease (p=0.00, p=0.00, respectively p=0.0053) in women with natural or surgically induced menopause (groups 3 and 4), compared with fertile women and premenopausal women (Groups 1, 2 and 5). Serum levels of IL-4 and IL-10 are significantly higher in fertile patients with associated chronic inflammatory diseases (133.5±1.314 pg/ml, respectively 6.406±13.47 pg/ml) than in fertile patients without chronic inflammatory diseases or premenopausal women (84.67±1.22 pg/ml, respectively 0.627±0.714). Conclusions. IL-4 and IL-10, together with IL-17, show significantly lower serum values in patients with natural or surgically induced menopause compared with patients of childbearing age or in premenopause. IL-4 and IL-10 show significantly higher serum values for patients of childbearing age presenting chronic inflammatory pathology compared with patients of childbearing age without chronic inflammatory pathology or premenopausal patients.

The Free Software Model of Development in the Area of Medical Informatics

Abstract: Our study has assessed the benefits that electronics health records can bring to small health care facilities by qualitatively and quantitatively analyzing a limited number of open source software suites in the area of medical informatics. We have investigated the way in which these benefits may be achieved by implementing the presented software solutions, taking care to highlight the peculiarities of the open source model of development that prove to be differentiating factors against equivalent closed source commercial solutions. Not taking into account the financial aspect (free software solutions have no licensing costs), we have tried to discern the intrinsic advantages of the model of free software development and its particularities in this specific area of investigation: health informatics.

Cognitive Coping Strategies and Emotional Distress in Mothers of Children with Autism Spectrum Disorder

Abstract: Mothers’ emotional distress,when having a child with diagnosis of autism spectrum disorder (ASD), isdifferent depending on depending on the thinking pattern (rational orirrational) and cognitive coping strategies used. The aim of this study was to assess irrational beliefs, negativeautomatic thoughts, emotional distress, cognitive coping strategies and therelation between them, in mothers of children with ASD. Datawere collected from 65 mothers having a child with diagnosis of ASD. Several psychologicalinstruments were used to assess the irrational beliefs (ABSs), automatic negativethoughts (ATQ), emotional distress (PAD) and cognitive coping strategies(CERQ). Mothers reported high levels of emotional distress, automatic negative thoughtsand irrational beliefs. The cognitive coping strategies that correlated positivelyand statistically significant with emotional distress were self-blame,catastrophizing and rumination. Self-blame and catastrophizing strategies correlatedpositively and statistically significant with the irrational beliefs. Theresults also suggest that the use of maladaptive coping strategies correlateswith a higher levels of irrational beliefs and emotional distress.

Obesity - Important Risk Factor for Sleep Apnea Syndrome

Abstract: Sleep apnea syndrome is a common pathology with negative consequences on cardiovascular and metabolic diseases. The relationship between obesity and OSAS is complex, multifactorial and bidirectional; that leads to a negative mutual influence of the two pathologies. The main purpose of this study is to evaluate the risk associated with obesity and the occurrence of the apnea phenomenon, as well as, to compare the various polysomnographic parameters and to compare them with obesity. 100 patients took part to this study. 60 % of the patients were diagnosed with OSAS. 71 % of the patients had varying degrees of obesity. Significant statistic differences were revealed between: the Mean variation of the BMI in patients with and without apnea (T Test p= 0,007 < 0,05); the dorsal AHI Mean of the non-obese group as against to the dorsal AHI Mean of the obese group (T Test p= 0,002), the AHI Mean in other positions of the non-obese group as against to the AHI Mean in other positions of the obese group (T Test p= 0,000) and the Mean of the arousal index of the non-obese group as against to the Mean of the arousal index of the obese group (T Test p= 0,009). The current study revealed that the arousals associated with breathing events and the position during sleep, especially in obese patients, worsen the consequences of OSAS.

Cervical Lesions and Cellular Atypia in a Female Population from Transylvania

Abstract: Introduction: The purpose of this study was to detect the types of the cervix lesions and to establish the correlations between age, environment of origin, diagnosis and gravity of the lesions Methods: In the period 2009-2012, all cervical secretions from female subjects presented at Integrated Outpatient Unit, of the Clinical Hospital for Infectious Diseases, Cluj-Napoca, Romania were tested by Babes-Papanicolaou examination Babes-Papanicolaou cytological smear was performed according to the 2001 Bethesda System criteria Results: From 3153 cervical secretions (2736 female subjects from urban areas and 417 female subjects from rural areas) with age 10 - 87 years, 2899 (919%) smears (372 women from rural area and 2527 women from urban area) had normal appearance Premalignant or malignant lesions (positive cases) were detected in 254 (81%) smears (45 (121%) cases from rural area, 209 (83%) cases from urban area) In the urban area, most positive cases were recorded in the age range of 45-54 years, while in the rural areas in the age range of 35-44 years The multivariate logistic regression analysis showed that environment and age significantly influenced the occurrence of positive cases (OR=144 95% CI 102-202, p=004 for rural area, OR=071 95% CI 060-085, p<0001 for age) The correlation between age and the degree of severity diagnosis (r=-009, p=014) was not significant Conclusions: Cervical lesions detected through Babes-Papanicolaou test in adult women are more common in the rural area

Using Moodle as On-line Survey Instrument in Medical Education

Abstract: One of the principal issues in any university community is the lack of communication between community categories – leadership, administration, teaching staff and students. Sometimes is important to know in a short time the opinion of one particular group, without investing a lot of resources and without being extremely formal. The aim of this study was to test if an open-source platform – Moodle – can be used for quick surveys inside the Faculty of Medicine, UMF “Iuliu Hatieganu” Cluj-Napoca community. For this, on existing Moodle platform was installed one specific survey instrument – a questionnaire module and a survey containing a real life issue to the students of Faculty of Medicine was launched. The researchers have focused on how the specific problems of a survey - preparing of the survey, the survey process and the analysis of the results can be handle in Moodle. The pilot survey was a success; the conclusion of the study was that Moodle can be used as on-line survey instrument for that community.

E-Learning Content for Early Detection Cervical Cancer

Abstract: Cervical cancer is the second most commonly type of cancer that strikes women. The rate of deaths caused by this type of cancer is quite high. The mortality rate caused by this cancer can be reduced through early detection program. To support this program, the Ministry of Health of the Republic of Indonesia is aware of the need for training the health workers in order to do the socialization quickly and evenly to all corners of Indonesia in order to reduce the number of cases of death due to cervical cancer. The aim of this research was to find out the type of online learning content that was suitable and easy for the public and medical personnel to understand on early detection of cervical cancer. The method used British Columbia’s standard for online learning content which mainly focused on four criteria. Moreover, the method that was used by Jeong and Kim to designthe content of an instructional approach was also employed. Bloom’s taxonomy theory was followed as the reference theory in designing the online learning material. The result described the information content of the early detection of cervical cancer in form of multimedia in online learning.

Medical Image Registration Based Retrieval

Abstract: This paper presents a quantitative evaluation of state-of-the art intensity based image registration with retrieval methods applied to medical images. The purpose of this study is to access the stability of these methods for medical image analysis. The accuracy of this medical image retrieval with affine based registration and without registration is evaluated using observer study. For retrieval without registration and with registration, we examine the performance of various transform methods for the retrieval of medical images by extracting the features. This helps for the early diagnosis. The technique used for retrieval of medical images were a set of 2-D discrete Fourier transform (DFT), discrete cosine transform (DCT), discrete wavelet transform (DWT), Complex wavelet transform (CWT), and rotated complex wavelet filters (RCWF) were implemented and examined for MRI imaging modalities. Especially RCWF gives texture information strongly oriented in six different directions (45° apart from the complex wavelet transform). Experimental results indicate that the DWT method perform well in retrieval of medical images. The method also retains the comparable levels of computational complexity. Then the experimental evaluation is carried by calculating the precision and recall values. It is found that DWT performs well for retrieval without registration and CWT with affine performs well in registration based retrieval with efficiency of 92% from retrieval efficiency 83% of DWT without registration. This helps in classification as before registration and after registration especially for clinical treatment and diagnosis.

Medical image retrieval using transforms.

Abstract: The purpose of this study is to access the stability of transformation methods for medical image analysis. The reason for image retrieval is due to the increase in acquisition of images. Imaging has occupied a huge role in the management of patients, whether hospitalized or not. Depending upon the patient’s clinical problem, a variety of imaging modalities were available for use. In this article various distance methods were used and then they are compared for effective medical image retrieval. A transform based approach is followed for effective retrieval. This paper describes discrete Fourier transforms (DFT), discrete cosine transforms (DCT), discrete wavelet transforms(DWT), complex wavelet transforms (CWT) and rotated complex wavelet transform filter (RCWF) for medical image retrieval. From the final results it is very clear that each transforms performance defers and shows different results in retrieval of medical images. DWT shows the best results in terms of average retrieval results with 95% precision and 83% recall value, average searching time with 8 seconds, and less number of irrelevant images. These results indicate that these easily computable similarity distance measures have a wide variety of medical image retrieval applications.

Validation of the Diagnostic Value of Nuclear Matrix Protein 22 Depending on Tumoral Stage and Grade

Abstract: Objectives: The aim of the present study was to validate the sensitivity and specificity of the NMP22® BladderChek® test in our group of patients according to the tumoral stage and grade and to identify the patient categories that might benefit from the non-invasive nature of NMP22® BladderChek® test. Methods: Voided urine samples from 266 patients with imagistic suspicion of bladder cancer were collected to perform the NMP22® BladderChek® test. The nuclear matrix protein 22 (NMP22) levels were measured by a lateral flow immunochromatographic qualitative assay, using 10 U/ml as the cut-off value. After this patients underwent transurethral resection of bladder tumors (TUR-BT) follewed by histologic grading and tumor staging for a proper and optimal patient management. Sensitivity specificity and positive predictive value of the NMP22® BladderChek® test were defined for different tumoral stage and grade. Results: Two hundred thirty-eight of the 265 patients had urothelial malignancies (76 pTa, 81 pT1, 37 pT2, 32 pT3, 12 pT4, 27 pT0; 118 G1, 54 G2, 64 G3). The sensitivity was 0.629 [0.612; 0.629] for the NMP22® BladderChek® test while the specificity was equal to 1 [0.851; 1]. Positive predictive values was 1 [0.973; 1], and the negative predictive value was 0.235 [0.200; 0.235]. Conclusions : The results demonstrate that the even if the NMP22® BladderChek® is an easily applied test, giving diagnostic findings within 30 min, cannot be recommended for screening or surveillance in clinical routine use in non muscle invasive bladder cancer because of its poor sensitivity.

Early Arthritis: A Rapid and Sustained Response to Treatment over one Year Follow-up

Abstract: Aim : We aimed to assess the evolution in a group of patients diagnosed with early arthritis, by using clinical outcome measures and to find possible predictors for the clinical response. Methods : The study was conducted in the Rheumatology Department between January 2010 - December 2011. Thirty-six patients between 18-75 years of age with arthritis of at least one peripheral joint less then 12 months duration were consecutively included; other definite causes for arthritis were clinically excluded. The visits were performed at baseline, 3, 6 and 12 months. Clinical examination and biological investigations related to the disease activity were performed. Clinical remission and the EULAR (“European League Against Rheumatism”) response criteria were assessed based on the disease activity score 28 (DAS28). Results : At baseline 91.67% of patients received treatment indication with disease modifying antirheumatic drugs. A significant decrease in the number of tender, swollen joints, erythrocyte sedimentation rate was obtained at 3 months (p<0.001). The mean DAS28 decreased from 5.02±1.31 at baseline to 3.54±1.36 at 3 months (p<0.001). At 3 months, 33.3% of patients were good and 50% moderate responders (p<0.001), while at 6 months 47.2% were good and 33.3% moderate responders (p<0.001). Remission and low disease activity were achieved by 47.2% of patients at 3 and 12 months. Conclusions : A rapid response to treatment was obtained at 3 months. Low disease activity and remission were achieved by almost a half of patients at each visit. The favorable response rate was preserved at 6 and 12 months of follow-up.

Simple Machines Forum, a Solution for Dialogue Optimization between Physicians

Abstract: We developed an instrument which can ensure a quick and easy dialogue between the physicians of the Oncology Institute and family physicians. The platform we chose was Simple Machines Forum (abbreviated as SMF), a free Internet forum (BBS - Bulletin Board System) application. The purpose of this article is not to detail the software platform, but to emphasize the facilities and advantages of using this solution in the medical community.