物件導向軟體之架構(Object-Oriented Software Construction)探討

The ongoing coronavirus disease 2019 (COVID-19) pandemic poses a severe threat to public health worldwide. We combine data on demography, contact patterns, disease severity, and health care capacity and quality to understand its impact and inform strategies for its control. Younger populations in lower-income countries may reduce overall risk, but limited health system capacity coupled with closer intergenerational contact largely negates this benefit. Mitigation strategies that slow but do not interrupt transmission will still lead to COVID-19 epidemics rapidly overwhelming health systems, with substantial excess deaths in lower-income countries resulting from the poorer health care available. Of countries that have undertaken suppression to date, lower-income countries have acted earlier. However, this will need to be maintained or triggered more frequently in these settings to keep below available health capacity, with associated detrimental consequences for the wider health, well-being, and economies of these countries.

The impact of COVID-19 and strategies for mitigation and suppression in low- and middle-income countries.

Background Breast cancer is the most common malignancy in women. It is often characterized by a lack of early symptoms, which results in late detection of the disease. Detection at advanced stages of the decease implies the treatment is more difficult and uncertain. The appropriate screening programs have been conducted within the organized preventive examinations and have made significant contributions to the early breast cancer detection. Objective It is necessary to improve the screening process in order to reduce the percentage of female population that is not covered by screening programs and increase the number of early-detected breast cancers. The improvement of the screening program may be reflected in the following: more efficient determination of the list of the women who have to undergo preventive examination, introduction of screening program in thermography as a diagnostic method applied in pre-screening stage, more efficient analysis of mammograms and continuous follow up of patients. Methods The identification of target population for breast cancer screening program has been based on the age of women. The improvement of the early breast cancer diagnosis process proposed in this paper is reflected in more efficient determination of the group of women who have to undergo preventive examination based on the factors affecting the occurrence of breast cancer. Inclusion of the pre-screening phase in which thermal imaging could be applied and software support to mammographic detection of tumor are suggested. Results This paper describes the breast cancer, current screening program and techniques for early-stage breast cancer detection, module of medical information system MEDIS.NET for creating screening list based on the analysis of risk factors affecting the occurrence of breast cancer, mammography and role of thermal imaging in the process of early breast cancer detection. It also presents an overview on important achievements in computer-aided detection and diagnosis of breast cancer in mammography and thermography. Conclusions Based on the obtained results, dynamics of preventive examinations for particular groups of women that is different from the standard two-year examinations, can be successfully defined. It can be concluded that the use of a computer system for tumor diagnosis in mammogram based on various methods of image processing can help doctors in decision-making, while the use of thermal imaging in the pre-screening phase would significantly reduce the list of women for screening mammograms.

Early diagnosis and detection of breast cancer.

Preparation of Carbon Quantum Dots- Quinic Acid for Drug Delivery of Gemcitabine to Breast Cancer Cells

Breast cancer (BC) is positioned as the second among all cancers remaining at the top of women´s diseases worldwide followed by colorectum, lung, cervix, and thyroid cancers. The main drawback of most the screening/diagnostic methods is their low sensitivity/specificity and in some cases the invasive procedure required to obtain the samples. On the present investigation, we report a statistical design was to evaluate by central composite design the influence towards the optimization of the most significant variables of solid-phase microextraction (SPME) procedure for the isolation of volatile organic metabolites (VOMs) from urine of BC patients (N = 31) and healthy individuals (CTL; N = 40). The establishment of the urinary volatomic composition, through gas chromatography-mass spectrometry (GC–MS) analysis, can boost the identification of volatile organic metabolites (VOMs) potential BC biomarkers useful to be used together or to complement the current BC diagnostics tools. Better early detection methods are needed to improve the outcomes of patients with BC. Several combinations of experiments were considered with a central composite design (CCD) of response surface methodology (RSM) for the urinary volatomic pattern. Three-level three-factor CCD was employed assessing the most important extraction-influencing variables—fiber coating, NaCl amount, extraction time and temperature. The optimal conditions were achieved using a carboxen/polydimethylsiloxane fiber with 15% (w/v) NaCl during 75 min at 50 °C. A total of ten VOMs belonging to sulfur compounds, terpenoids and carbonyl compounds presented the highest contribution towards discrimination of BC patients from CTL (variable importance in projection (VIP) > 1, p < 0.05). The discrimination efficiency and accuracy of urinary metabolites was ascertained by receiver operating characteristic (ROC) curve analysis that allowed the identification of some metabolites with highest sensitivity and specificity to discriminate the groups. The results obtained with this approach suggest the possibility to identify endogenous metabolites as a platform to discovery potential BC biomarkers and paves a way to explore the related metabolomic pathways in order to improve BC diagnostic tools.

Implementing a central composite design for the optimization of solid phase microextraction to establish the urinary volatomic expression: a first approach for breast cancer.

Extensions and adaptations of existing medical information system in order to reduce social contacts during COVID-19 pandemic.

This paper presents major challenges and lessons learned during the process
 of including and adapting modern medical informatics concepts in challenging
 circumstances of a health care organization in the Republic of Serbia. The
 processes of choosing the overall software architecture, application
 development and later software deployment are examined, and the most critical
 places (slow network, slow workstations, repetitive data entry, wrong data
 entered, inappropriate and complex GUI, and low IT knowledge of an end-user)
 are pointed out, and the general solving strategies are defined. The
 mentioned strategies are joined together as a general approach for
 maintaining a complete medical information system life-cycle. Eventually,
 this approach provides shorter training, efficient support during deployment,
 more comfortable and efficient work, and makes positive impact on adoption
 process. In a view of this, our main objective is to specify development and
 deployment guidelines that can be applied for the information systems
 developed in different developing countries facing similar problems.

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Developing and deploying medical information systems for Serbian public healthcare: Challenges, lessons learned and guidelines

Checking the potential shift to perceived usefulness-The analysis of users' response to the updated electronic health record core features.

A large number of analyses performed in a biochemical laboratory requires that results of these analyses are automatically acquired from analyzers which can be of different types and produced by various producers. Automatic data acquisition prevents errors which are possible if results are manually transcribed into reports for patients. Beside this, acquired results are saved in database from where they are available to be used in electronic health record (EHR). Above requirement resulted in development of a solution for data acquisition from heterogeneous laboratory analyzers. Here we present the solution which is based on minicomputer Raspberry Pi model B, Raspbian OS, Mono Framework and a .NET Framework 4.0 console application written in C# programming language. Proposed solution is tightly connected with medical information system MEDIS.NET and with laboratory information system LabIS. In order to test whole concept we developed a laboratory simulator which completely implements protocol for biochemical analyzers. The emphasis is on an inexpensive solution which connects a large number of heterogeneous analyzers at a biochemical laboratory.

Aleksandar Milenkovic

Papers

Early diagnosis and detection of breast cancer.

Extensions and adaptations of existing medical information system in order to reduce social contacts during COVID-19 pandemic.

Developing and deploying medical information systems for Serbian public healthcare: Challenges, lessons learned and guidelines

Checking the potential shift to perceived usefulness-The analysis of users' response to the updated electronic health record core features.

Using of Raspberry Pi for data acquisition from biochemical analyzers