Rutgers University

About: Rutgers University is a education organization based out in New Brunswick, New Jersey, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 68736 authors who have published 159418 publications receiving 6713860 citations. The organization is also known as: Rutgers, The State University of New Jersey & Rutgers.

Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems

Abstract: Preface 1 Overview of Learning Systems 1.1 What is a Learning System? 1.2 Motivation for Building Learning Systems 1.3 Types of Practical Empirical Learning Systems 1.3.1 Common Theme: The Classification Model 1.3.2 Let the Data Speak 1.4 What's New in Learning Methods 1.4.1 The Impact of New Technology 1.5 Outline of the Book 1.6 Bibliographical and Historical Remarks 2 How to Estimate the True Performance of a Learning System 2.1 The Importance of Unbiased Error Rate Estimation 2.2. What is an Error? 2.2.1 Costs and Risks 2.3 Apparent Error Rate Estimates 2.4 Too Good to Be True: Overspecialization 2.5 True Error Rate Estimation 2.5.1 The Idealized Model for Unlimited Samples 2.5.2 Train-and Test Error Rate Estimation 2.5.3 Resampling Techniques 2.5.4 Finding the Right Complexity Fit 2.6 Getting the Most Out of the Data 2.7 Classifier Complexity and Feature Dimensionality 2.7.1 Expected Patterns of Classifier Behavior 2.8 What Can Go Wrong? 2.8.1 Poor Features, Data Errors, and Mislabeled Classes 2.8.2 Unrepresentative Samples 2.9 How Close to the Truth? 2.10 Common Mistakes in Performance Analysis 2.11 Bibliographical and Historical Remarks 3 Statistical Pattern Recognition 3.1 Introduction and Overview 3.2 A Few Sample Applications 3.3 Bayesian Classifiers 3.3.1 Direct Application of the Bayes Rule 3.4 Linear Discriminants 3.4.1 The Normality Assumption and Discriminant Functions 3.4.2 Logistic Regression 3.5 Nearest Neighbor Methods 3.6 Feature Selection 3.7 Error Rate Analysis 3.8 Bibliographical and Historical Remarks 4 Neural Nets 4.1 Introduction and Overview 4.2 Perceptrons 4.2.1 Least Mean Square Learning Systems 4.2.2 How Good Is a Linear Separation Network? 4.3 Multilayer Neural Networks 4.3.1 Back-Propagation 4.3.2 The Practical Application of Back-Propagation 4.4 Error Rate and Complexity Fit Estimation 4.5 Improving on Standard Back-Propagation 4.6 Bibliographical and Historical Remarks 5 Machine Learning: Easily Understood Decision Rules 5.1 Introduction and Overview 5.2 Decision Trees 5.2.1 Finding the Perfect Tree 5.2.2 The Incredible Shrinking Tree 5.2.3 Limitations of Tree Induction Methods 5.3 Rule Induction 5.3.1 Predictive Value Maximization 5.4 Bibliographical and Historical Remarks 6 Which Technique is Best? 6.1 What's Important in Choosing a Classifier? 6.1.1 Prediction Accuracy 6.1.2 Speed of Learning and Classification 6.1.3 Explanation and Insight 6.2 So, How Do I Choose a Learning System? 6.3 Variations on the Standard Problem 6.3.1 Missing Data 6.3.2 Incremental Learning 6.4 Future Prospects for Improved Learning Methods 6.5 Bibliographical and Historical Remarks 7 Expert Systems 7.1 Introduction and Overview 7.1.1 Why Build Expert Systems? New vs. Old Knowledge 7.2 Estimating Error Rates for Expert Systems 7.3 Complexity of Knowledge Bases 7.3.1 How Many Rules Are Too Many? 7.4 Knowledge Base Example 7.5 Empirical Analysis of Knowledge Bases 7.6 Future: Combined Learning and Expert Systems 7.7 Bibliographical and Historical Remarks References Author Index Subject Index

Clinical Practice Guidelines From the AABB: Red Blood Cell Transfusion Thresholds and Storage

Abstract: Importance More than 100 million units of blood are collected worldwide each year, yet the indication for red blood cell (RBC) transfusion and the optimal length of RBC storage prior to transfusion are uncertain. Objective To provide recommendations for the target hemoglobin level for RBC transfusion among hospitalized adult patients who are hemodynamically stable and the length of time RBCs should be stored prior to transfusion. Evidence Review Reference librarians conducted a literature search for randomized clinical trials (RCTs) evaluating hemoglobin thresholds for RBC transfusion (1950-May 2016) and RBC storage duration (1948-May 2016) without language restrictions. The results were summarized using the Grading of Recommendations Assessment, Development and Evaluation method. For RBC transfusion thresholds, 31 RCTs included 12 587 participants and compared restrictive thresholds (transfusion not indicated until the hemoglobin level is 7-8 g/dL) with liberal thresholds (transfusion not indicated until the hemoglobin level is 9-10 g/dL). The summary estimates across trials demonstrated that restrictive RBC transfusion thresholds were not associated with higher rates of adverse clinical outcomes, including 30-day mortality, myocardial infarction, cerebrovascular accident, rebleeding, pneumonia, or thromboembolism. For RBC storage duration, 13 RCTs included 5515 participants randomly allocated to receive fresher blood or standard-issue blood. These RCTs demonstrated that fresher blood did not improve clinical outcomes. Findings It is good practice to consider the hemoglobin level, the overall clinical context, patient preferences, and alternative therapies when making transfusion decisions regarding an individual patient. Recommendation 1: a restrictive RBC transfusion threshold in which the transfusion is not indicated until the hemoglobin level is 7 g/dL is recommended for hospitalized adult patients who are hemodynamically stable, including critically ill patients, rather than when the hemoglobin level is 10 g/dL (strong recommendation, moderate quality evidence). A restrictive RBC transfusion threshold of 8 g/dL is recommended for patients undergoing orthopedic surgery, cardiac surgery, and those with preexisting cardiovascular disease (strong recommendation, moderate quality evidence). The restrictive transfusion threshold of 7 g/dL is likely comparable with 8 g/dL, but RCT evidence is not available for all patient categories. These recommendations do not apply to patients with acute coronary syndrome, severe thrombocytopenia (patients treated for hematological or oncological reasons who are at risk of bleeding), and chronic transfusion–dependent anemia (not recommended due to insufficient evidence). Recommendation 2: patients, including neonates, should receive RBC units selected at any point within their licensed dating period (standard issue) rather than limiting patients to transfusion of only fresh (storage length: Conclusions and Relevance Research in RBC transfusion medicine has significantly advanced the science in recent years and provides high-quality evidence to inform guidelines. A restrictive transfusion threshold is safe in most clinical settings and the current blood banking practices of using standard-issue blood should be continued.

The complete DNA sequence of yeast chromosome III.

Abstract: The entire DNA sequence of chromosome III of the yeast Saccharomyces cerevisiae has been determined. This is the first complete sequence analysis of an entire chromosome from any organism. The 315-kilobase sequence reveals 182 open reading frames for proteins longer than 100 amino acids, of which 37 correspond to known genes and 29 more show some similarity to sequences in databases. Of 55 new open reading frames analysed by gene disruption, three are essential genes; of 42 non-essential genes that were tested, 14 show some discernible effect on phenotype and the remaining 28 have no overt function.

Essential versus accessory aspects of cell death: recommendations of the NCCD 2015

Abstract: Cells exposed to extreme physicochemical or mechanical stimuli die in an uncontrollable manner, as a result of their immediate structural breakdown. Such an unavoidable variant of cellular demise is generally referred to as ‘accidental cell death’ (ACD). In most settings, however, cell death is initiated by a genetically encoded apparatus, correlating with the fact that its course can be altered by pharmacologic or genetic interventions. ‘Regulated cell death’ (RCD) can occur as part of physiologic programs or can be activated once adaptive responses to perturbations of the extracellular or intracellular microenvironment fail. The biochemical phenomena that accompany RCD may be harnessed to classify it into a few subtypes, which often (but not always) exhibit stereotyped morphologic features. Nonetheless, efficiently inhibiting the processes that are commonly thought to cause RCD, such as the activation of executioner caspases in the course of apoptosis, does not exert true cytoprotective effects in the mammalian system, but simply alters the kinetics of cellular demise as it shifts its morphologic and biochemical correlates. Conversely, bona fide cytoprotection can be achieved by inhibiting the transduction of lethal signals in the early phases of the process, when adaptive responses are still operational. Thus, the mechanisms that truly execute RCD may be less understood, less inhibitable and perhaps more homogeneous than previously thought. Here, the Nomenclature Committee on Cell Death formulates a set of recommendations to help scientists and researchers to discriminate between essential and accessory aspects of cell death.