AIMC Topic: Decision Support Techniques

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Machine learning and deep analytics for biocomputing: call for better explainability.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The goals of this workshop are to discuss challenges in explainability of current Machine Leaning and Deep Analytics (MLDA) used in biocomputing and to start the discussion on ways to improve it. We define explainability in MLDA as easy to use inform...

Calibration drift in regression and machine learning models for acute kidney injury.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Predictive analytics create opportunities to incorporate personalized risk estimates into clinical decision support. Models must be well calibrated to support decision-making, yet calibration deteriorates over time. This study explored the...

Neural networks as a tool to predict syncope risk in the Emergency Department.

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
AIMS: There is no universally accepted tool for the risk stratification of syncope patients in the Emergency Department. The aim of this study was to investigate the short-term predictive accuracy of an artificial neural network (ANN) in stratifying ...

Computer-Assisted Decision Support for Student Admissions Based on Their Predicted Academic Performance.

American journal of pharmaceutical education
To develop predictive computational models forecasting the academic performance of students in the didactic-rich portion of a doctor of pharmacy (PharmD) curriculum as admission-assisting tools. All PharmD candidates over three admission cycles wer...

Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.

Transplantation
BACKGROUND: The ability to predict graft failure or primary nonfunction at liver transplant decision time assists utilization of scarce resource of donor livers, while ensuring that patients who are urgently requiring a liver transplant are prioritiz...

Effects of Implementing a Tree Model of Diagnosis into a Bayesian Diagnostic Inference System.

Studies in health technology and informatics
To estimate a diagnostic probability similarly to experts using answers to interviews, we developed a system that fundamentally behaves as a Bayesian model. For predefined interviews, we defined the sensitivity and specificity related to one or more ...

Reasoning and Data Representation in a Health and Lifestyle Support System.

Studies in health technology and informatics
Case-based reasoning and data interpretation is an artificial intelligence approach that capitalizes on past experience to solve current problems and this can be used as a method for practical intelligent systems. Case-based data reasoning is able to...

Using a fuzzy comprehensive evaluation method to determine product usability: A proposed theoretical framework.

Work (Reading, Mass.)
BACKGROUND: In order to compare existing usability data to ideal goals or to that for other products, usability practitioners have tried to develop a framework for deriving an integrated metric. However, most current usability methods with this aim r...