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Decision Support Techniques

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Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem.

Artificial intelligence in medicine
OBJECTIVE: Create an efficient decision-support model to assist medical experts in the process of organ allocation in liver transplantation. The mathematical model proposed here uses different sources of information to predict the probability of orga...

A case-based reasoning system based on weighted heterogeneous value distance metric for breast cancer diagnosis.

Artificial intelligence in medicine
OBJECTIVE: We present the implementation and application of a case-based reasoning (CBR) system for breast cancer related diagnoses. By retrieving similar cases in a breast cancer decision support system, oncologists can obtain powerful information o...

A First Step towards a Clinical Decision Support System for Post-traumatic Stress Disorders.

AMIA ... Annual Symposium proceedings. AMIA Symposium
PTSD is distressful and debilitating, following a non-remitting course in about 10% to 20% of trauma survivors. Numerous risk indicators of PTSD have been identified, but individual level prediction remains elusive. As an effort to bridge the gap bet...

Comprehensible knowledge model creation for cancer treatment decision making.

Computers in biology and medicine
BACKGROUND: A wealth of clinical data exists in clinical documents in the form of electronic health records (EHRs). This data can be used for developing knowledge-based recommendation systems that can assist clinicians in clinical decision making and...

Biologically Relevant Heterogeneity: Metrics and Practical Insights.

SLAS discovery : advancing life sciences R & D
Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medic...

A Comparison of a Machine Learning Model with EuroSCORE II in Predicting Mortality after Elective Cardiac Surgery: A Decision Curve Analysis.

PloS one
BACKGROUND: The benefits of cardiac surgery are sometimes difficult to predict and the decision to operate on a given individual is complex. Machine Learning and Decision Curve Analysis (DCA) are recent methods developed to create and evaluate predic...

Neural network prediction of severe lower intestinal bleeding and the need for surgical intervention.

The Journal of surgical research
BACKGROUND: The prognosis for patients with severe acute lower intestinal bleeding (ALIB) may be assessed by complex artificial neural networks (ANNs) or user-friendly regression-based models. Comparisons between these modalities are limited, and pre...

Intelligent Process Abnormal Patterns Recognition and Diagnosis Based on Fuzzy Logic.

Computational intelligence and neuroscience
Locating the assignable causes by use of the abnormal patterns of control chart is a widely used technology for manufacturing quality control. If there are uncertainties about the occurrence degree of abnormal patterns, the diagnosis process is impos...

A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices.

Journal of environmental management
Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain...