AI Medical Compendium Topic:
Bayes Theorem

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BO-ALLCNN: Bayesian-Based Optimized CNN for Acute Lymphoblastic Leukemia Detection in Microscopic Blood Smear Images.

Sensors (Basel, Switzerland)
Acute lymphoblastic leukemia (ALL) is a deadly cancer characterized by aberrant accumulation of immature lymphocytes in the blood or bone marrow. Effective treatment of ALL is strongly associated with the early diagnosis of the disease. Current pract...

In-depth evaluation of machine learning methods for semi-automating article screening in a systematic review of mechanistic literature.

Research synthesis methods
We aimed to evaluate the performance of supervised machine learning algorithms in predicting articles relevant for full-text review in a systematic review. Overall, 16,430 manually screened titles/abstracts, including 861 references identified releva...

Return of the normal distribution: Flexible deep continual learning with variational auto-encoders.

Neural networks : the official journal of the International Neural Network Society
Learning continually from sequentially arriving data has been a long standing challenge in machine learning. An emergent body of deep learning literature suggests various solutions, through introduction of significant simplifications to the problem s...

Analysis of epidemiological association patterns of serum thyrotropin by combining random forests and Bayesian networks.

PloS one
BACKGROUND: Approaching epidemiological data with flexible machine learning algorithms is of great value for understanding disease-specific association patterns. However, it can be difficult to correctly extract and understand those patterns due to t...

Four-Class Classification of Neuropsychiatric Disorders by Use of Functional Near-Infrared Spectroscopy Derived Biomarkers.

Sensors (Basel, Switzerland)
Diagnosis of most neuropsychiatric disorders relies on subjective measures, which makes the reliability of final clinical decisions questionable. The aim of this study was to propose a machine learning-based classification approach for objective diag...

Weighted Bayesian Belief Network: A Computational Intelligence Approach for Predictive Modeling in Clinical Datasets.

Computational intelligence and neuroscience
There are growing concerns about the mortality due to Breast cancer many of which often result from delayed detection and treatment. So an effective computational approach is needed to develop a predictive model which will help patients and physician...

Systematic evaluation of machine learning algorithms for neuroanatomically-based age prediction in youth.

Human brain mapping
Application of machine learning (ML) algorithms to structural magnetic resonance imaging (sMRI) data has yielded behaviorally meaningful estimates of the biological age of the brain (brain-age). The choice of the ML approach in estimating brain-age i...

Indoor Place Category Recognition for a Cleaning Robot by Fusing a Probabilistic Approach and Deep Learning.

IEEE transactions on cybernetics
Indoor place category recognition for a cleaning robot is a problem in which a cleaning robot predicts the category of the indoor place using images captured by it. This is similar to scene recognition in computer vision as well as semantic mapping i...

Exploration of machine learning methods to predict systemic lupus erythematosus hospitalizations.

Lupus
OBJECTIVES: Systemic lupus erythematosus (SLE) is a heterogeneous disease characterized by disease flares which can require hospitalization. Our objective was to apply machine learning methods to predict hospitalizations for SLE from electronic healt...

Appropriate Supervised Machine Learning Techniques for Mesothelioma Detection and Cure.

BioMed research international
Mesothelioma is a dangerous, violent cancer, which forms a protecting layer around inner tissues such as the lungs, stomach, and heart. We investigate numerous AI methodologies and consider the exact DM conclusion outcomes in this study, which focuse...