AI Medical Compendium Topic:
Bayes Theorem

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Challenges and Opportunities for Bayesian Statistics in Proteomics.

Journal of proteome research
Proteomics is a data-rich science with complex experimental designs and an intricate measurement process. To obtain insights from the large data sets produced, statistical methods, including machine learning, are routinely applied. For a quantity of ...

PEPPI: Whole-proteome Protein-protein Interaction Prediction through Structure and Sequence Similarity, Functional Association, and Machine Learning.

Journal of molecular biology
Proteome-wide identification of protein-protein interactions is a formidable task which has yet to be sufficiently addressed by experimental methodologies. Many computational methods have been developed to predict proteome-wide interaction networks, ...

Accurate Physical Property Predictions via Deep Learning.

Molecules (Basel, Switzerland)
Neural networks and deep learning have been successfully applied to tackle problems in drug discovery with increasing accuracy over time. There are still many challenges and opportunities to improve molecular property predictions with satisfactory ac...

Developing stacking ensemble models for multivariate contamination detection in water distribution systems.

The Science of the total environment
This study presents a new stacking ensemble model for contamination event detection using multiple water quality parameters. The stacking model consists of a number of machine learning base predictors and a meta-predictor, and it is trained using cro...

Uncertainty-aware skin cancer detection: The element of doubt.

Computers in biology and medicine
Artificial intelligence (AI)-based medical diagnosis has received huge attention due to its potential to improve and accelerate the decision-making process at the patient level in a range of healthcare settings. Despite the recent signs of progress i...

Estimation and Prediction of Hospitalization and Medical Care Costs Using Regression in Machine Learning.

Journal of healthcare engineering
Medical costs are one of the most common recurring expenses in a person's life. Based on different research studies, BMI, ageing, smoking, and other factors are all related to greater personal medical care costs. The estimates of the expenditures of ...

Comparative analysis of explainable machine learning prediction models for hospital mortality.

BMC medical research methodology
BACKGROUND: Machine learning (ML) holds the promise of becoming an essential tool for utilising the increasing amount of clinical data available for analysis and clinical decision support. However, the lack of trust in the models has limited the acce...

Identification and Prediction of Chronic Diseases Using Machine Learning Approach.

Journal of healthcare engineering
Nowadays, humans face various diseases due to the current environmental condition and their living habits. The identification and prediction of such diseases at their earlier stages are much important, so as to prevent the extremity of it. It is diff...

Machine learning for predicting chronic diseases: a systematic review.

Public health
OBJECTIVES: We aimed to review the literature regarding the use of machine learning to predict chronic diseases.

Effectiveness of Artificial Intelligence Models for Cardiovascular Disease Prediction: Network Meta-Analysis.

Computational intelligence and neuroscience
Heart failure is the most common cause of death in both males and females around the world. Cardiovascular diseases (CVDs), in particular, are the main cause of death worldwide, accounting for 30% of all fatalities in the United States and 45% in Eur...