Scientific Research Publishing

Rodrigues, F., Ortelli, N., Bierlaire, M. and Pereira, F.C. (2022) Bayesian Automatic Relevance Determination for Utility Function Specification in Discrete Choice Models. IEEE ...

ABSTRACT: In the world of Material Informatics (MI), conventional methods involve tremendous laboratory work or extensive simulations that may not yield the expected results. Our objectives are to ...
GitHub

ECS7020P Principles of Machine Learning - Mini Project

This repository contains the mini project for the ECS7020P Principles of Machine Learning course at Queen Mary University of London. This project develops an automated song recognition system capable ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
ahajournals.org

Abstract Wed136: Integration of Mechanistic Fontan Circulatory Models with Interpretable Machine Learning Classifiers

Abstract Wed136: Integration of Mechanistic Fontan Circulatory Models with Interpretable Machine Learning Classifiers Noah Schenk, BS, Alexander Egbe, MD, MPH, Brian Carlson, PhD, and Daniel Beard, ...
ascopubs.org

Bayesian Counterfactual Machine Learning Individualizes Radiation Modality Selection to Mitigate Immunosuppression

Tumor Site–Specific Radiation-Induced Lymphocyte Depletion Models After Fractionated Radiotherapy: Considerations of Model Structure From an Aggregate Data Meta-Analysis Lymphocytes play critical ...
Frontiers

Optimized prediction of diabetes complications using ensemble learning with Bayesian optimization: a cost-efficient laboratory-based approach

Background and objective: The increasing global prevalence of diabetes has led to a surge in complications, significantly burdening healthcare systems and affecting patient quality of life. Early ...
IEEE

A Performance Comparison Between Machine Learning, Deep Learning, and Bayesian Approaches for COVID-19 Diagnosis

Abstract: The COVID-19 pandemic emphasizes the critical need for rapid and reliable diagnostic procedures to improve infection detection and prevention. This study compares Machine Learning (ML), Deep ...