The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
IEEE

Predictive Modelling for Early Cervical Cancer Diagnosis using Python – based Machine Learning

Abstract: Cervical Cancer is still a major cause of cancer-related morbidity and mortality in women globally, especially in low and middle financial country where routine screening and diagnostic ...
IEEE

Optimizing Machine Learning-Based Ovarian Cancer Prediction Through Normalization Strategies

Abstract: Ovarian cancer is one of the most challenging cancers to detect early, often leading to poor survival rates. This study explores supervised and unsupervised machine learning and deep ...
Journal of Medical Internet Research

Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...
Medical Xpress

Deep-learning algorithms enhance mutation detection in cancer and RNA sequencing

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic ...
ascopubs.org

Evaluation of de novo oligometastatic, oligorecurrent, and oligoprogressive prostate cancer patients managed with radiation therapy: A multi-institution, real-world dataset.

Prospective monitoring of prostate specific membrane antigen–positive biochemically recurrent prostate cancer (PSMA+ BCR): Preliminary data from 6-month PSMA follow-up.