This rare disease has an especially poor survival rate and few treatment options. The patient could be the first of many to have their lives saved by an AI prediction system, which could ...

Background and Objectives: Chronic kidney disease ... The predictions for ESKD occurring within a 2-year period were better than the most experienced clinician. The work here shows that predictive ...

Objective The aim of this systematic literature review was to provide a comprehensive and exhaustive overview of the use of machine learning ... prediction metrics such as accuracy, sensitivity, ...

SEVEN engineers behind the rise of the artificial intelligence technologies that are revolutionising industries and ...

Machine learning tools can improve personalised prognostication of aggressive skin cancers such as Merkel cell carcinoma, a ...

Discussion: Our results demonstrate that using ... prediction performance. In the future, we hope to replace the repetitive, cumbersome task of manual labeling with more advanced machine automated ...

While ML models are powerful tools for predicting diabetes, their lack of interpretability presents a major challenge for clinical adoption. Healthcare professionals require AI models to not only be ...

AI-enabled ECG biological age (ECG-BA) improves disease risk classification beyond chronological age, enhancing early ...

Antimicrobial resistance is a growing health crisis that could lead to millions of deaths by 2050, according to the World ...

Changes in these factors can play a critical role in disease. Epigenetics involves genetic ... 2004). Caution in using epigenetic therapy is necessary because epigenetic processes and changes ...

Want to know how to lose weight using ... disease. If you’re committed to taking the steps to a leaner physique, then read on for expert advice about how to lose weight using a rowing machine ...