The goal of the heart disease prediction project is to use machine learning and deep learning techniques to create an accurate and efficient system. To obtain insights into the dataset, the project ...

While traditional landslide prediction methods often rely solely on rainfall intensity, the new approach integrates various water-related processes with a machine-learning model.

The newly developed intervention, called MODERN (Machine-learning-assisted Optimizing Dietary intERvention against demeNtia risk), was introduced in a paper in Nature Human Behavior.

Doctors at Northwell Health in New York are using mammograms to help identify women at risk for heart disease.

Machine learning models using step count data of the two preceding weeks were able to predict hospitalization in the upcoming week for patients during systemic therapy, but not other adverse events.

Navigating TAVR Failure Using App-Guided Decision Making Case 2: Flail MV with Shock in a Non-operative Patient Within the prior 24 months, I have had a financial relationship with a company producing ...

Saliva analysis could reveal risk of developing cancer, heart disease or Parkinson's using molecular markers by University of the Basque Country edited by Gaby Clark, reviewed by Andrew Zinin ...

In an analysis published in the journal Heart, researchers report heightened risks of stroke, acute coronary syndrome, and death from cardiovascular disease associated with frequent cannabis use.

An experimental study shows that already small-scale quantum computers can boost the performance of machine learning algorithms.

SAVANA uses a machine learning algorithm to identify cancer-specific structural variations and copy number aberrations in long-read DNA sequencing data. The complex structure of cancer genomes ...

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...