Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

A large real-world clinical trial has found that a generative AI-powered support tool used to support frontline clinicians was safe and improved the quality of clinical decision-making, but did not ...

Each year in the U.S., more than 300,000 people die from sudden cardiac arrest, a condition in which the heart's electrical ...

ML algorithms were trained using the earlier HRQoL assessment and clinical data to predict dichotomized impairments in QLQ-C30 domains at the later assessment between 2 weeks and 5 years ahead, ...

Abstract: The growing use of Internet of Things (IoT) technologies has helped organizations to gather huge amounts of real-time information that has disrupted the operational decision-making systems.

Objectives We validate a machine learning-based sepsis-prediction algorithm (InSight) for the detection and prediction of three sepsis-related gold standards, using only six vital signs. We evaluate ...

aDepartment of Medicine, University of California San Francisco, San Francisco, CA, USA bDepartment of Medicine, University of California Los Angeles, Los Angeles, CA, USA cDepartment of Medicine, ...

To develop and internally validate a machine learning (ML) model that identifies older outpatients with MCI using routine electronic health record (EHR) data. We conducted a retrospective ...

Polygenic risk scores (PRSs) aggregate genetic information to estimate individual predisposition to a trait. While most PRSs model the phenotypic mean, patterns of variability can also be informative ...

Claire Price, a PhD student in health sciences, has been focusing on quantifying weight loss prior to pancreatic cancer diagnosis, to help improve early detection while embracing the principles of ...

Nanotechnology Research Laboratory, Research School of Chemistry, College of Science, The Australian National University, Canberra, ACT 2601, Australia School of Engineering and Technology, The ...

This model was trained and tested on a 70%/30% split (train/test result cohort), achieving an area under the receiver operator curve on the test set of 0.866 (95% CI, 0.857 to 0.875). Assigning a ...