CNET

ChatGPT Health: What You're Meant to Use the AI for, and Everything You Should Avoid

A "health-focused experience" inside ChatGPT is designed to help you understand medical information and prepare for ...
University of California, San Francisco

AI Bots Accurately Analyze Big Data Set to Predict Preterm Birth

A team of UCSF researchers successfully tested several mainstream AI agents for the ability to analyze big data on women's ...

Big data and human height: Scientists develop algorithm to boost biobank data retrieval and analysis

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...
IEEE

Development of a Patient Care Cost Prediction Model Using the Light Gradient Boosting Machine (LightGBM) Algorithm

Abstract: The prediction of patient care costs is essential in supporting hospital financial planning and enhancing service transparency. This practical work report presents the development of a cost ...
Journal of Medical Internet Research

Data Poisoning Vulnerabilities Across Health Care Artificial Intelligence Architectures: Analytical Security Framework and Defense Strategies

Objective: This study provides a comprehensive threat analysis of data poisoning vulnerabilities across major health care AI architectures. The goals are to (1) identify attack surfaces in clinical AI ...
The Lancet

Machine learning prediction of 1-year mortality in older patients with heart failure: a nationwide, multicenter, prospective cohort study

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...
Frontiers

Macrovascular complications in type 2 diabetes: a multiregional study in rural Bangladesh

Objectives: To assess the prevalence and determinants of macrovascular complications (coronary artery disease, stroke, and diabetic foot) among adults living with T2DM in rural Bangladesh. Methods: A ...
Journal of Medical Internet Research

Patients’ Experiences With Using a Digital Platform for Chat-Based Consultation in Primary Health Care in Sweden: Qualitative Study

Objective: This study aims to explore patients’ experiences using the digital platform 1177-direkt for chat-based consultations in Swedish primary health care, with a focus on understanding their ...
IEEE

Detection of Referral Inefficiency at First Level Health Facilities in BPJS using the Light Gradient Boosting Machine Algorithm

Abstract: The referral system in the National Health Insurance program aims to optimize the function of First Level Health Facilities as an initial health service filter. However, practice in the ...
Pew Research Center

What the data says about Affordable Care Act health insurance exchanges

Nearly 23 million Americans get health insurance through one of the online “exchanges” (also called “marketplaces”) that operate under the 2010 Affordable Care Act, or ACA. Most receive subsidies from ...
Scientific Research Publishing

Friedman, J. H. (2001). Greedy Function Approximation: A Gradient Boosting Machine. The Annals of Statistics, 29, 1189-1232.

ABSTRACT: Accurate prediction of survey response rates is essential for optimizing survey design and ensuring high-quality data collection. Traditional methods often struggle to capture the complexity ...