With the right prompts, AI chatbots can analyze biomedical big data accurately

In an early test of how AI can be used to decipher large amounts of health data, researchers at UC San Francisco and Wayne State University found that generative AI tools could perform orders of ...

AI in neonatal intensive care units: Investigating its use and impact

A team of researchers from the SABIEN group at the ITACA Institute of the Universitat Politècnica de València (UPV) has led an international study that comprehensively analyzes the use and impact of ...

Q&A: Algorithm achieves near end-to-end genome assembly without ultra-long DNA sequencing

Haoyu Cheng, Ph.D., assistant professor of biomedical informatics and data science at Yale School of Medicine, has developed a new algorithm capable of building complete human genomes using standard ...
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 ...