Latest AI and machine learning research in us health policy for healthcare professionals.
Background High body mass index (BMI) presents a serious and ongoing global health challenge. However, the difficulty of high BMI intervention has not yet been systematically evaluated. Methods We developed a Generative Artificial Intelligence Meta-Evaluation (GAME) framework, which integrated 18 indicators from 4 dimensions, including "Macro-System Level", "Socio-Cultural Level", "Community-Famil...
Fraud in the health landscape is an aggravating issue, with far-reaching consequences burdening the financial stability of the health industry and threatening the quality of medical care. It results from vulnerabilities within the current healthcare framework that are exploited by the fraudsters in their favor. In spite of many developed models that aim to detect fraudulent patterns in insurance c...
Antimicrobial resistance (AMR) threatens antibiotic effectiveness, but quantitatively evaluating stewardship strategies under partial observability an...
The medial prefrontal cortex integrates information about salience and valence of stimuli, including rewarding solutions like alcohol and sucrose, and...
Hospital artificial intelligence (AI) and robotics are spreading unevenly across the United States, yet national evidence on how these technologies ar...
Individualized decision rules (IDRs) have become increasingly prevalent in societal applications such as personalized marketing, healthcare, and publi...
Platelets expire within five days. Blood banks face uncertain daily demand and must balance ordering decisions between costly wastage from overstockin...
Lung cancer is characterized by profound intratumoral and inter-patient heterogeneity, spanning histological subtypes, molecular landscapes, and the t...
Background Clinicians in care management programs are often in low supply relative to patient demand, especially in US Medicaid programs, and must sim...
Introduction Improving the efficiency and accuracy of annotation and extraction of performance data from mouse behavioural tasks will improve both the...
Vision-Language-Action (VLA) models leverage pretrained Vision-Language Models (VLMs) as backbones to map images and instructions to actions, demonstr...
Background and Aims: Choledocholithiasis (CDL) is a common condition that can lead to serious complications, requiring effective risk stratification f...
Background: Nursing documentation patterns may reflect patient acuity and clinical deterioration, yet their prognostic value remains underexplored. We...
This study centers around the design and implementation of the Maya Robot, a portable elephant-shaped social robot, intended to engage with children u...
Artificial intelligence allows automatic extraction of imaging biomarkers from already-acquired radiologic images. This paradigm of opportunistic imag...
Randomized controlled trials estimate average treatment effects, but treatment response heterogeneity motivates personalized approaches. A critical qu...
Accurate prediction of outcomes is crucial for clinical decision-making and personalized patient care. Supervised machine learning algorithms, which a...
Reinforcement learning from human feedback (RLHF) shows promise for aligning diffusion and flow models, yet policy optimization methods such as GRPO s...
Klebsiella pneumoniae is a major causative agent of hospital-acquired infections worldwide, contributing substantially to morbidity, mortality, and he...
Background: Many patients with triple-negative breast cancer (TNBC), particularly those who are older, Black, or insured by Medicaid, do not receive g...