Latest AI and machine learning research in us health policy for healthcare professionals.
Operative management of spinal metastatic disease is largely for symptom palliation rather than curative and revolves around the expectation that postoperative survival will exceed recovery time. While several scoring systems and models to predict survival exist, few studies have unified diverse predictors into integrated models to predict short-term postoperative outcomes as indicators of recover...
User experience (UX) as both a vocation and a skillset is currently in the center of a wicked knot: emerging technologies such as generative artificial intelligence (GenAI) and large language models (LLMs) are (for the moment) widely accessible in unprecedented ways and are already heavily integrated into modern workplace practices and educational spaces. Further, workplace demands have led to a c...
BACKGROUND: The oral microbiome plays a pivotal role in the occurrence and progression of dental caries and black stain (BS) pigment. OBJECTIVES: The ...
OBJECTIVES: To introduce a vertically integrated model between a health care service provider and technology developer as a learning accelerator to ad...
BACKGROUND: The Agatston CAC score from CT-calcium scoring (CTCS) is a standard guideline recommended measure for cardiovascular risk assessment that ...
INTRODUCTION: Artificial Intelligence (AI) tools may deliver significant improvements in healthcare and Learning Health Systems are well positioned to...
Rapid evaluation, triage, and transport of patients with stroke for thrombolytics, thrombectomy, and other acute treatments have become a vital part o...
The pervasive implementation of generative AI technology in art and design has made exploring students' learning intentions towards generative art a p...
The paper explores the impact of artificial intelligence (AI) in medicine through a three-dimensional model of medical understanding, which encompasse...
BACKGROUND: Falls and related injuries (FRI) pose a large burden among older adults with depression. Proactively identifying individuals at high FRI r...
Hearing loss affects approximately two thirds of adults in the United States aged 70 years or older and frequently remains untreated despite its well-...
OBJECTIVES: 1. To develop a deep-learning segmentation model for automated measurement of maximal aortic diameter (Dmax) and volumes of aortic dissect...
BACKGROUND & AIMS: Small bowel capsule endoscopy (SBCE) is limited by lengthy, variable interpretation. Artificial intelligence (AI) offers a transfor...
Rice cooking and eating quality (CEQ), a core agronomic trait tied to consumer preference and market value, is regulated by endosperm starch, protein,...
PURPOSE: To develop and validate an AI method for automated quantification of whole-skeleton bone marrow (BM) metabolic activity using Carbon 11 (11C)...
ETHNOPHARMACOLOGICAL RELEVANCE: Eleven Flavored Shenqi Tablets (EFST) is a classical multi-herbal prescription in traditional Chinese medicine, tradit...
The rapid integration of artificial intelligence in healthcare, accelerated by the Trump administration's 2025 AI Action Plan and private sector innov...
Offline reinforcement learning provides the capability to learn a policy only from pre-collected datasets, but its performance is often limited by the...
The principle of (respect for) patient autonomy has traditionally emphasized independence in medical decision-making, reflecting a broader commitment ...
Community Value Prediction (CVP) is an important emerging task in the field of social commerce, which aims to predict the community values. However, d...