US Health Policy

Hybrid seed production: new paradigms and challenges in the twenty-first century.

Hybrid seed technology future depends on integrating advanced genomics, AI-driven breeding, and enabling policies to sustainably delivery climate-resilient, high-performing hybrids with broad accessibility and equitable benefits worldwide. Hybrid seeds, which exploit heterosis, have driven agricultural productivity gains since the 1920s. Understanding the genetics and molecular biology of hybrid g...

Bridging Population Patterns and Individual Prediction: Framework for Prospective Multimorbidity Study.

BACKGROUND: Multimorbidity has become a major global public health challenge. However, existing research primarily emphasizes the identification of disease patterns at the population level and lacks the capacity to provide predictive insights into individual future pattern membership. Bridging this gap is crucial for personalized prevention and management. OBJECTIVE: This study aims to propose an ...

From innovation to implementation: Addressing the AI adoption gap in cardiac surgery.

BACKGROUND: While artificial intelligence (AI) is advancing rapidly across cardiovascular medicine, its translation into cardiac surgery remains limit...

European Health Care Professionals' Readiness, Benefits, and Ethical Concerns Regarding Generative AI in Continuing Education.

INTRODUCTION: Generative artificial intelligence (GenAI) tools such as ChatGPT are rapidly transforming health care education. Understanding how healt...

Global patterns and predictors of initial treatment in early rheumatoid arthritis: insights from a multinational machine learning study.

BACKGROUND: Rheumatoid arthritis (RA) treatment guidelines recommend early initiation of disease-modifying antirheumatic drugs (DMARDs), but actual pr...

Evaluation of Otolaryngology Provider Bias in Portal Messaging.

BACKGROUND/OBJECTIVES: Patient messaging portals are widely used in clinical practice and are linked to improved patient outcomes, but they are also a...

Using Machine Learning to Predict Features Within Substance Use Disorder Treatment Service Settings That Increase the Likelihood of Positive Treatment Outcomes.

Given the conceptual issues involved in defining and measuring recovery and accordingly substance use disorder (SUD) treatment outcomes, the role of e...

Enabling digital multifactorial risk assessment in primary care: an umbrella review and recommendations for design and implementation.

OBJECTIVES: To develop recommendations to inform development and integration of predictive digital health and artificial intelligence tools in primary...

Mesocorticostriatal reinforcement learning of state representation and value with implications for the mechanisms of schizophrenia.

Mesocorticostriatal dopamine projections are crucial for value learning, motivational control, and cognitive functions. However, while dopamine's role...

Comparing Logistic Regression and Artificial Neural Network Models for Analyzing Medicare Utilization and Costs Among Older Adults.

BACKGROUND: Artificial neural networks (ANNs) are increasingly applied in health care outcome prediction, yet their relative benefits compared with tr...

Advancing specific local wine identification through integration of ICP-MS mineral wine profiles and Machine Learning: A case study on discrimination among the ten Beaujolais crus.

The Beaujolais vineyard, located in France's Auvergne-Rhône-Alpes region, is internationally recognized for its geological diversity and the strong id...

Exploring key risk factors for loss to follow-up after hospitalization for acute stroke.

BACKGROUND: A significant proportion of stroke patients are lost to follow-up (LTFU) after discharge, which may increase risks of morbidity, mortality...

Touch, Trust, and Truth; Why the Physical Exam Still Matters In the Age of AI: A Framework for the Physical Exam as a Bridge to Trust, Healing, and Increased Patient Adherence.

We aim to demonstrate the therapeutic value of the physical examination beyond its diagnostic function and to examine theoretical pathways that contri...

Longitudinal multisource clinical model for early lung cancer risk stratification and screening.

OBJECTIVES: Lung cancer is the leading cause of cancer-related mortality worldwide, with poor prognosis largely due to late-stage diagnosis. Current s...

Natriuretic peptides and cardiac troponins in hypertension and heart failure: A contemporary review of the evidence.

Hypertension is the second leading cause of heart failure (HF), yet strategies for identifying hypertensive individuals at increased HF risk remain li...

Mitigating OOD overoptimism via in-sample value function in offline reinforcement learning.

Offline Reinforcement Learning (RL) was proposed to learn from pre-recorded decision data without online interactions. In this setting, evaluating out...

Prediction of Postoperative Pancreatic Fistula Occurrence by the Pancreatic Stump Shape and Remnant Pancreatic Volume Measured Using AI-Guided Three-Dimensional Simulation.

BACKGROUND: When three-dimensional computer graphics (3DCG) images are used, artificial intelligence (AI) engines can semiautomatically estimate the p...

AI-Generated Images of Substance Use and Recovery: Mixed Methods Case Study.

BACKGROUND: Images created with generative artificial intelligence (AI) tools are increasingly used for health communication due to their ease of use,...

Practice Pattern Changes After Adoption Of Diagnostic AI Tool Used In Conjunction With Cardiac Imaging.

In 2018, Medicare established coverage and reimbursement for its first service using artificial intelligence (AI): computed tomography (CT) fractional...

ESMO adaptation of Lines of Systemic Therapy (EnLiST): a consensus framework for standardising the designation of lines of therapy in solid tumours.

Enumeration of lines of therapy (LoT) is critical across oncology for ensuring optimal patient care, establishing uniform eligibility for clinical tri...