Medicaid

Increasing Large Language Model Accuracy for Care-Seeking Advice Using Prompts Reflecting Human Reasoning Strategies in the Real World: Validation Study.

BACKGROUND: Current prompting techniques for large language models (LLMs), such as ChatGPT, mainly focus on well-structured, low-uncertainty problems; yet, many real-world tasks (eg, care-seeking decisions) are ill-defined and involve high uncertainty. Naturalistic decision-making (NDM) specifically analyzes how humans make accurate decisions in such settings, but NDM concepts have not yet been ap...

Using natural language processing to assess MDD psychotherapy patterns among Veterans Affairs patients with suicide risk.

Major depressive disorder (MDD) is a leading risk factor for suicide. Within the US Department of Veterans Affairs (VA), psychotherapy is widely used to treat MDD and prevent suicide. Little is known about how classified suicide risk impacts this treatment. Addressing this gap, this study assesses patterns in MDD-diagnosed VA patients' unstructured electronic health record (EHR) notes using Latent...

The Patient Monitoring Roundtable as Catalyst for Health Care Innovation: Case Study.

BACKGROUND: In the field of patient monitoring, there often remains a gap between clinical needs and the monitoring technologies available from indust...

A Machine Learning Model to Improve Risk Adjustment Accuracy in Medicare.

OBJECTIVE: To develop a machine learning (ML) algorithm that improves accuracy compared to the Hierarchical Condition Category (HCC) score used by the...

Eliminating Nonvalue-Added Tasks in Health Care: Artificial Intelligence in the Orthopedic Office.

PURPOSE: This study examines the efficiency and proof-of-concept use of a generative artificial intelligence (AI) documentation prototype, evaluating ...

Artificial Intelligence-Assisted Ultrasound in Austere Trauma Environments: Implications for Role 1 Military Medicine.

Pararescue jumpers are United States Air Force medical tactical operators who provide advanced trauma and prolonged casualty care in austere, high-ris...

Integrated Implementation Strategies to Promote the Use of AI-Assisted Diagnostic Software for Lung Nodule Screening in China: Process Evaluation Based on the RE-AIM Framework.

BACKGROUND: While artificial intelligence (AI)-assisted diagnostic software holds promise for improving diagnostic efficiency and reducing disparities...

Evaluating Patient and Professional Satisfaction and Documentation Time Reduction Through AI-Driven Automatic Clinical Note Generation in Primary Care: Proof-of-Concept Study.

BACKGROUND: The workload that stems from writing clinical histories is one of the main sources of stress and overload for primary care professionals, ...

What factors influence patient participation in an artificial intelligence-based initiative to optimise referrals from primary to specialist haematology care? A multicentre retrospective observational study in four Spanish hospitals.

OBJECTIVES: Increasing demand for haematological specialist care makes the optimisation of referrals and outpatient workflow a priority. Automated pla...

The role of artificial intelligence in virtual emergency care: a systematic review.

BACKGROUND: The integration of artificial intelligence (AI) into virtual emergency care represents a potentially transformative approach to healthcare...

Developing a Cross-Device Platform for Robotic Systems in Nursing Care: Mixed Methods Feasibility Study.

BACKGROUND: Aging populations and rising chronic illness prevalences are increasing demands for nursing care, while staff shortages threaten care qual...

Telehealth Approaches for Pediatric Otitis Media and Clinical Outcomes: Scoping Review.

BACKGROUND: Otitis media (OM) is a common pediatric infection worldwide. Conventionally, accurate diagnosis depends on in-person pneumatic otoscopy, w...

Dose-aware diffusion model for 3D PET image denoising: Multi-institutional validation with reader study and real low-dose data.

Reducing scan times, radiation dose, and enhancing image quality, especially for lower-performance scanners, are critical in low-count/low-dose PET im...

AI-enhanced precision: boosting pathologist confidence in HER2 ultra-low diagnosis through intelligent re-screening.

Accurate assessment of Human Epidermal Growth Factor Receptor 2 (HER2) immunohistochemistry (IHC) expression, particularly the precise identification ...

Generating synthetic CEM from low-energy images using deep learning: A future without contrast media? A proof-of-concept study.

OBJECTIVE: We used deep learning to generate synthetic, resembling in appearance, iodine-enhanced, mammograms from low-energy contrast-enhanced mammog...

[Care for uncontrolled asthma in Germany - with focus on Magdeburg and Mannheim regions].

Description of treatment and prescription patterns among asthma patients in the regions of Magdeburg (MD) and Mannheim (MA) compared nationwide.We ana...

Patterns of AI Use in Clinical Work by Hospitalists: Survey Study.

BACKGROUND: Artificial intelligence (AI) tools are widely and freely available for clinical use. Understanding hospitalists' real-world adoption patte...

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...

Effectiveness of natural language intelligence technology in chronic diseases nursing: A systematic review and meta-analysis.

BACKGROUND: Chronic diseases pose a heavy global burden, with challenges in utilizing unstructured data for continuous care. Natural language intellig...

Machine learning-based prediction of disability in subacute low back pain: a primary care study on clinical and psychosocial determinants.

BACKGROUND: Subacute low back pain (LBP) is a highly prevalent condition and a major contributor to disability and health care burden. Early identific...