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HealthEvidence-backed gain

Artificial Intelligence-Based Adaptive Simulation Integrated With a Workforce Decision-Support System to Improve Simulated Nursing Leadership Performance: A Randomized Controlled Study

Background The growing integration of artificial intelligence (AI) in healthcare necessitates that nurse leaders develop advanced competencies in decision-making, communication, and data-informed clinical judgment. Traditional simulation-based education, while effective, often relies on fixed scenarios with limited adaptability and minimal real-time decision support. AI-enhanced simulation offers a potential solution by creating responsive, adaptive learning environments that support leadership development. Meth…

Cureus

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Diagnostic Efficiency of Artificial Intelligence Integrated Intraoral Mobile Photographs in Identification of Oral Potentially Malignant Disorders: An Umbrella Review

Evidence-backed gain

Longitudinal symptom severity tracking in vagus nerve stimulation patients: a 2-stage LLM-based pipeline with explainable AI

$A review of digital orthopedic techniques in pre- and intra-operative management of scaphoid fracture$

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A review of digital orthopedic techniques in pre- and intra-operative management of scaphoid fracture

Both readings

Enhancing the Role of Digital Health Navigators With Lived Experience: AI-Assisted Conavigation for Safety, Support, and Engagement

As artificial intelligence (AI) expands across mental health services, questions arise about whether it can replace digital health navigators (DHNs), including those with lived experience. The DHN role generally resists automation because lived experience deepens specific dimensions that AI cannot replicate. Drawing on emerging evidence of AI's limitations in contextual reasoning, cultural sensitivity, and clinical safety, the authors identify where DHNs with lived experience are least substitutable: real-world…

Evidence-backed gain

Multiclass Diagnostic Improvement of Interstitial Cystitis (IC) and Overactive Bladder (OAB) via Machine Learning Pipeline on Surface-Enhanced Raman Spectroscopy (SERS)

Interstitial cystitis (IC) and overactive bladder (OAB) are chronic pelvic conditions with shared symptoms of urinary urgency, increased frequency, and nocturia with pain in the bladder. IC is characterized by bladder pain and inflammation without a clear etiology, whereas OAB involves detrusor overactivity in the absence of infection. Despite this symptomatic overlap, IC and OAB differ in underlying pathophysiology and require distinct treatment and medical care. A specific diagnostic strategy is currently lack…

Evidence-backed gain

Revolutionizing healthcare: the role of artificial intelligence in clinical practice

INTRODUCTION: Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advancements can revolutionize healthcare by integrating it into clinical practice. Reporting AI's role in clinical practice is crucial for successful implementation by equipping healthcare providers with essential knowledge and tools. RESEARCH SIGNIFICANCE: This review art…

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Artificial Intelligence in Mental Health Care: Implications for Psychiatric Mental Health Nursing-A Scoping Review

AI is increasingly being integrated into mental health support, with applications spanning chatbots, large language models, digital therapeutics and clinical decision-support systems. Although these technologies have demonstrated potential to improve access to care and support clinical practice, their implications for psychiatric mental health nursing (PMHN) remain insufficiently synthesized. This scoping review aimed to examine how AI is being applied in mental health care and to synthesize its implications for…

Health

Melanoma Prognostication Using AI-Guided Histopathology

Accurate diagnosis and risk stratification are central for optimal management of patients with melanoma. Current American Joint Committee on Cancer (AJCC) staging systems inadequately stratify patients with clinically meaningful metastatic potential. Manual histopathologic interpretation compounds this limitation, particularly for diagnostically ambiguous lesions at the benign-malignant interface, where concordance is highly variable. This review examines how computational pathology and convolutional neural netw…

Health

Artificial Intelligence Across the Pharmaceutical Life Cycle: Implications for Industry-Based Clinical Pharmacists

Artificial intelligence (AI) is increasingly shaping the pharmaceutical industry. This ACCP commentary examines the implications of AI for industry-based clinical pharmacists across the pharmaceutical life cycle, including drug development, regulatory affairs, medical affairs, health economics and outcomes research, and pharmacovigilance. Artificial intelligence-enabled tools may support target identification, clinical trial design, regulatory intelligence, evidence synthesis, medical content generation, real-wo…

Health

Integrative Single-Cell Transcriptomics, Multi-Omics Analyses, and Computational Pharmacology Reveal Macrophage Heterogeneity and the Putative THBS1-CD36 Axis in Coronary Atherosclerosis

Coronary atherosclerosis (CA) is characterized by profound macrophage heterogeneity that drives plaque progression and vulnerability, yet the precise subpopulations and their niche-specific functions remain incompletely defined. Here, we constructed a single-cell transcriptomic atlas of human CA using dataset GSE131778 and identified six distinct macrophage subpopulations. Among these, the THBS1+ macrophage subset emerged as a terminally differentiated, hypoxia-adaptive population with elevated TGF-β signaling a…

Health

A review on diffusion tensor imaging-based comprehensive intelligent diagnosis of Alzheimer's disease

AI-assisted early diagnosis of Alzheimer's disease (AD) has substantial clinical value, and diffusion tensor imaging (DTI), which captures white matter microstructural alterations, has considerable potential across the AD continuum. However, major barriers to clinical translation remain. This review systematically evaluated the evolution of algorithmic paradigms, the effectiveness of multimodal fusion, and barriers to clinical generalization in DTI-based AD diagnosis. Using an "Input-Model-Fusion" evaluation fra…

Health

Development and validation of VentPilot: an AI-based recommendation system for mechanical ventilation

Background Mechanical ventilation requires repeated adjustment to changing patient physiology, but consistent individualized management remains challenging. We developed VentPilot, an artificial intelligence-based system for recommending ventilator settings, and evaluated it in multicenter retrospective validation cohorts. Methods VentPilot was developed using offline reinforcement learning on high-resolution physiologic and ventilator trajectories from Seoul National University Hospital (SNUH), with a reward co…

Health

Enhancing diagnostic precision for BI-RADS 4a breast nodules: A multimodal AI model integrating ultrasound radiomics, hemodynamic signatures, and clinical profiles

Background Breast Imaging Reporting and Data System (BI-RADS) 4a nodules represent a diagnostic dilemma, with a malignancy rate ranging from 2% to 10%. The majority of these nodules prove benign after biopsy, leading to unnecessary invasive procedures, patient anxiety, and healthcare costs. Current clinical practice lacks a reliable, noninvasive tool to accurately distinguish benign from malignant BI-RADS 4a lesions. Emerging evidence suggests that integrating multiparametric ultrasound data with clinical factor…

Health

Artificial Intelligence Triage of Urgent Versus Non-Urgent CT Brain Findings to Support Expedited Emergency Department Disposition: A Retrospective Validation Study

Objective Evaluate the diagnostic accuracy of an artificial intelligence (AI) model for identifying urgent computed tomography brain (CTB) findings in consecutive emergency department (ED) patients and estimate the proportion eligible for expedited disposition. Methods We retrospectively analysed 3424 consecutive non-contrast CTB scans from adults presenting to a quaternary ED in 2024. The AI model (Harrison Enterprise CTB) classified each scan as "urgent" or "non-urgent." The reference standard was the index co…