Medicolegal

Deep learning integrated plasmonic electrochemical sensing for fast and accurate pathogen detection.

The development of plasmonic electrochemical biosensors using the new generation of deep learning algorithms is a potent pathway toward the troublesome, immediate and field-mediable diagnostics of the pathogen. This article provides a combination of a MobileNet-Transformer and Gated Recurrent Unit (GRU) deep neural network with a nanostructured plasmonic biosensor designed to sense Escherichia col...

Ambient AI Scribe Implementation in an Ambulatory Setting in a Single Medical Group: Prospective Study.

BACKGROUND: Health care providers spend an excessive amount of time within electronic medical record (EMR) systems documenting patient encounters, often amounting to hours of work outside of regular office hours. This affects physician productivity and directly contributes to burnout. Artificial intelligence (AI) is becoming more integrated into medical care, including the development of speech re...

The reproducibility gap in graph neural network workflows for cell dynamics: A checklist-driven case study.

As part of a Global BioImage Analysts' Society (GloBIAS) initiative, we evaluated the reproducibility of a Graph Neural Network (GNN) study on cell dy...

[Keeping track of things: large language models for patient synopses : Source-bound system for clinical information systems].

BACKGROUND: The increasing documentation burden in electronic health records makes it difficult to obtain a rapid overview of relevant prior informati...

CTE has multiple pathologic variants that might relate to different clinical symptom presentation.

Chronic traumatic encephalopathy (CTE) is a progressive neurodegenerative disease found in individuals with a history of repetitive head injury (RHI) ...

Automated Summarization of Military Medical Records Using AI: Evaluation Via the OPTICA Framework.

INTRODUCTION: Military medical fitness evaluations require physicians to rapidly review extensive and heterogeneous medical records to determine servi...

Artificial intelligence in clinical occupational therapy: Current and future applications and practitioner insights.

BackgroundOccupational therapy practitioners (OTPs) are increasingly using artificial intelligence (AI) in various settings to enhance evaluation, int...

Barriers and facilitators to developing and implementing artificial intelligence-based clinical decision support in the emergency department: a qualitative study.

OBJECTIVES: This study examined why artificial intelligence (AI)-based clinical decision support tools have had limited clinical translation in the em...

Assessing cost overrun in the saudi arabian building construction projects for value preservation.

The pervasive issue of cost overruns remains a significant barrier to ensuring project success within budget and schedule constraints. While the cause...

AI in the NICU: Considerations for Nursing Practice and Advocacy in Quality Care Outcomes for Patients and Families.

BACKGROUND: Neonatal nurses and APRNs may not recognize when AI drives an alert, recommendation, or summary unless training and policy make it explici...

Sweat and air permeable electronics enabled by engineered hierarchical fabric system for exercise management.

Scientific exercise monitoring is significant for injury risk prevention and training outcome promotion. Wearable biosensing technologies have emerged...

Sulfur-Induced Shape Compliance Modulates Fe Catalyst Agglomeration in Carbon Nanotube Growth.

Large-scale carbon nanotube (CNT) synthesis based on floating catalyst chemical vapor deposition (FC-CVD), unlike conventional CVD, utilizes a growth ...

Automating standardization of prostate cancer biopsy and histopathology reports with privacy-preserving local large language models.

PURPOSE: Large-scale biomedical analysis in prostate cancer requires structured, tabular datasets, yet most clinical documentation remains in free-tex...

Local performance and fairness testing of an AI Scribe in a paediatric developmental assessment clinic in South Australia: a silent trial protocol.

INTRODUCTION: Any tool that can reduce the administrative burden on healthcare providers while preserving safe, accountable and high-quality medical d...

Regulating digital surgery to balance safety and innovation: a SAGES white paper.

BACKGROUND: Digital surgery technologies, including robotic systems, artificial intelligence (AI) algorithms, augmented reality platforms, and advance...

Incorporating dietary information to enhance polygenic prediction models with applications to body mass index and type 2 diabetes.

BACKGROUND: Polygenic predictors can enhance screening for metabolism-related traits such as body mass index (BMI) and type 2 diabetes (T2D). However,...

Automated extraction of colonoscopy quality indicators from free-text reports using a prompt-based large language model pipeline.

BACKGROUND AND AIMS: Artificial intelligence has increasingly enabled large-scale analysis of clinical documentation, offering new opportunities to im...

Probing Ink Evaporation-Deposition Behavior for Scalable Catalyst-Layer Fabrication in PEM Electrolysis: Systematic Droplet Metrology Coupled with Explainable Machine Learning.

Nonuniform catalyst-ink deposition during droplet drying, such as coffee-ring formation, remains a key bottleneck for scalable fabrication of proton e...

Radiomics-enhanced 18F-AV45 PET/MRI for integrative assessment and centiloid estimation of amyloid-β burden in Alzheimer's disease.

OBJECTIVE: Reliable assessment of cerebral amyloid-β (Aβ) deposition is essential for the diagnosis and management of Alzheimer's disease (AD). This s...

A selective deep learning framework for pressure injury staging with calibrated confidence and automated clinical documentation.

OBJECTIVES: Pressure injuries are common chronic wounds that require accurate staging to guide management. Deep learning has shown promise for automat...