Medicolegal

The Pediatric Surgeon's AI Toolbox: How Large Language Models Like ChatGPT Are Simplifying Practice and Expanding Global Access.

INTRODUCTION: Pediatric surgeons face substantial administrative workload. Large language models (LLMs) may streamline documentation, family communication, rapid reference, and education, but raise concerns about accuracy, bias, and privacy. This review summarizes practical, near-term uses with clinician oversight. MATERIALS AND METHODS: Narrative review of LLMs in pediatric surgical workflows and...

Preserving bloodstain evidence: Completely non-destructive estimation of time-since-deposition with ATR-FTIR spectroscopy and chemometrics.

Determining the time since deposition (TSD) of bloodstains is critical for reconstructing events in forensic investigations. However, traditional methods often involve destructive techniques that compromise evidence integrity. This study demonstrates the feasibility of attenuated total reflectance-Fourier transform infrared (ATR-FTIR) spectroscopy combined with chemometrics for non-destructive TSD...

A Datasheet for Age-Related Eye Disease Study 2 on the Database of Genotypes and Phenotypes.

OBJECTIVE: To provide a comprehensive summary of the controlled-access Age-Related Eye Disease Study 2 (AREDS2) data elements, encompassing phenotypic...

From promise to practice: A roadmap for artificial intelligence in critical care.

Artificial intelligence (AI) has regained strong momentum in medicine, driven by unprecedented computing power and the availability of massive clinica...

Utilization of an Artificial Intelligence-Based Documentation System Improves Provider Efficiency in Outpatient Orthopaedic Clinics: Reducing the Afterhours Burden of the Electronic Health Record-A Pilot Study.

INTRODUCTION: Despite recent technological advancements, documentation within the electronic health record (EHR) remains a time-consuming task within ...

EFLM checklist for the assessment of AI/ML studies in laboratory medicine: enhancing general medical AI frameworks for laboratory-specific applications.

The integration of artificial intelligence (AI) and machine learning (ML) into laboratory medicine shows promise for advancing diagnostic, prognostic,...

An emerging machine learning-optimized MIP-ECL platform for ultrasensitive and selective detection of 5-hydroxytryptamine.

Accurate detection of 5-hydroxytryptamine (5-HT) is essential for the diagnosis and treatment of clinical depression. A functionalized film was fabric...

Generative AI in perioperative medicine and anesthesiology: ethical integration, educational innovation, and the future of clinical professionalism.

Generative artificial intelligence (AI) is rapidly transforming perioperative medicine, particularly anesthesiology, by enabling novel applications, s...

Medical Apps for Physicians: Leveraging MHealth to Enhance Healthcare.

Mobile health (mHealth) leverages mobile technologies, including smartphones, wearables, and apps, to support clinical care, administration, education...

A deep learning-clinical nomogram hybrid for predicting sentinel lymph node metastasis in melanoma.

BACKGROUND: Melanoma is a life-threatening skin malignancy, with sentinel lymph node metastasis (SLNM) serving as a critical prognostic factor. While ...

Big Data in Neurosurgery: A Guideline on Data Structures, Machine Learning Models, and Ethical Considerations.

Artificial intelligence (AI) is reshaping neurosurgery, offering unprecedented opportunities to enhance diagnostics, personalize treatment, and predic...

Artificial Intelligence for Knee Osteoarthritis Care and Rehabilitation: A Systematic Review.

OBJECTIVES: To explore how artificial intelligence (AI) can improve the clinical and rehabilitation management of knee osteoarthritis (KOA), emphasizi...

Surgeon, Trainee, or GPT? A Blinded Multicentric Study of AI-Augmented Operative Notes.

OBJECTIVES: Clear, complete operative documentation is essential for surgical safety, continuity of care, and medico-legal standards. Large language m...

Perovskite Neuromorphic Engine for Transformer Architectures.

Memristive computing refers to the hardware implementation of artificial neural networks (ANNs) by employing memristive devices. It supports analog mu...

Prediabetes phenotypes: can aetiology and risk profile guide lifestyle strategies for diabetes prevention?

INTRODUCTION: Type 2 diabetes (T2D) continues to worsen globally alongside rise in obesity. Asymptomatic dysglycaemia, which precedes T2D, provides op...

SynergyBug: A deep learning approach to autonomous debugging and code remediation.

Bug detection and resolution are pivotal to maintaining the quality, reliability, and performance of software systems. Manual debugging, along with tr...

How machine learning on real world clinical data improves adverse event recording for endoscopy.

Endoscopic interventions are essential for diagnosing and treating gastrointestinal conditions. Accurate and comprehensive documentation is crucial fo...

Machine learning combined with the PMF model reveals the sources and driving factors of PAHs and Cl-PAHs in urban runoff.

Urban rainwater runoff is an important source of nonpoint source pollution due to its transport of diverse contaminants, including polycyclic aromatic...

MMDental - A multimodal dataset of tooth CBCT images with expert medical records.

In the rapidly evolving field of dental intelligent healthcare, where Artificial Intelligence (AI) plays a pivotal role, the demand for multimodal dat...

Current Research and Development in the Field of Magnetic Resonance Contrast Media.

The next-generation, high relaxivity, gadolinium-based contrast agents (GBCAs) are discussed, together with new studies of safety, improvements in MR ...