Medicolegal

The Impact of Collaborative Documentation on Person-Centered Care: Textual Analysis of Clinical Notes.

BACKGROUND: Collaborative documentation (CD) is a behavioral health practice involving shared writing of clinic visit notes by providers and consumers. Despite widespread dissemination of CD, research on its effectiveness or impact on person-centered care (PCC) has been limited. Principles of PCC planning, a recovery-based approach to service planning that operationalizes PCC, can inform the measu...

Opportunity and Opportunism in Artificial Intelligence-Powered Data Extraction: A Value-Centered Approach.

Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatment decisions to be made. This charge is rapidly evolving due to forces such as artificial intelligence (AI), big data (opportunistic imaging, imaging prognostication), and advanced diagnostic technologies. A new modernistic paradigm is emerging whereb...

Emerging investigator series: predicted losses of sulfur and selenium in european soils using machine learning: a call for prudent model interrogation and selection.

Reductions in sulfur (S) atmospheric deposition in recent decades have been attributed to S deficiencies in crops. Similarly, global soil selenium (Se...

Editorial Commentary: The Scope of Medical Research Concerning ChatGPT Remains Limited by Lack of Originality.

There is no shortage of literature surrounding ChatGPT and whether this large language model can provide accurate and clinically relevant information ...

Virtual birefringence imaging and histological staining of amyloid deposits in label-free tissue using autofluorescence microscopy and deep learning.

Systemic amyloidosis involves the deposition of misfolded proteins in organs/tissues, leading to progressive organ dysfunction and failure. Congo red ...

Image-Based Artificial Intelligence in Psoriasis Assessment: The Beginning of a New Diagnostic Era?

Psoriasis, a chronic inflammatory skin disease, affects millions of people worldwide. It imposes a significant burden on patients' quality of life and...

Advancing Tau PET Quantification in Alzheimer Disease with Machine Learning: Introducing THETA, a Novel Tau Summary Measure.

Alzheimer disease (AD) exhibits spatially heterogeneous 3- or 4-repeat tau deposition across participants. Our overall goal was to develop an automate...

A nondestructive technique for the sex identification of third instar Cochliomyia macellaria larvae.

Forensic entomology plays an important role in medicolegal investigations by using insects, primarily flies, to estimate the time of colonization. Thi...

Bridging the Gap: Can Large Language Models Match Human Expertise in Writing Neurosurgical Operative Notes?

BACKGROUND: Proper documentation is essential for patient care. The popularity of artificial intelligence (AI) offers the potential for improvements i...

Latest developments of generative artificial intelligence and applications in ophthalmology.

The emergence of generative artificial intelligence (AI) has revolutionized various fields. In ophthalmology, generative AI has the potential to enhan...

Contribution assessment and accumulation prediction of heavy metals in wheat grain in a smelting-affected area using machine learning methods.

Due to the diverse controlling factors and their uneven spatial distribution, especially atmospheric deposition from smelters, assessing and predictin...

A comprehensive overview of barriers and strategies for AI implementation in healthcare: Mixed-method design.

Implementation of artificial intelligence systems for healthcare is challenging. Understanding the barriers and implementation strategies can impact t...

Botulinum Toxin Type A (BoNT-A) Use for Post-Stroke Spasticity: A Multicenter Study Using Natural Language Processing and Machine Learning.

We conducted a multicenter and retrospective study to describe the use of botulinum toxin type A (BoNT-A) to treat post-stroke spasticity (PSS). Data ...

The real ethical issues with AI for clinical psychiatry.

This article explores the ethical issues arising from ordinary AI applications currently used in mental health care, rather than speculative future sc...

Understanding natural language: Potential application of large language models to ophthalmology.

Large language models (LLMs), a natural language processing technology based on deep learning, are currently in the spotlight. These models closely mi...

Leveraging AI and Machine Learning in Six-Sigma Documentation for Pharmaceutical Quality Assurance.

The pharmaceutical industry must maintain stringent quality assurance standards to ensure product safety and regulatory compliance. A key component of...

Artificial intelligence in colorectal multidisciplinary team meetings. What are the medicolegal implications?

AIM: To give an insight into areas for future development and suggestions in the complexities of incorporation of AI into human colorectal cancer (CRC...

Ethical Implications of Artificial Intelligence in Gastroenterology: The Co-pilot or the Captain?

Though artificial intelligence (AI) is being widely implemented in gastroenterology (GI) and hepatology and has the potential to be paradigm shifting ...

Emergence of Artificial Intelligence and Machine Learning Models in Sudden Cardiac Arrest: A Comprehensive Review of Predictive Performance and Clinical Decision Support.

Sudden cardiac death/sudden cardiac arrest (SCD/SCA) is an increasingly prevalent cause of mortality globally, particularly in individuals with preexi...

ChatGPT in Urology: Bridging Knowledge and Practice for Tomorrow's Healthcare, a Comprehensive Review.

Among emerging AI technologies, Chat-Generative Pre-Trained Transformer (ChatGPT) emerges as a notable language model, uniquely developed through art...