Medicolegal

AI in Dental Radiology-Improving the Efficiency of Reporting With ChatGPT: Comparative Study.

BACKGROUND: Structured and standardized documentation is critical for accurately recording diagnostic findings, treatment plans, and patient progress in health care. Manual documentation can be labor-intensive and error-prone, especially under time constraints, prompting interest in the potential of artificial intelligence (AI) to automate and optimize these processes, particularly in medical docu...

Automated Pathologic TN Classification Prediction and Rationale Generation From Lung Cancer Surgical Pathology Reports Using a Large Language Model Fine-Tuned With Chain-of-Thought: Algorithm Development and Validation Study.

BACKGROUND: Traditional rule-based natural language processing approaches in electronic health record systems are effective but are often time-consuming and prone to errors when handling unstructured data. This is primarily due to the substantial manual effort required to parse and extract information from diverse types of documentation. Recent advancements in large language model (LLM) technology...

Flow Matching for Optimal Reaction Coordinates of Biomolecular Systems.

We present flow matching for reaction coordinates (FMRC), a novel deep learning algorithm designed to identify optimal reaction coordinates (RC) in bi...

Artificial intelligence for better goals of care documentation.

OBJECTIVES: Lower rates of goals of care (GOC) conversations have been observed in non-white hospitalised patients, which may contribute to racial dis...

Large Language Models Applied to Health Care Tasks May Improve Clinical Efficiency, Value of Care Rendered, Research, and Medical Education.

Large language models (LLMs) are generative artificial intelligence models that create content on the basis of the data on which it was trained. Proce...

Inclusive AI for radiology: Optimising ChatGPT-4 with advanced prompt engineering.

This letter responds to the article "Encouragement vs. liability: How prompt engineering influences ChatGPT-4's radiology exam performance," offering ...

Diversity, inclusivity and traceability of mammography datasets used in development of Artificial Intelligence technologies: a systematic review.

PURPOSE: There are many radiological datasets for breast cancer, some which have supported the development of AI medical devices for breast cancer scr...

A combined deep learning framework for mammalian m6A site prediction.

N-methyladenosine (m6A) is the most prevalent chemical modification in eukaryotic mRNAs and plays key roles in diverse cellular processes. Precise loc...

Whole Slide Imaging, Artificial Intelligence, and Machine Learning in Pediatric and Perinatal Pathology: Current Status and Future Directions.

The integration of artificial intelligence (AI) into healthcare is becoming increasingly mainstream. Leveraging digital technologies, such as AI and d...

Long-term water quality assessment in coastal and inland waters: An ensemble machine-learning approach using satellite data.

Accurate estimation of coastal and in-land water quality parameters is important for managing water resources and meeting the demand of sustainable de...

Comprehensive analysis and validation of TP73 as a biomarker for calcium oxalate nephrolithiasis using machine learning and in vivo and in vitro experiments.

Calcium oxalate (CaOx) nephrolithiasis constitutes approximately 75% of nephrolithiasis cases, resulting from the supersaturation and deposition of Ca...

Natural Language Processing of Clinical Documentation to Assess Functional Status in Patients With Heart Failure.

IMPORTANCE: Serial functional status assessments are critical to heart failure (HF) management but are often described narratively in documentation, l...

Quantification of Size-Binned Particulate Matter in Electronic Cigarette Aerosols Using Multi-Spectral Optical Sensing and Machine Learning.

To monitor health risks associated with vaping, we introduce a multi-spectral optical sensor powered by machine learning for real-time characterizatio...

Past, Present, and Future: A History Lesson in Artificial Intelligence.

Over the past 5 decades, artificial intelligence (AI) has evolved rapidly. Moving from basic models to advanced machine learning and deep learning sys...

Charting the growth through intelligence: A SWOC analysis on AI-assisted radiologic bone age estimation.

Bone age estimation (BAE) is based on skeletal maturity and degenerative process of the skeleton. The clinical importance of BAE is in understanding t...

Perspective: on the importance of extensive, high-quality and reliable deposition of biomolecular NMR data in the age of artificial intelligence.

Artificial intelligence (AI) models are revolutionising scientific data analysis but are reliant on large training data sets. While artificial trainin...

Generative artificial intelligence (GenAI) and decision-making: Legal & ethical hurdles for implementation in mental health.

This article argues that significant risks are being taken with using GenAI in mental health that should be assessed urgently. It recommends that guid...

Artificial intelligence and informatics in neonatal resuscitation.

Neonatal intensive care unit resuscitative care continually evolves and increasingly relies on data. Data driven precision resuscitation care can be e...

Deep learning-based binary classification of beta-amyloid plaques using 18 F florapronol PET.

PURPOSE: This study aimed to investigate a deep learning model to classify amyloid plaque deposition in the brain PET images of patients suspected of ...

The legal regulation of artificial intelligence in the European Union: A practical guide for radiologists.

The European Union is taking the lead globally on the regulation of Artificial Intelligence (AI) and developing important legislation, namely the AI A...