Latest AI and machine learning research in medicolegal for healthcare professionals.
Background: Formulation, associated with suicide risk assessment, is an individualised process that seeks to understand the idiosyncratic nature and development of an individual's problems. Auditing clinical documentation on an electronic health record (EHR) is challenging as it requires resource-intensive manual efforts to identify keywords in relevant sections of specific forms. Furthermore, c...
This research investigates the application of a hybrid Retrieval-Augmented Generation (RAG) and Generative Pre-trained Transformer (GPT) pipeline for extracting and categorizing substance use information from unstructured clinical notes. The aim is to enhance the accuracy and efficiency of identifying substance use mentions and determining their status in patient documentation. By integrating RAG ...
During the COVID-19 pandemic, artificial intelligence (AI) models were created to address health-care resource constraints. Previous research shows th...
Large language models (LLMs) represent a transformative class of AI tools capable of revolutionizing various aspects of healthcare by generating hum...
The increasing administrative burden of medical documentation, particularly through Electronic Health Records (EHR), significantly reduces the time ...
The application of large language models (LLMs) in healthcare has gained significant attention due to their ability to process complex medical data ...
The exponential growth in computational power and accessibility has transformed the complexity and scale of bioinformatics research, necessitating s...
Abdominal computed tomography (CT) scans are frequently performed in clinical settings. Opportunistic CT involves repurposing routine CT images to e...
Automatic differentiation is everywhere, but there exists only minimal documentation of how it works in complex arithmetic beyond stating "derivativ...
Patient perception involves a patient's thoughts and beliefs regarding their health status. It is also associated with medical compliance and outcomes...
With cancer being a leading cause of death globally, epidemiological and clinical cancer registration is paramount for enhancing oncological care and ...
We provide a realist review of product launches for Large Language Models (LLMs) in the healthcare industry. Through a systematic search in the Factiv...
Generative AI models, such as ChatGPT, have significantly impacted healthcare through the strategic use of prompts to enhance precision, relevance, an...
Etruscan mirrors constitute a significant category in Etruscan art, characterized by elaborate figurative illustrations featured on their backside. ...
This study aimed to develop ICU mortality prediction models using a conceptual framework, focusing on nurses' concerns reflected in nursing records fr...
This paper describes a service learning project used in an upper-level and graduate-level database systems course. Students complete a small databas...
PURPOSE: Stage in multiple myeloma (MM) is an essential measure of disease risk, but its measurement in large databases is often lacking. We aimed to ...
Educating students about academic integrity expectations has been suggested as one of the ways to reduce malpractice in take-home programming assign...
Accurate and comprehensive clinical documentation is crucial for delivering high-quality healthcare, facilitating effective communication among prov...
This paper examines the legal challenges associated with medical robots, including their legal status, liability in cases of malpractice, and concerns...