Artificial Intelligence Medical Compendium

Effective referral triage in pain medicine is essential to ensure that patients receive timely and appropriate care. This study presents a multistage machine learning framework to better identify patients who may benefit from one of five specialised ... read more 

PURPOSE: This study proposes the development of "Motion-DSD", an artificial intelligence-assisted workflow for digital smile design (DSD), which enables a dynamic 2-dimensional (2D) simulation of digital diagnostic waxing by transferring an intraoral... read more 

Accurate rainfall forecasting is a critical component of climate analysis and disaster management, directly influencing agricultural planning, water resource management, and flood mitigation strategies. In this study, we propose an efficient MonoGRU ... read more 

OBJECTIVES: Generative AI chatbots are revolutionizing health education by making complex information more accessible to the public. However, their use presents risks, including bias, hallucinations, ethical concerns, and misinformation, which are pa... read more 

OBJECTIVES: Management of patients with vestibular schwannoma (VS) relies on precise tumor size and growth trend evaluation. We introduce and evaluate a novel computer-assisted reporting tool for clinical decision support during multidisciplinary tea... read more 

OBJECTIVES: The increasing volume of clinical trial documents presents a significant challenge for biomedical researchers who must analyze vast amounts of unstructured and structured data. Traditional methods are no longer feasible given the scale an... read more 

The successful use of deep learning in computational biology depends on the ability to extract meaningful biological information from the trained models. Recent work has demonstrated that the attention maps generated by self-attention layers can be i... read more 

BACKGROUND: The platelet to white blood cell ratio (PWR) has shown prognostic value in many diseases. Yet its predictive utility for patients with atherosclerotic cardiovascular disease (ASCVD) who receive care in the intensive care unit (ICU) remain... read more 

OBJECTIVES: This study aimed to assess the feasibility and practical utility of using large language models (LLMs) for Logical Observation Identifiers Names and Codes (LOINC) mapping to standardise healthcare data in the field of laboratory medicine.... read more 

BACKGROUND: Response to transcranial magnetic stimulation (TMS) in major depressive disorder (MDD) is highly variable, underscoring the need for biomarkers that both predict treatment efficacy and elucidate underlying neural mechanisms. METHODS: We i... read more