The UK Deceased Donor Kidney Transplant Outcome Prediction (UK-DTOP) Tool, developed using advanced artificial intelligence (AI), significantly enhances the prediction of outcomes for deceased-donor kidney transplants in the UK. This study analyzed d...
INTRODUCTION AND OBJECTIVES: Sri Lankans do not have a specific cardiovascular (CV) risk prediction model and therefore, World Health Organization(WHO) risk charts developed for the Southeast Asia Region are being used. We aimed to develop a CV risk ...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Oct 21, 2024
The increasing torrents of health AI innovations hold promise for facilitating the delivery of patient-centered care. Yet the enablement and adoption of AI innovations in the healthcare and life science industries can be challenging with the rising c...
BACKGROUND: Machine learning (ML) may provide novel insights into data patterns and improve model prediction accuracy. The current study sought to develop and validate an ML model to predict early extra-hepatic recurrence (EEHR) among patients underg...
International journal of medical informatics
Oct 18, 2024
OBJECTIVE: Predicting mortality risk following orthopedic surgery is crucial for informed decision-making and patient care. This study aims to develop and validate a machine learning model for predicting one-year mortality risk after orthopedic hospi...
The 9th German Pharm-Tox Summit (GPTS) and the 90th Annual Meeting of the German Society for Experimental and Clinical Pharmacology and Toxicology (DGPT) took place in Munich from March 13-15, 2024. The event brought together over 700 participants fr...
Multiple sclerosis and related disorders
Oct 16, 2024
BACKGROUND: Multiple sclerosis (MS) is an autoimmune disease that can increase the risk of falls in patients due to various factors. Traditional clinical assessments may not effectively identify those at risk of falling.
Thyroid : official journal of the American Thyroid Association
Oct 15, 2024
Thyroid nodules are challenging to accurately characterize on ultrasound (US), though the emergence of risk stratification systems and more recently artificial intelligence (AI) algorithms has improved nodule classification. The purpose of this stud...
BACKGROUND: Beatriz Nistal-Nuño designed a machine learning system type of ensemble learning for patients undergoing cardiac surgery and intensive care unit cardiology patients, based on sequences of cardiovascular physiological measurements and othe...
BACKGROUND: Multiple artificial intelligence (AI) systems have been approved to risk-stratify thyroid nodules through sonographic characterization. We sought to validate the ability of one such AI system, Koios DS (Koios Medical, Chicago, IL), to aid...