Latest AI and machine learning research in product alert for healthcare professionals.
The field of high-entropy alloy nanoparticles (HEA-NPs) had to move and indeed has moved beyond the early enthusiasm of simply "mixing five or more elements and hoping the configurational entropy will do some magic" in terms of chemical and physical properties. What the 2025 Faraday Discussion made clear is that, at the nanoscale, entropy is often a minor player. Phase stability, structure, and fu...
PURPOSE: Decision-making for orchiectomy following testicular torsion often relies on subjective clinical evaluations. This study investigates the efficacy of machine learning (ML) models in objectively predicting post-torsion testicular viability, aiming to maintain a parenchymal ratio over 80% compared to the contralateral testicle, irrespective of initial appearance and surgical timing. METHODS...
BACKGROUND: Artificial intelligence (AI) and machine learning (ML) are increasingly integrated into healthcare, offering potential advancements in pat...
BACKGROUND: Language barriers in pediatric emergency medicine discharge instructions can impact patient safety, leading to poorer post-discharge outco...
INTRODUCTION: Cochlear implant outcomes vary widely and are difficult to predict, with traditional methods explaining <20% of variance. This study tes...
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia worldwide, with catheter ablation being an effective yet recurrence-prone treatment...
Acute ischemic stroke (AIS) outcomes depend critically on rapid, accurate early diagnosis in the emergency department. Traditional prehospital tools a...
AIM: Tacrolimus dosing in the early post-kidney transplant period is challenging due to a narrow therapeutic index and substantial interindividual pha...
OBJECTIVE: To identify pre-treatment determinants of hypothyroidism and decision regret (DR) following radioiodine (RAI) therapy in Graves' disease (G...
BACKGROUND: Traumatic Brain Injury (TBI) poses a significant public health challenge in India, with nearly 2 million cases annually and limited CT ava...
BACKGROUND: Post-cardiac arrest syndrome carries substantial mortality despite advances in resuscitation. We developed a machine learning model to pre...
OBJECTIVE: Fluoropyrimidines are widely prescribed for colorectal and breast cancers, but are associated with toxicities such as hand-foot syndrome an...
The recurrence of cerebral aneurysms after coil embolization remains a significant concern in clinical practice. This study introduced a novel approac...
Accurate assessment of sperm concentration and motility is critical for the diagnosis and management of male infertility. However, current methods, ma...
The current biodiversity landscape results from hundreds of millions of years of evolution, yet the accumulation of biodiversity has been punctuated b...
The advent of normothermic machine perfusion (NMP) has substantially enhanced liver transplantation outcomes by enabling physiologic preservation and ...
EEG recordings obtained before medication are regarded as valuable biological indicators for depression detection. Currently, depression diagnosis bas...
Knowledge of diet composition and intake levels in beef cattle is valuable for post hoc feed traceability and for more accurate modelling of the diet ...
Assessing small-molecule blood-brain barrier permeability is laborious, yet critical in drug development. Quantitative prediction models are hindered ...
BACKGROUND: Multi-center imaging studies create large-scale data that are useful for identifying pathological patterns and robust training of deep lea...