The burden of diabetic foot ulcers (DFU) is exacerbated in diabetic patients with concomitant arteriosclerotic occlusion disease (ASO) in the lower extremities, who experience more severe symptoms and poorer prognoses. The study aims to develop a pre...
Autism spectrum disorder (ASD) presents significant challenges in diagnosis and intervention due to its diverse clinical manifestations and underlying biological complexity. This study explored machine learning approaches to enhance ASD screening acc...
Parkinson's disease (PD) is a neurodegenerative disorder affecting motor control, leading to symptoms such as tremors and stiffness. Early diagnosis is essential for effective treatment, but traditional methods are often time-consuming and expensive....
Early detection of pancreatic cancer (PC) remains challenging largely due to the low population incidence and few known risk factors. However, screening in at-risk populations and detection of early cancer has the potential to significantly alter sur...
BACKGROUND: Male infertility contributes to 20-30% of infertility cases, yet traditional diagnostic and treatment methods face limitations in accuracy and consistency. Artificial intelligence (AI) promises to transform male infertility management wit...
Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association
Apr 4, 2025
BACKGROUND & AIMS: Elemental diets (EDs) have desirable safety and efficacy profiles in several clinical settings partly because of modulation of gut microbiome. Palatability of EDs remains the main barrier to compliance/adherence, and their effect h...
OBJECTIVE: To develop a deep learning (DL) model for the detection of spinal cord (SC) multiple sclerosis (MS) lesions from both sagittal T2 and short tau inversion recovery (STIR) sequences and to investigate whether such a model could improve the p...
OBJECTIVE: To develop an automated method for the joint and consistent evaluation of emphysema and mortality risk that provides quantification of data and model uncertainty.
OBJECTIVES: Machine learning (ML) is an emerging discipline centered around complex pattern matching and large data-based prediction modeling and can improve precision medicine healthcare. Cochlear implants (CI) are highly effective, however, outcome...
Objective: Necrotizing enterocolitis (NEC) is a life-threatening condition in premature infants, where timely diagnosis and intervention are crucial. This study investigated the potential of serum CYP3A4 as an early predictive biomarker for NEC and d...
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