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Machine-learning assisted discovery unveils novel interplay between gut microbiota and host metabolic disturbance in diabetic kidney disease.
Gut microbes
Mar 6, 2025
Diabetic kidney disease (DKD) is a serious healthcare dilemma. Nonetheless, the interplay between the functional capacity of gut microbiota and their host remains elusive for DKD. This study aims to elucidate the functional capability of gut microbio...
A Preoperative CT-based Multiparameter Deep Learning and Radiomic Model with Extracellular Volume Parameter Images Can Predict the Tumor Budding Grade in Rectal Cancer Patients.
Academic radiology
Mar 6, 2025
RATIONALE AND OBJECTIVES: To investigate a computed tomography (CT)-based multiparameter deep learning-radiomic model (DLRM) for predicting the preoperative tumor budding (TB) grade in patients with rectal cancer.
Leveraging Deep Learning in Real-Time Intelligent Bladder Tumor Detection During Cystoscopy: A Diagnostic Study.
Annals of surgical oncology
Mar 6, 2025
BACKGROUND: Accurate detection of bladder lesions during cystoscopy is crucial for early tumor diagnosis and recurrence monitoring. However, conventional visual inspection methods have low and inconsistent detection rates. This study aimed to evaluat...
How Can Robotic Devices Help Clinicians Determine the Treatment Dose for Post-Stroke Arm Paresis?
Sensors (Basel, Switzerland)
Mar 6, 2025
Upper limb training dose after stroke is usually quantified by time and repetitions. This study analyzed upper limb motor training dose in stroke participants (N = 36) using a more comprehensive approach. Participants, classified by initial motor sev...
Machine Learning Models With Prognostic Implications for Predicting Gastrointestinal Bleeding After Coronary Artery Bypass Grafting and Guiding Personalized Medicine: Multicenter Cohort Study.
Journal of medical Internet research
Mar 6, 2025
BACKGROUND: Gastrointestinal bleeding is a serious adverse event of coronary artery bypass grafting and lacks tailored risk assessment tools for personalized prevention.
Perspectives on Using Artificial Intelligence to Derive Social Determinants of Health Data From Medical Records in Canada: Large Multijurisdictional Qualitative Study.
Journal of medical Internet research
Mar 6, 2025
BACKGROUND: Data on the social determinants of health could be used to improve care, support quality improvement initiatives, and track progress toward health equity. However, this data collection is not widespread. Artificial intelligence (AI), spec...
Preoperative multiclass classification of thymic mass lesions based on radiomics and machine learning.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 6, 2025
BACKGROUND: Apart from rare cases such as lymphomas, germ cell tumors, neuroendocrine neoplasms, and thymic hyperplasia, thymic mass lesions (TMLs) are typically categorized into cysts, and thymomas. However, the classification results cannot be dete...
Combined effects and timing of robotic training and botulinum toxin on upper limb spasticity and motor function: a single‑blinded randomized controlled pilot study.
Journal of neuroengineering and rehabilitation
Mar 6, 2025
BACKGROUND: This study aimed to evaluate the combined effects of robotic training (RT) and botulinum toxin (BTX) injections on motor function and spasticity in individuals with post-stroke upper limb spasticity (ULS). We also sought to investigate th...
Deep learning-based classification of dementia using image representation of subcortical signals.
BMC medical informatics and decision making
Mar 6, 2025
BACKGROUND: Dementia is a neurological syndrome marked by cognitive decline. Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the common forms of dementia, each with distinct progression patterns. Early and accurate diagnosis of dementi...
Artificial intelligence for breast cancer screening in mammography (AI-STREAM): preliminary analysis of a prospective multicenter cohort study.
Nature communications
Mar 6, 2025
Artificial intelligence (AI) improves the accuracy of mammography screening, but prospective evidence, particularly in a single-read setting, remains limited. This study compares the diagnostic accuracy of breast radiologists with and without AI-base...
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