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Predicting 5-Year EDSS in Multiple Sclerosis with LSTM Networks: A Deep Learning Approach to Disease Progression.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Apr 1, 2025
BACKROUNDS: Multiple Sclerosis (MS) is a neurodegerative disease that is common worldwide, has no definitive cure yet, and negatively affects the individual's quality of life due to disease-related disability. Predicting disability in MS is difficult...
Global disparities in artificial intelligence-based mammogram interpretation for breast cancer: A scientometric analysis of representation, trends, and equity.
European journal of cancer (Oxford, England : 1990)
Apr 1, 2025
BACKGROUND: Breast cancer (BC) is the most frequently diagnosed cancer and the leading cause of cancer death among women worldwide. Artificial intelligence (AI) shows promise for improving mammogram interpretation, especially in resource-limited sett...
Identifying progression subphenotypes of Alzheimer's disease from large-scale electronic health records with machine learning.
Journal of biomedical informatics
Apr 1, 2025
OBJECTIVE: Identification of clinically meaningful subphenotypes of disease progression can enhance the understanding of disease heterogeneity and underlying pathophysiology. In this study, we propose a machine learning framework to identify subpheno...
Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing.
NeuroImage
Apr 1, 2025
Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the a...
A novel skeletal muscle quantitative method and deep learning-based sarcopenia diagnosis for cervical cancer patients treated with radiotherapy.
Medical physics
Apr 1, 2025
BACKGROUND: Sarcopenia is associated with decreased survival in cervical cancer patients treated with radiotherapy. Cone-beam computed tomography (CBCT) was widely used in image-guided radiotherapy. Sarcopenia is assessed by the skeletal muscle index...
Generation of surgical reports for lymph node dissection during laparoscopic gastric cancer surgery based on artificial intelligence.
International journal of computer assisted radiology and surgery
Apr 1, 2025
PURPOSE: This study aimed to develop an artificial intelligence (AI) model for the surgical report output of laparoscopic lymph node dissection in the suprapancreatic region during gastric cancer surgery.
Generalizability of FDA-Approved AI-Enabled Medical Devices for Clinical Use.
JAMA network open
Apr 1, 2025
IMPORTANCE: The primary objective of any newly developed medical device using artificial intelligence (AI) is to ensure its safe and effective use in broader clinical practice.
AI-Enabled Screening for Retinopathy of Prematurity in Low-Resource Settings.
JAMA network open
Apr 1, 2025
IMPORTANCE: Retinopathy of prematurity (ROP) is the leading cause of preventable childhood blindness worldwide. If detected and treated early, ROP-associated blindness is preventable; however, identifying patients who might respond to treatment requi...
Clinical Trial Notifications Triggered by Artificial Intelligence-Detected Cancer Progression: A Randomized Trial.
JAMA network open
Apr 1, 2025
IMPORTANCE: Historically, fewer than 10% of adults with cancer have enrolled in clinical trials. Computational tools have been developed to match patients to trials, but these tools are relevant only when patients need new treatment.
Using 3D Convolutional Neural Network and Corvis ST Corneal Dynamic Video for Detecting Forme Fruste Keratoconus.
Journal of refractive surgery (Thorofare, N.J. : 1995)
Apr 1, 2025
PURPOSE: To evaluate the performance of a three-dimensional convolutional neural network (3D CNN) in detecting forme fruste keratoconus (FFKC).
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