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Exploring the significance of the frontal lobe for diagnosis of schizophrenia using explainable artificial intelligence and group level analysis.
Psychiatry research. Neuroimaging
Mar 13, 2025
Schizophrenia (SZ) is a complex mental disorder characterized by a profound disruption in cognition and emotion, often resulting in a distorted perception of reality. Magnetic resonance imaging (MRI) is an essential tool for diagnosing SZ which helps...
Multi-omics integration and machine learning identify and validate neutrophil extracellular trap-associated gene signatures in chronic rhinosinusitis with nasal polyps.
Clinical immunology (Orlando, Fla.)
Mar 13, 2025
This study aimed to explore the molecular characteristics of neutrophil extracellular traps (NETs) in chronic rhinosinusitis with nasal polyps (CRSwNP). Differentially expressed gene analysis, weighted gene co-expression network analysis, and machine...
Risk of bias assessment of post-stroke mortality machine learning predictive models: Systematic review.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Mar 13, 2025
BACKGROUND: Stroke is a major cause of mortality and permanent disability worldwide. Precise prediction of post-stroke mortality is essential for guiding treatment decisions and rehabilitation planning. The ability of Machine learning models to proce...
DCE-MRI based deep learning analysis of intratumoral subregion for predicting Ki-67 expression level in breast cancer.
Magnetic resonance imaging
Mar 13, 2025
OBJECTIVE: To evaluate whether deep learning (DL) analysis of intratumor subregion based on dynamic contrast-enhanced MRI (DCE-MRI) can help predict Ki-67 expression level in breast cancer.
Machine Learning-Based localization of the epileptogenic zone using High-Frequency oscillations from SEEG: A Real-World approach.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Mar 13, 2025
INTRODUCTION: Localizing the epileptogenic zone (EZ) using Stereo EEG (SEEG) is often challenging through manual analysis. Even methods based on signal analysis have limitations in identifying the EZ, particularly in patients with neocortical epileps...
Artificial Intelligence-Assisted Capsule Endoscopy Versus Conventional Capsule Endoscopy for Detection of Small Bowel Lesions: A Systematic Review and Meta-Analysis.
Journal of gastroenterology and hepatology
Mar 13, 2025
BACKGROUND: Capsule endoscopy (CE) is a valuable tool used in the diagnosis of small intestinal lesions. The study aims to systematically review the literature and provide a meta-analysis of the diagnostic accuracy, specificity, sensitivity, and nega...
Posttraumatic Arthritis After Anterior Cruciate Ligament Injury: Machine Learning Comparison Between Surgery and Nonoperative Management.
The American journal of sports medicine
Mar 13, 2025
BACKGROUND: Nonoperative and operative management techniques after anterior cruciate ligament (ACL) injury are both appropriate treatment options for selected patients. However, the subsequent development of posttraumatic knee osteoarthritis (PTOA) r...
Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Methods.
Tomography (Ann Arbor, Mich.)
Mar 13, 2025
RATIONALE: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response of NAC for patients with LABC before initiating treatment would be valuable to customize therapies and ensure t...
Development and evaluation of a deep learning framework for pelvic and sacral tumor segmentation from multi-sequence MRI: a retrospective study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 13, 2025
BACKGROUND: Accurate segmentation of pelvic and sacral tumors (PSTs) in multi-sequence magnetic resonance imaging (MRI) is essential for effective treatment and surgical planning.
Machine learning-derived diagnostic model of epithelial ovarian cancer based on gut microbiome signatures.
Journal of translational medicine
Mar 13, 2025
BACKGROUND: Prior studies have elucidated that alterations in gut microbiota are associated with a spectrum of tumors and metabolic disorders. However, the diagnostic value of gut microbiota in epithelial ovarian cancer remains insufficiently investi...
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