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Predicting clinical prognosis in gastric cancer using deep learning-based analysis of tissue pathomics images.
Computer methods and programs in biomedicine
Jun 4, 2025
OBJECTIVE: Evaluate the utility of a machine learning-based pathomics model in predicting overall survival (OS) post-surgery for gastric cancer patients.
Radiomics-Based Differentiation of Primary Central Nervous System Lymphoma and Solitary Brain Metastasis Using Contrast-Enhanced T1-Weighted Imaging: A Retrospective Machine Learning Study.
Academic radiology
Jun 4, 2025
PURPOSE: To develop and evaluate radiomics-based models using contrast-enhanced T1-weighted imaging (CE-T1WI) for the non-invasive differentiation of primary central nervous system lymphoma (PCNSL) and solitary brain metastasis (SBM), aiming to impro...
Comparison among artificial intelligence-based age estimation from morphological analysis of the pubic symphysis versus experienced and novice practitioners using a new atlas for component labeling.
International journal of legal medicine
Jun 4, 2025
Traditional age estimation methods based on macroscopic observation has been criticized for being excessively dependent on the observer's experience. The aim of this technical note is to propose a new atlas to assist the forensic practitioner in labe...
Predicting clinical outcomes using 18F-FDG PET/CT-based radiomic features and machine learning algorithms in patients with esophageal cancer.
Nuclear medicine communications
Jun 4, 2025
OBJECTIVE: This study evaluated the relationship between 18F-fluorodeoxyglucose PET/computed tomography (18F-FDG PET/CT) radiomic features and clinical parameters, including tumor localization, histopathological subtype, lymph node metastasis, mortal...
The value of machine learning based on magnetic resonance imaging (MRI) and biopsy whole-slide image to predict pathological complete response to breast cancer after neoadjuvant chemotherapy: a two-centre study.
Clinical radiology
Jun 4, 2025
AIM: To develop and validate a combined model based on magnetic resonance imaging (MRI), and whole-slide imaging (WSI) to predict pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) in breast cancer.
Machine learning-based histopathological features of histological slides and clinical characteristics as a novel prognostic indicator in diffuse large B-cell lymphoma.
Pathology, research and practice
Jun 4, 2025
OBJECTIVE: This study developed and validated a deep learning model based on clinical and histopathological features for predicting the outcomes of diffuse large B-cell lymphoma (DLBCL).
Impact of AI-Generated ADC Maps on Computer-Aided Diagnosis of Prostate Cancer: A Feasibility Study.
Academic radiology
Jun 4, 2025
RATIONALE AND OBJECTIVES: To evaluate the impact of AI-generated apparent diffusion coefficient (ADC) maps on diagnostic performance of a 3D U-Net AI model for prostate cancer (PCa) detection and segmentation at biparametric MRI (bpMRI).
Predicting mortality risk following major lower extremity amputation using machine learning.
Journal of vascular surgery
Jun 4, 2025
OBJECTIVE: Major lower extremity amputation for advanced vascular disease involves significant perioperative risks. Although outcome prediction tools could aid in clinical decision-making, they remain limited. To address this, we developed machine le...
Associations between all-cause and ischemic heart disease mortality and long-term ambient ultrafine particles exposure: a comparison of statistical and machine learning exposure models.
Environment international
Jun 4, 2025
BACKGROUND: Evidence about the health effects of ultrafine particles (UFPs) remains limited, especially due to challenges in estimating exposure in epidemiological studies.
Shotgun Metagenomics Identifies in a Cross-Sectional Setting Improved Plaque Microbiome Biomarkers for Peri-Implant Diseases.
Journal of clinical periodontology
Jun 4, 2025
AIM: This observational study aimed to verify and improve the predictive value of plaque microbiome of patients with dental implant for peri-implant diseases.
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