AIMC Topic: Retrospective Studies
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Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Jul 7, 2025
OBJECTIVES: The purpose of this study is to mainly develop a predictive model based on clinicoradiological and radiomics features from preoperative gadobenate-enhanced (Gd-BOPTA) magnetic resonance imaging (MRI) using multilayer perceptron (MLP) deep...
Gender difference in cross-sectional area and fat infiltration of thigh muscles in the elderly population on MRI: an AI-based analysis.
European radiology experimental
Jul 7, 2025
BACKGROUND: Aging alters musculoskeletal structure and function, affecting muscle mass, composition, and strength, increasing the risk of falls and loss of independence in older adults. This study assessed cross-sectional area (CSA) and fat infiltrat...
Development and retrospective validation of an artificial intelligence system for diagnostic assessment of prostate biopsies: study protocol.
BMJ open
Jul 7, 2025
INTRODUCTION: Histopathological evaluation of prostate biopsies using the Gleason scoring system is critical for prostate cancer diagnosis and treatment selection. However, grading variability among pathologists can lead to inconsistent assessments, ...
Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cases.
Acta orthopaedica
Jul 7, 2025
BACKGROUND AND PURPOSE: Treatment-related shared decision-making (SDM) in older adults with hip fractures is complex due to the need to balance patient-specific factors such as life goals, frailty, and surgical risks. It includes considerations such...
Performance of GPT-4 for automated prostate biopsy decision-making based on mpMRI: a multi-center evidence study.
Military Medical Research
Jul 7, 2025
BACKGROUND: Multiparametric magnetic resonance imaging (mpMRI) has significantly advanced prostate cancer (PCa) detection, yet decisions on invasive biopsy with moderate prostate imaging reporting and data system (PI-RADS) scores remain ambiguous.
Artificial intelligence-assisted longitudinal assessment of coronary artery calcification in the Korean lung cancer screening CT program.
Clinical imaging
Jul 6, 2025
PURPOSE: The clinical implications of coronary artery calcification (CAC) growth remain underexplored. This study aims to assess CAC growth and its association with adverse cardiovascular events (ACEs) in individuals undergoing lung cancer screening ...
Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn's disease.
Annals of medicine
Jul 5, 2025
BACKGROUND: Crohn's disease (CD) is a chronic inflammatory bowel disease, with infliximab (IFX) commonly used for treatment. However, no clinically applicable model currently exists to predict the response of patients with CD to IFX therapy. Given th...
A deep learning model for preoperative risk stratification of pancreatic ductal adenocarcinoma based on genomic predictors of liver metastasis.
European journal of cancer (Oxford, England : 1990)
Jul 5, 2025
BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) frequently presents with occult metastatic disease which can undermine the benefit of local treatment. Improved preoperative tools may enhance risk stratification.
Machine learning-based predictive tools and nomogram for in-hospital mortality in critically ill cancer patients: development and external validation using retrospective cohorts.
BMC medical informatics and decision making
Jul 4, 2025
BACKGROUND: The incidence of intensive care unit (ICU) admissions and the corresponding mortality rates among cancer patients are both high. However, the existing scoring systems all lack specificity. This research seeks to establish and validate a p...
Predicting ESWL success for ureteral stones: a radiomics-based machine learning approach.
BMC medical imaging
Jul 4, 2025
OBJECTIVES: This study aimed to develop and validate a machine learning (ML) model that integrates radiomics and conventional radiological features to predict the success of single-session extracorporeal shock wave lithotripsy (ESWL) for ureteral sto...
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