AIMC Topic: Retrospective Studies
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Establishment of an interpretable MRI radiomics-based machine learning model capable of predicting axillary lymph node metastasis in invasive breast cancer.
Scientific reports
Jul 18, 2025
This study sought to develop a radiomics model capable of predicting axillary lymph node metastasis (ALNM) in patients with invasive breast cancer (IBC) based on dual-sequence magnetic resonance imaging(MRI) of diffusion-weighted imaging (DWI) and dy...
Type of pre-existing chronic conditions and their associations with Merkel cell carcinoma (MCC) treatment: Prediction and interpretation using machine learning methods.
PloS one
Jul 18, 2025
OBJECTIVE: This study examined the prevalence of pre-existing chronic conditions and their association with the receipt of specific cancer-directed treatments among older adults with incident primary Merkel Cell Carcinoma (MCC) using novel predictive...
The application of super-resolution ultrasound radiomics models in predicting the failure of conservative treatment for ectopic pregnancy.
Reproductive biology and endocrinology : RB&E
Jul 17, 2025
BACKGROUND: Conservative treatment remains a viable option for selected patients with ectopic pregnancy (EP), but failure may lead to rupture and serious complications. Currently, serum β-hCG is the main predictor for treatment outcomes, yet its accu...
Development of a machine learning-derived model to predict unplanned ICU admissions after major non-cardiac surgery.
BMC anesthesiology
Jul 17, 2025
BACKGROUND: Unplanned postoperative intensive care unit admissions (UIAs) are rare events that cause significant challenges to perioperative workflow. We describe the development of a machine-learning derived model to predict UIAs using only widely u...
Integrative habitat analysis and multi-instance deep learning for predictive model of PD-1/PD-L1 immunotherapy efficacy in NSCLC patients: a dual-center retrospective study.
BMC medical imaging
Jul 17, 2025
BACKGROUND: PD-1/PD-L1 immunotherapy represents the primary treatment for advanced NSCLC patients; however, response rates to this therapy vary among individuals. This dual-center study aimed to integrate habitat radiomics and multi-instance deep lea...
Deep Learning-Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization.
Journal of medical Internet research
Jul 17, 2025
BACKGROUND: Traditional ocular gaze photograph preprocessing, relying on manual cropping and head tilt correction, is time-consuming and inconsistent, limiting artificial intelligence (AI) model development and clinical application.
Statistical toolkit for analysis of radiotherapy DICOM data.
Biomedical physics & engineering express
Jul 17, 2025
Radiotherapy (RT) has become increasingly sophisticated, necessitating advanced tools for analyzing extensive treatment data in hospital databases. Such analyses can enhance future treatments, particularly through Knowledge-Based Planning, and aid in...
Comparison of synthetic LGE with optimal inversion time vs. conventional LGE via representation learning: Quantification of Bias in Population Analysis.
Computers in biology and medicine
Jul 16, 2025
PURPOSE: Late Gadolinium Enhancement (LGE) images are crucial elements of CMR protocols for evaluating myocardial infarct (MI) severity and size. However, these images rely on signal intensity changes and manual inversion time (TI) settings, leading ...
An end-to-end interpretable machine-learning-based framework for early-stage diagnosis of gallbladder cancer using multi-modality medical data.
BMC cancer
Jul 16, 2025
BACKGROUND: The accurate early-stage diagnosis of gallbladder cancer (GBC) is regarded as one of the major challenges in the field of oncology. However, few studies have focused on the comprehensive classification of GBC based on multiple modalities....
Artificial intelligence-based diabetes risk prediction from longitudinal DXA bone measurements.
Scientific reports
Jul 16, 2025
Diabetes mellitus (DM) is a serious global health concern that poses a significant threat to human life. Beyond its direct impact, diabetes substantially increases the risk of developing severe complications such as hypertension, cardiovascular disea...
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