AIMC Topic: Retrospective Studies

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AI-powered model for predicting mortality risk in VA-ECMO patients: a multicenter cohort study.

Scientific reports
Veno-arterial extracorporeal membrane oxygenation (VA-ECMO) is a critical life support technology for severely ill patients. Despite its benefits, patients face high costs and significant mortality risks. To improve clinical decision-making, this stu...

Uncertainty-aware deep learning for segmentation of primary tumor and pathologic lymph nodes in oropharyngeal cancer: Insights from a multi-center cohort.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
PURPOSE: Information on deep learning (DL) tumor segmentation accuracy on a voxel and a structure level is essential for clinical introduction. In a previous study, a DL model was developed for oropharyngeal cancer (OPC) primary tumor (PT) segmentati...

Preoperative Prediction of STAS Risk in Primary Lung Adenocarcinoma Using Machine Learning: An Interpretable Model with SHAP Analysis.

Academic radiology
BACKGROUND: Accurate preoperative prediction of spread through air spaces (STAS) in primary lung adenocarcinoma (LUAD) is critical for optimizing surgical strategies and improving patient outcomes.

Thyroid nodule classification in ultrasound imaging using deep transfer learning.

BMC cancer
BACKGROUND: The accurate diagnosis of thyroid nodules represents a critical and frequently encountered challenge in clinical practice, necessitating enhanced precision in diagnostic methodologies. In this study, we investigate the predictive efficacy...

Multi-center study: ultrasound-based deep learning features for predicting Ki-67 expression in breast cancer.

Scientific reports
Applying deep learning algorithms to mine ultrasound features of breast cancer and construct a machine learning model that accurately predicts Ki-67 expression level. This multi-center retrospective study analyzed clinical and ultrasound data from 92...

Machine learning prediction of preterm birth in women under 35 using routine biomarkers in a retrospective cohort study.

Scientific reports
Preterm birth (PTB), defined as delivery before 37 weeks, affects 15 million infants annually, accounting for 11% of live births and over 35% of neonatal deaths. While advanced maternal age (≥ 35 years) is a known risk factor, PTB risk in women under...

An interpreting machine learning models to predict amputation risk in patients with diabetic foot ulcers: a multi-center study.

Frontiers in endocrinology
BACKGROUND: Diabetic foot ulcers (DFUs) constitute a significant complication among individuals with diabetes and serve as a primary cause of nontraumatic lower-extremity amputation (LEA) within this population. We aimed to develop machine learning (...

A machine learning-based model for predicting survival in patients with Rectosigmoid Cancer.

PloS one
BACKGROUND: The unique anatomical characteristics and blood supply of the rectosigmoid junction confer particular significance to its physiological functions and clinical surgeries. However, research on the prognosis of rectosigmoid junction cancer (...