AIMC Topic: Retrospective Studies

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Multimodal Machine Learning for Prediction of 30-Day Readmission Risk in Elderly Population.

The American journal of medicine
BACKGROUND: Readmission within 30 days is a prevalent issue among elderly patients, linked to unfavorable health outcomes. Our objective was to develop and validate multimodal machine learning models for predicting 30-day readmission risk in elderly ...

Influence of Deep Learning Based Image Reconstruction on Quantitative Results of Coronary Artery Calcium Scoring.

Academic radiology
RATIONALE AND OBJECTIVES: To assess the impact of deep learning-based imaging reconstruction (DLIR) on quantitative results of coronary artery calcium scoring (CACS) and to evaluate the potential of DLIR for radiation dose reduction in CACS.

Development and validation of machine learning models to predict postoperative infarction in moyamoya disease.

Journal of neurosurgery
OBJECTIVE: Cerebral infarction is a common complication in patients undergoing revascularization surgery for moyamoya disease (MMD). Although previous statistical evaluations have identified several risk factors for postoperative brain ischemia, the ...

Multistep validation of a post-ERCP pancreatitis prediction system integrating multimodal data: a multicenter study.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: The impact of various categories of information on the prediction of post-ERCP pancreatitis (PEP) remains uncertain. We comprehensively investigated the risk factors associated with PEP by constructing and validating a model inco...

Rapid Endoscopic Diagnosis of Benign Ulcerative Colorectal Diseases With an Artificial Intelligence Contextual Framework.

Gastroenterology
BACKGROUND & AIMS: Benign ulcerative colorectal diseases (UCDs) such as ulcerative colitis, Crohn's disease, ischemic colitis, and intestinal tuberculosis share similar phenotypes with different etiologies and treatment strategies. To accurately diag...

Initial experience of a single surgeon for safety and feasibility of the Versius Robotic System in robot-assisted cholecystectomy and hernia repair.

Journal of robotic surgery
This study aimed to evaluate the feasibility, safety, and perioperative outcomes of cholecystectomy and hernia repair performed with the Versius Robotic System by a surgeon with no prior robotic surgery experience. A retrospective analysis was conduc...

Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to invasive breast cancer, but most DCIS lesions never will. Therefore, four clinical trials (COMET, LORIS, LORETTA, AND LORD) test whether active surveillance for women with low-risk Ductal ca...

Application value of the automated machine learning model based on modified CT index combined with serological indices in the early prediction of lung cancer.

Frontiers in public health
BACKGROUND AND OBJECTIVE: Accurately predicting the extent of lung tumor infiltration is crucial for improving patient survival and cure rates. This study aims to evaluate the application value of an improved CT index combined with serum biomarkers, ...

Evaluation of large language models performance against humans for summarizing MRI knee radiology reports: A feasibility study.

International journal of medical informatics
OBJECTIVES: This study addresses the critical need for accurate summarization in radiology by comparing various Large Language Model (LLM)-based approaches for automatic summary generation. With the increasing volume of patient information, accuratel...