AIMC Topic: Aged

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A two-stage machine learning-based risk assessment model for intravenous thrombolysis in acute ischemic stroke (AIS): A multi-center modeling study of pooled datasets.

International journal of medical informatics
OBJECTIVE: Develop a two-stage, machine learning-based thrombolysis risk stratification model from existing medical datasets and electronic health records to predict the risk of early hemorrhagic transformation(HT) and in-hospital mortality(IM) follo...

Predictive modeling of postoperative hyponatremia after pituitary adenoma surgery.

Clinical neurology and neurosurgery
OBJECTIVE: To improve the prediction of postoperative hyponatremia after pituitary surgery by comparing six machine learning (ML) models.

Deep learning dosiomics in grade 4 radiation-induced lymphopenia prediction in radiotherapy for esophageal cancer: a multi-center study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To investigate the feasibility and accuracy of using deep learning and dosiomics features, as well as their combination with dose-volume histogram (DVH) parameters and clinical factors to predict grade 4 radiation-induced lymphopenia (G4RIL)...

PMFF-Net: A deep learning-based image classification model for UIP, NSIP, and OP.

Computers in biology and medicine
BACKGROUND: High-resolution computed tomography (HRCT) is helpful for diagnosing interstitial lung diseases (ILD), but it largely depends on the experience of physicians. Herein, our study aims to develop a deep-learning-based classification model to...

Prediction of 30-day readmission in diabetes management using Machine learning.

Computers in biology and medicine
This study aims to develop a robust and accurate model to forecast 30-day readmissions for patients with diabetes by leveraging machine learning techniques. Diabetes, being a chronic condition with complex care needs, often leads to frequent hospital...

Optimizing treatment to control LDL cholesterol using machine learning.

Computers in biology and medicine
INTRODUCTION: Increased LDL cholesterol is one of the main risk factors for cardiovascular diseases; therefore, adequate therapy reduces the risk of developing cardiovascular disease. Artificial intelligence (AI) is a tool that can significantly help...

Quantification of Breast Arterial Calcification in Mammograms Using a UNet-Based Deep Learning for Detecting Cardiovascular Disease.

Academic radiology
BACKGROUND: Breast arterial calcification (BAC) is increasingly recognized as a significant indicator of cardiovascular risk, necessitating improvements in detection and quantification methods through mammographic screening.

A comparative study of recent large language models on generating hospital discharge summaries for lung cancer patients.

Journal of biomedical informatics
OBJECTIVE: Generating discharge summaries is a crucial yet time-consuming task in clinical practice, essential for conveying pertinent patient information and facilitating continuity of care. Recent advancements in large language models (LLMs) have s...

Performance assessment of an artificial intelligence algorithm for opportunistic screening of abdominal aortic aneurysms.

Clinical imaging
PURPOSE: Abdominal aortic aneurysm (AAA) is a common incidental finding on CT imaging performed in the acute care setting. Artificial intelligence (AI) algorithms have been developed to automatically measure aortic lumen size and thus facilitate AAA ...

Preoperative prediction of severe short-term complications in patients with bladder cancer undergoing radical cystectomy.

Surgical oncology
BACKGROUND AND OBJECTIVE: Radical cystectomy (RC) is associated with a high risk of postoperative complications. The prediction of individual patient risk for severe complications can facilitate preoperative shared decision-making. Patients with elev...