AI Medical Compendium Topic

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Retrospective Studies

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A novel framework for esophageal cancer grading: combining CT imaging, radiomics, reproducibility, and deep learning insights.

BMC gastroenterology
OBJECTIVE: This study aims to create a reliable framework for grading esophageal cancer. The framework combines feature extraction, deep learning with attention mechanisms, and radiomics to ensure accuracy, interpretability, and practical use in tumo...

Machine learning model to predict sepsis in ICU patients with intracerebral hemorrhage.

Scientific reports
Patients with intracerebral hemorrhage (ICH) are highly susceptible to sepsis. This study evaluates the efficacy of machine learning (ML) models in predicting sepsis risk in intensive care units (ICUs) patients with ICH. We conducted a retrospective ...

Identification of HER2-over-expression, HER2-low-expression, and HER2-zero-expression statuses in breast cancer based on F-FDG PET/CT radiomics.

Cancer imaging : the official publication of the International Cancer Imaging Society
PURPOSE: According to the updated classification system, human epidermal growth factor receptor 2 (HER2) expression statuses are divided into the following three groups: HER2-over-expression, HER2-low-expression, and HER2-zero-expression. HER2-negati...

Application of interpretable machine learning algorithms to predict macroangiopathy risk in Chinese patients with type 2 diabetes mellitus.

Scientific reports
Macrovascular complications are leading causes of morbidity and mortality in patients with type 2 diabetes mellitus (T2DM), yet early diagnosis of cardiovascular disease (CVD) in this population remains clinically challenging. This study aims to deve...

Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan.

Journal of medical Internet research
BACKGROUND: Stigma associated with HIV/AIDS continues to be a major barrier to prevention, management, and care. HIV stigma can negatively influence health behaviors. Surveys of the general public in Japan also demonstrated substantial gaps in knowle...

A machine learning-based prediction model for colorectal liver metastasis.

Clinical and experimental medicine
Colorectal liver metastasis (CRLM) is a primary factor contributing to poor prognosis and metastasis in colorectal cancer (CRC) patients. This study aims to develop and validate a machine learning (ML)-based risk prediction model using conventional c...

All-Cause Mortality Risk in Elderly Patients with Femoral Neck and Intertrochanteric Fractures: A Predictive Model Based on Machine Learning.

Clinical interventions in aging
INTRODUCTION: The aim of this study was to identify the influencing factors for all-cause mortality in elderly patients with intertrochanteric and femoral neck fractures and to construct predictive models.

Diagnostic Accuracy of On-Premise Automated Coronary CT Angiography Analysis Based on Coronary Artery Disease Reporting and Data System 2.0.

Radiology
Background Chest pain is a leading cause of outpatient and emergency department visits; advancements in artificial intelligence (AI) could improve coronary CT angiography (CCTA) workflows for these patients. Purpose To evaluate the performance of an ...

Association of Deep Learning-based Chest CT-derived Respiratory Parameters with Disease Progression in Amyotrophic Lateral Sclerosis.

Radiology
Background Forced vital capacity (FVC) is a standard measure of respiratory function in patients with amyotrophic lateral sclerosis (ALS) but has limitations, particularly for patients with bulbar impairment. Purpose To determine the value of deep le...