AIMC Topic: Retrospective Studies
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Association of visceral fat obesity with structural change in abdominal organs: fully automated three-dimensional volumetric computed tomography measurement using deep learning.
Abdominal radiology (New York)
Feb 12, 2025
The purpose of this study was to explore the association between structural changes in abdominal organs and visceral fat obesity (VFO) using a fully automated three-dimensional (3D) volumetric computed tomography (CT) measurement method based on deep...
Causal Machine Learning for Left Atrial Appendage Occlusion in Patients With Atrial Fibrillation.
JACC. Clinical electrophysiology
Feb 12, 2025
BACKGROUND: Transcatheter left atrial appendage occlusion (LAAO) is an alternative to lifelong anticoagulation, but optimal patient selection remains challenging.
Artificial Intelligence Model for Detection of Colorectal Cancer on Routine Abdominopelvic CT Examinations: A Training and External-Testing Study.
AJR. American journal of roentgenology
Feb 12, 2025
Radiologists are prone to missing some colorectal cancers (CRCs) on routine abdominopelvic CT examinations that are in fact detectable on the images. The purpose of this study was to develop an artificial intelligence (AI) model to detect CRC on ro...
Efficacy and effectiveness of therapist-guided internet versus face-to-face cognitive behavioural therapy for depression via counterfactual inference using naturalistic registers and machine learning in Finland: a retrospective cohort study.
The lancet. Psychiatry
Feb 12, 2025
BACKGROUND: According to meta-analyses of randomised controlled trials (RCTs), therapist-guided internet-delivered cognitive behavioural therapy (iCBT) is as effective a treatment for depression as traditional face-to-face CBT (fCBT), despite its sub...
Classification of fundus autofluorescence images based on macular function in retinitis pigmentosa using convolutional neural networks.
Japanese journal of ophthalmology
Feb 12, 2025
PURPOSE: To determine whether convolutional neural networks (CNN) can classify the severity of central vision loss using fundus autofluorescence (FAF) images and color fundus images of retinitis pigmentosa (RP), and to evaluate the utility of those i...
Prediction of adverse pregnancy outcomes using machine learning techniques: evidence from analysis of electronic medical records data in Rwanda.
BMC medical informatics and decision making
Feb 12, 2025
BACKGROUND: Despite substantial progress in maternal and neonatal health, Rwanda's mortality rates remain high, necessitating innovative approaches to meet health related Sustainable Development Goals (SDGs). By leveraging data collected from Electro...
Application of Clinical Department-Specific AI-Assisted Coding Using Taiwan Diagnosis-Related Groups: Retrospective Validation Study.
JMIR human factors
Feb 12, 2025
BACKGROUND: The accuracy of the ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) procedure coding system (PCS) is crucial for generating correct Taiwan diagnosis-related groups (DRGs), as coding errors can l...
Eliminating the second CT scan of dual-tracer total-body PET/CT via deep learning-based image synthesis and registration.
European journal of nuclear medicine and molecular imaging
Feb 11, 2025
PURPOSE: This study aims to develop and validate a deep learning framework designed to eliminate the second CT scan of dual-tracer total-body PET/CT imaging.
Chat GPT vs. Clinical Decision Support Systems in the Analysis of Drug-Drug Interactions.
Clinical pharmacology and therapeutics
Feb 11, 2025
The current standard method for the analysis of potential drug-drug interactions (pDDIs) is time-consuming and includes the use of multiple clinical decision support systems (CDSSs) and the interpretation by healthcare professionals. With the emergen...
Evaluation of factors predicting transition from prediabetes to diabetes among patients residing in underserved communities in the United States - A machine learning approach.
Computers in biology and medicine
Feb 11, 2025
INTRODUCTION: Over one-third of the population in the United States (US) has prediabetes. Unfortunately, underserved population in the United States face a higher burden of prediabetes compared to urban areas, increasing the risk of stroke and heart ...
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