AI Medical Compendium Topic

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Diagnosis, Computer-Assisted

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Exploring the potential of ChatGPT as an adjunct for generating diagnosis based on chief complaint and cone beam CT radiologic findings.

BMC medical informatics and decision making
AIM: This study aimed to assess the performance of OpenAI's ChatGPT in generating diagnosis based on chief complaint and cone beam computed tomography (CBCT) radiologic findings.

Establishment of a machine learning predictive model for non-alcoholic fatty liver disease: A longitudinal cohort study.

Nutrition, metabolism, and cardiovascular diseases : NMCD
BACKGROUND AND AIMS: Non-alcoholic fatty liver disease (NAFLD) is a common chronic liver disease, which lacks effective drug treatments. This study aimed to construct an eXtreme Gradient Boosting (XGBoost) prediction model to identify or evaluate pot...

[Artificial intelligence-enhanced electrocardiography : Will it revolutionize diagnosis and management of our patients?].

Herzschrittmachertherapie & Elektrophysiologie
The use of artificial intelligence (AI) in healthcare has made significant progress in the last 10 years. Many experts believe that utilization of AI technologies, especially deep learning, will bring about drastic changes in how physicians understan...

TFCNet: A texture-aware and fine-grained feature compensated polyp detection network.

Computers in biology and medicine
PURPOSE: Abnormal tissue detection is a prerequisite for medical image analysis and computer-aided diagnosis and treatment. The use of neural networks (CNN) to achieve accurate detection of intestinal polyps is beneficial to the early diagnosis and t...

Accurate Liver Fibrosis Detection Through Hybrid MRMR-BiLSTM-CNN Architecture with Histogram Equalization and Optimization.

Journal of imaging informatics in medicine
The early detection and accurate diagnosis of liver fibrosis, a progressive and potentially serious liver condition, are crucial for effective medical intervention. Invasive methods like biopsies for diagnosis can be risky and expensive. This researc...

Improving abdominal image segmentation with overcomplete shape priors.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The extraction of abdominal structures using deep learning has recently experienced a widespread interest in medical image analysis. Automatic abdominal organ and vessel segmentation is highly desirable to guide clinicians in computer-assisted diagno...

Autonomous Artificial Intelligence vs Artificial Intelligence-Assisted Human Optical Diagnosis of Colorectal Polyps: A Randomized Controlled Trial.

Gastroenterology
BACKGROUND & AIMS: Artificial intelligence (AI)-based optical diagnosis systems (CADx) have been developed to allow pathology prediction of colorectal polyps during colonoscopies. However, CADx systems have not yet been validated for autonomous perfo...

Identifying Diabetic Retinopathy in the Human Eye: A Hybrid Approach Based on a Computer-Aided Diagnosis System Combined with Deep Learning.

Tomography (Ann Arbor, Mich.)
Diagnosing and screening for diabetic retinopathy is a well-known issue in the biomedical field. A component of computer-aided diagnosis that has advanced significantly over the past few years as a result of the development and effectiveness of deep ...

Fusion between an Algorithm Based on the Characterization of Melanocytic Lesions' Asymmetry with an Ensemble of Convolutional Neural Networks for Melanoma Detection.

The Journal of investigative dermatology
Melanoma is still a major health problem worldwide. Early diagnosis is the first step toward reducing its mortality, but it remains a challenge even for experienced dermatologists. Although computer-aided systems have been developed to help diagnosis...