AI Medical Compendium Journal:
Computational and mathematical methods in medicine

Showing 111 to 120 of 406 articles

Auxiliary Diagnosis of Lung Cancer with Magnetic Resonance Imaging Data under Deep Learning.

Computational and mathematical methods in medicine
This study was aimed at two image segmentation methods of three-dimensional (3D) U-shaped network (U-Net) and multilevel boundary sensing residual U-shaped network (RUNet) and their application values on the auxiliary diagnosis of lung cancer. In thi...

Implementation of a Heart Disease Risk Prediction Model Using Machine Learning.

Computational and mathematical methods in medicine
Cardiovascular disease prediction aids practitioners in making more accurate health decisions for their patients. Early detection can aid people in making lifestyle changes and, if necessary, ensuring effective medical care. Machine learning (ML) is ...

Da Vinci Robot-Assisted Video Image Processing under Artificial Intelligence Vision Processing Technology.

Computational and mathematical methods in medicine
This research was aimed to explore the application value of intelligent algorithm-based digital images in Da Vinci robot-assisted treatment of patients with gastric cancer surgery. 154 patients were included as the research objects, with 89 cases in ...

Deep Learning-Based Multimodal 3 T MRI for the Diagnosis of Knee Osteoarthritis.

Computational and mathematical methods in medicine
The objective of this study was to investigate the application effect of deep learning model combined with different magnetic resonance imaging (MRI) sequences in the evaluation of cartilage injury of knee osteoarthritis (KOA). Specifically, an image...

Evaluation Algorithm for the Effectiveness of Stroke Rehabilitation Treatment Using Cross-Modal Deep Learning.

Computational and mathematical methods in medicine
It is important to study the evaluation algorithm for the stroke rehabilitation treatment effect to make accurate evaluation and optimize the stroke disease treatment plan according to the evaluation results. To address the problems of poor restorati...

Research Progress of Machine Learning and Deep Learning in Intelligent Diagnosis of the Coronary Atherosclerotic Heart Disease.

Computational and mathematical methods in medicine
The coronary atherosclerotic heart disease is a common cardiovascular disease with high morbidity, disability, and societal burden. Early, precise, and comprehensive diagnosis of the coronary atherosclerotic heart disease is of great significance. Th...

Computed Tomography Images under Artificial Intelligence Algorithms on the Treatment Evaluation of Intracerebral Hemorrhage with Minimally Invasive Aspiration.

Computational and mathematical methods in medicine
The aim of this study was to investigate the therapeutic effect of minimally invasive aspiration on intracerebral hemorrhage (ICH) and the value of artificial intelligence algorithm combined with computed tomography (CT) image evaluation. Ninety-two ...

Efficient Framework for Detection of COVID-19 Omicron and Delta Variants Based on Two Intelligent Phases of CNN Models.

Computational and mathematical methods in medicine
INTRODUCTION: While the COVID-19 pandemic was waning in most parts of the world, a new wave of COVID-19 Omicron and Delta variants in Central Asia and the Middle East caused a devastating crisis and collapse of health-care systems. As the diagnostic ...

Deep Learning-Based Ultrasound Combined with Gastroscope for the Diagnosis and Nursing of Upper Gastrointestinal Submucous Lesions.

Computational and mathematical methods in medicine
The study focused on the diagnostic value of deep learning-based ultrasound combined with gastroscope examination for upper gastrointestinal submucous lesions and nursing. A total of 104 patients with upper gastrointestinal submucous lesions diagnose...

Deep Possibilistic -means Clustering Algorithm on Medical Datasets.

Computational and mathematical methods in medicine
In the past, the possibilistic -means clustering algorithm (PCM) has proven its superiority on various medical datasets by overcoming the unstable clustering effect caused by both the hard division of traditional hard clustering models and the suscep...