Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 1,011 to 1,020 of 6,689 articles

Research and optimization of a multilevel fire detection framework based on deep learning and classical pattern recognition techniques.

Scientific reports
Fire detection technology is essential for safeguarding public safety and minimizing property damage. Despite advancements in both traditional methodologies and modern deep learning models, challenges such as suboptimal accuracy and elevated false al... read more 

Machine learning based prediction of geotechnical parameters affecting slope stability in open-pit iron ore mines in high precipitation zone.

Scientific reports
Rainfall and its interaction with soil, rock, and environmental factors such as soil moisture content, temperature variations, groundwater levels, and vegetation cover are critical determinants of slope stability in geotechnical engineering. This stu... read more 

Construction of intelligent gymnastics teaching model based on neural network and artificial intelligence.

Scientific reports
This study aims to develop intelligent gymnastics teaching model based on Artificial Neural Network (ANN). It addresses key issues in traditional gymnastics teaching, such as difficulty in quantifying the teaching process and lack of personalized gui... read more 

Factors influencing AI adoption by Chinese mathematics teachers in STEM education.

Scientific reports
This study refines the Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) to explore the factors influencing the adoption and utilization of artificial intelligence (AI) by Chinese mathematics teachers in STEM education, aiming to p... read more 

CFM-UNet: coupling local and global feature extraction networks for medical image segmentation.

Scientific reports
In medical image segmentation, traditional CNN-based models excel at extracting local features but have limitations in capturing global features. Conversely, Mamba, a novel network framework, effectively captures long-range feature dependencies and e... read more 

Comparison of AI chatbot predicted and realworld survival outcomes in hepatocellular carcinoma.

Scientific reports
This study compares survival predictions made by an artificial intelligence (AI) based chatbot with real-world data in hepatocellular carcinoma (HCC) patients. It aims to evaluate the reliability and accuracy of AI technologies in HCC prognosis. A re... read more 

A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein.

Scientific reports
Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemen... read more 

Determination of the oral carcinoma and sarcoma in contrast enhanced CT images using deep convolutional neural networks.

Scientific reports
Oral cancer is a hazardous disease and a major cause of morbidity and mortality worldwide. The purpose of this study was to develop the deep convolutional neural networks (CNN)-based multiclass classification and object detection models for distingui... read more 

Assessment of resilience and key drivers of Tibetan villages in Western Sichuan.

Scientific reports
This study employs an integrated analytical framework combining the Social-Ecological System (SES) and Driver-Pressure-State-Impact-Response (DPSIR) models, supplemented by quantitative methodologies including the Entropy Weight Method (EWM), General... read more 

A hybrid compound scaling hypergraph neural network for robust cervical cancer subtype classification using whole slide cytology images.

Scientific reports
Cervical cancer is a major cause of mortality among women, particularly in low-income countries with insufficient screening programs. Manual cytological examination is time-consuming, error-prone and subject to inter-observer variability. Automated a... read more