Artificial Intelligence Medical Compendium

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

Showing 1,651 to 1,660 of 6,954 articles

Multimodal deep learning for chemical toxicity prediction and management.

Scientific reports
The accurate prediction of chemical toxicity is a crucial research focus in chemistry, biotechnology, and national defense. The development of comprehensive datasets for chemical toxicity prediction remains limited due to security constraints and the... read more 

Machine learning optimization of microwave-assisted extraction of phenolics and tannins from pomegranate peel.

Scientific reports
The peel of pomegranate (Punica granatum) is rich in bioactive compounds, specifically phenolic compounds and tannin compounds. However, there is still a lot of difficulty dealing with the extraction of these substances due to the limitations of trad... read more 

Energy consumption analysis and prediction in exercise training based on accelerometer sensors and deep learning.

Scientific reports
This study aims to enhance the accuracy and efficiency of energy consumption prediction during exercise training and address the limitations of existing methods in terms of data feature extraction, model complexity, and adaptability to practical appl... read more 

FPA-based weighted average ensemble of deep learning models for classification of lung cancer using CT scan images.

Scientific reports
Cancer is among the most dangerous diseases contributing to rising global mortality rates. Lung cancer, particularly adenocarcinoma, is one of the deadliest forms and severely impacts human life. Early diagnosis and appropriate treatment significantl... read more 

Immuno-transcriptomic analysis based on machine learning identifies immunity signature genes of chronic rhinosinusitis with nasal polyps.

Scientific reports
Chronic rhinosinusitis with nasal polyps (CRSwNP) is a prevalent inflammatory disease where immunomodulation plays a pivotal role. However, immuno-transcriptomic characteristics and its clinical relevance remains largely known. We analyzed transcript... read more 

Out-of-distribution reject option method for dataset shift problem in early disease onset prediction.

Scientific reports
Machine learning is increasingly used to predict lifestyle-related disease onset using health and medical data. However, its predictive accuracy for use is often hindered by dataset shift, which refers to discrepancies in data distribution between th... read more 

Computational approaches in drug chemistry leveraging python powered QSPR study of antimalaria compounds by using artificial neural networks.

Scientific reports
The application of Machine Learning has become a revolutionary instrument in the domain of pharmaceutical research. Machine learning enables the modelling of Quantitative Structure Property Relationship, a crucial task in forecasting the physiochemic... read more 

Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis.

Scientific reports
Diabetes Mellitus is a chronic metabolic disorder affecting a substantial global population leading to complications such as retinopathy, nephropathy, neuropathy, foot problems, heart attacks, and strokes if left unchecked. Prompt detection and diagn... read more 

Research on insider threat detection based on personalized federated learning and behavior log analysis.

Scientific reports
As the cybersecurity landscape becomes increasingly challenging, insider threat detection has emerged as a critical research area. Traditional methods for detecting insider threats, such as Random Forest and Isolation Forest, suffer from high computa... read more 

Investigation of cold formed steel angle compression through high throughput design FEA and machine learning.

Scientific reports
This research investigates the finite element analysis (FEA) of cold-formed steel (CFS) L-columns with pin-ended supports under compression. The study involves a comprehensive parametric analysis with 110 FE models to assess the effects of section th... read more