Artificial Intelligence Medical Compendium

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

Showing 791 to 800 of 6,689 articles

Leveraging pathological markers of lower grade glioma to predict the occurrence of secondary epilepsy, a retrospective study.

Scientific reports
Epilepsy is a common manifestation in patients with lower grade glioma (LGG), often presenting as the initial symptom in approximately 70% of cases. This study aimed to identify clinical and pathological markers for epileptic seizures in patients wit... read more 

MultiFG: integrating molecular fingerprints and graph embeddings via attention mechanisms for robust drug side effect prediction.

Scientific reports
Accurate prediction of drug side effect frequencies is critical for drug safety assessment but remains challenging due to the high cost of clinical trials and the limited generalizability of existing models. We propose Multi Fingerprint and Graph Emb... read more 

Intelligent data-driven system for mold manufacturing using reinforcement learning and knowledge graph personalized optimization for customized production.

Scientific reports
Traditional manufacturing models are heavily dependent on standardized processes, which makes it challenging to accommodate customized production needs. To address this limitation, this study presents an optimized mold digitalization system grounded ... read more 

A robust machine learning approach to predicting remission and stratifying risk in rheumatoid arthritis patients treated with bDMARDs.

Scientific reports
Rheumatoid arthritis (RA) is a chronic autoimmune disease affecting millions worldwide, leading to inflammation, joint damage, and reduced quality of life. Although biological disease-modifying antirheumatic drugs (bDMARDs) are effective, they are co... read more 

Integrating AI predictive analytics with naturopathic and yoga-based interventions in a data-driven preventive model to improve maternal mental health and pregnancy outcomes.

Scientific reports
Maternal mental health during pregnancy is a crucial area of research due to its profound impact on both maternal and child well-being. This paper proposes a comprehensive approach to predicting and monitoring psychological health risks in pregnant w... read more 

Multi class aerial image classification in UAV networks employing Snake Optimization Algorithm with Deep Learning.

Scientific reports
In Unmanned Aerial Vehicle (UAV) networks, multi-class aerial image classification (AIC) is crucial in various applications, from environmental monitoring to infrastructure inspection. Deep Learning (DL), a powerful tool in artificial intelligence (A... read more 

Intelligent brain tumor detection using hybrid finetuned deep transfer features and ensemble machine learning algorithms.

Scientific reports
Brain tumours (BTs) are severe neurological disorders. They affect more than 308,000 people each year worldwide. The mortality rate is over 251,000 deaths annually (IARC, 2020 reports). Detecting BTs is complex because they vary in nature. Early diag... read more 

5-Hydroxymethylcytosine signatures as diagnostic biomarkers for septic cardiomyopathy.

Scientific reports
At present, there are currently no molecular biomarkers for the early diagnosis of sepsis cardiomyopathy (SCM) in clinical practice. This study focuses on an in-depth examination of the DNA hydroxymethylation profiles within plasma extracellular vesi... read more 

Fine-tuning of language models for automated structuring of medical exam reports to improve patient screening and analysis.

Scientific reports
The analysis of medical imaging reports is labour-intensive but crucial for accurate diagnosis and effective patient screening. Often presented as unstructured text, these reports require systematic organisation for efficient interpretation. This stu... read more 

Unveiling degradation patterns in dye-sensitized solar cells: a machine learning perspective.

Scientific reports
This study examines the time-dependent degradation of dye-sensitized solar cells (DSSCs) by systematically investigating several critical parameters, including TiO thickness, porosity, dye concentration, and iodine-based electrolyte concentration. We... read more