Artificial Intelligence Medical Compendium

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

Showing 781 to 790 of 6,689 articles

Sperm metabolomic signatures of asthenozoospermia and teratozoospermia in Chinese reproductive-age men.

Scientific reports
Asthenozoospermia and teratozoospermia are common causes of male infertility. Despite their prevalence, the underlying metabolic mechanisms remain poorly understood. In this study, we conducted targeted metabolomic profiling of sperm samples from 131... read more 

Enhancing smart city sustainability with explainable federated learning for vehicular energy control.

Scientific reports
The rise of electric and autonomous vehicles in smart cities poses challenges in vehicular energy management due to un-optimized consumption, inefficient grid use, and unpredictable traffic patterns. Traditional centralized machine learning models an... 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 

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 

Enhanced forecasting of shipboard electrical power demand using multivariate input and variational mode decomposition with mode selection.

Scientific reports
Accurate forecasting of shipboard electricity demand is essential for optimizing Energy Management Systems (EMSs), which are crucial for efficient and profitable operation of shipboard power grids. To address this challenge, this paper introduces a n... 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 

A hybrid self attentive linearized phrase structured transformer based RNN for financial sentence analysis with sentence level explainability.

Scientific reports
As financial institutions want openness and accountability in their automated systems, the task of understanding model choices has become more crucial in the field of financial text analysis. In this study, we propose xFiTRNN, a hybrid model that int... read more 

Multi-omics analysis identifies SNP-associated immune-related signatures by integrating Mendelian randomization and machine learning in hepatocellular carcinoma.

Scientific reports
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death globally, characterized by high morbidity and poor prognosis. The complex molecular and immune landscape of HCC makes accurate patient stratification and personalized treatment... read more 

A tailored deep learning approach for early detection of oral cancer using a 19-layer CNN on clinical lip and tongue images.

Scientific reports
Early and accurate detection of oral cancer plays a pivotal role in improving patient outcomes. This research introduces a custom-designed, 19-layer convolutional neural network (CNN) for the automated diagnosis of oral cancer using clinical images o... read more 

Optimal features assisted multi-attention fusion for robust fire recognition in adverse conditions.

Scientific reports
Deep neural networks have significantly enhanced visual data-based fire detection systems. However, high false alarm rates, shallow-layered networks, and poor recognition in challenging environments continue to hinder their practical deployment. To a... read more