Artificial Intelligence Medical Compendium

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

Showing 70,561 to 70,570 of 234,181 articles

Proxy-AN loss for deep metric learning.

Neural networks : the official journal of the International Neural Network Society
In deep metric learning, proxy-based losses aim to introduce proxy representations to approximate class distributions, reducing training complexity and accelerating model convergence. Existing proxy-based losses can be broadly categorized into two ty... read more 

Hierarchical reinforcement learning with kill chain-informed multi-objective optimization to enhance resilience in autonomous unmanned swarm.

Neural networks : the official journal of the International Neural Network Society
The resilience of autonomous unmanned swarms (AUS) serves as a cornerstone for guaranteeing continuous mission execution in the face of adversarial interferences. Contemporary methodologies often suffer from limited generalization efficacy and volati... read more 

Machine learning-based integration develops a lactate metabolism related gene signature for improving outcomes in pancreatic ductal adenocarcinoma.

Seminars in oncology
OBJECTIVES: Given its high global mortality rate, pancreatic ductal adenocarcinoma (PDAC) remains a significant area of investigation. However, a robust gene signature linked to lactate metabolism for PDAC patients has not yet been established. Our o... read more 

Harnessing Artificial Intelligence in Head and Neck Oncology Practice: Data, Diagnosis, and Therapy.

Otolaryngologic clinics of North America
Artificial intelligence (AI) has emerged as a transformative tool across the various domains of head and neck oncology. From early screening and risk stratification to diagnosis, staging, personalized treatment, rehabilitation, and research support, ... read more 

Unraveling the shared genetic architecture of osteoarthritis and metabolic traits through multi-omics insights.

Osteoarthritis and cartilage
OBJECTIVE: Osteoarthritis (OA) often coexists with metabolic traits (MTs), causing significant disability. Our study aims to uncover the shared genetic mechanisms between OA and MTs, revealing novel OA-MT related genes, proteins and pathways. DESIGN:... read more 

Artificial intelligence, machine learning and omic data integration in osteoarthritis.

Osteoarthritis and cartilage
OBJECTIVE: Artificial intelligence (AI), particularly its subfield of machine learning (ML), offer promising tools for integrating and interpreting high-dimensional omic data to advance our understanding of osteoarthritis (OA), a complex, multifactor... read more 

Using precision medicine methods to identify disease stages for chronic limb-threatening ischemia in participants of the BEST-CLI trial.

Journal of vascular surgery
BACKGROUND: Chronic limb-threatening ischemia (CLTI), the most severe form of peripheral artery disease, is associated with a high risk of limb loss. CLTI clinical presentation is highly heterogeneous, ranging from neuropathic ulcers with only mild t... read more 

Integrating structural and functional brain features to classify major depressive disorder: a multi modal approach.

Journal of affective disorders
Major Depressive Disorder (MDD) is a common mental disorder that markedly impairs psychosocial functioning and quality of life. Multi-modal fusion methods are essential for integrating diverse neuroimaging modalities to better understand complex psyc... read more 

XP-GCN: Extreme learning machines and parallel graph convolutional networks for high-throughput prediction of blood-brain barrier penetration based on feature fusion.

Computational biology and chemistry
Accurate prediction of molecular properties plays a crucial role in drug analysis and discovery. Especially for neurotherapeutic drugs developed for the treatment of neurological disorders, one of today's most critical challenges, this process become... read more