Artificial Intelligence Medical Compendium

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 

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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 

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 

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 

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 

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 

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 

Advances in computational biology have significantly impacted phylogenetic analysis, which is essential for studying evolutionary relationships among species. Phylogenetic inference has traditionally relied on techniques based on statistical models o... read more 

The high heterogeneity of Hepatocellular Carcinoma (HCC) severely hampers clinical outcomes. Current classifications based on gene expression profiles may not adequately capture patients' overall biological mechanisms and phenotypic changes. Therefor... read more