AIMC Topic: Biomarkers

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Identification of biomarkers for endometriosis based on summary-data-based Mendelian randomization and machine learning.

Medicine
Endometriosis (EM) significantly impacts the quality of life, and its diagnosis currently relies on surgery, which carries risks and may miss early lesions. Noninvasive biomarkers are urgently needed for early diagnosis and personalized treatment. Th...

Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.

European respiratory review : an official journal of the European Respiratory Society
Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and monitoring. In respiratory care, evidence supporting their clinical use remains fragmented and inco...

Exploring the Impact of PA and Sedentary Behavior on Gout Risk in Hyperuricemia: Insights From Machine Learning and SHAP Analysis.

International journal of rheumatic diseases
BACKGROUND: Individuals with hyperuricemia (HUA) are widely recognized as being at increased risk for gout. This study aimed to investigate how physical activity (PA) duration and sedentary duration impact gout risk in individuals with HUA and to dev...

Applications, challenges and future directions of artificial intelligence in cardio-oncology.

European journal of clinical investigation
BACKGROUND: The management of cardiotoxicity related to cancer therapies has emerged as a significant clinical challenge, prompting the rapid growth of cardio-oncology. As cancer treatments become more complex, there is an increasing need to enhance ...

Towards a unified framework for single-cell -omics-based disease prediction through AI.

Clinical and translational medicine
Single-cell omics has emerged as a powerful tool for elucidating cellular heterogeneity in health and disease. Parallel advances in artificial intelligence (AI), particularly in pattern recognition, feature extraction and predictive modelling, now of...

Identification of hypertension subtypes using microRNA profiles and machine learning.

European journal of endocrinology
OBJECTIVE: Hypertension is a major cardiovascular risk factor affecting about 1 in 3 adults. Although the majority of hypertension cases (∼90%) are classified as "primary hypertension" (PHT), endocrine hypertension (EHT) accounts for ∼10% of cases an...

Neuroimage Analysis Methods and Artificial Intelligence Techniques for Reliable Biomarkers and Accurate Diagnosis of Schizophrenia: Achievements Made by Chinese Scholars Around the Past Decade.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, dis...

Screening of mitochondrial-related biomarkers connected with immune infiltration for acute respiratory distress syndrome through WGCNA and machine learning.

Medicine
Septic acute respiratory distress syndrome (ARDS) is a complex and noteworthy type, but its molecular mechanism has not been fully elucidated. The aim is to explore specific biomarkers to diagnose sepsis-induced ARDS. Gene expression data of sepsis a...

Mutual-assistance learning for trustworthy biomarker discovery and disease prediction.

Briefings in bioinformatics
Integrating and analyzing multiple omics datasets, such as genomics, environmental influences, and imaging endophenotypes, has yielded an abundance of candidate biomarkers. However, translating such findings into beneficial clinical knowledge for dis...

BAMBI integrates biostatistical and artificial intelligence methods to improve RNA biomarker discovery.

Briefings in bioinformatics
RNA biomarkers enable early and precise disease diagnosis, monitoring, and prognosis, facilitating personalized medicine and targeted therapeutic strategies. However, identification of RNA biomarkers is hindered by the challenge of analyzing relative...