AIMC Topic: Biomarkers

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Voice as a digital biomarker in schizophrenia: a scoping review protocol on the application of artificial intelligence.

BMJ open
INTRODUCTION: There are many barriers to mental health services, including cost and stigma. Even when individuals receive professional care, assessments are intermittent and may be limited in part by the cyclical nature of psychiatric symptoms. The h...

Non-invasive assessment techniques for renal fibrosis: advances and perspectives.

Renal failure
Renal fibrosis is a critical pathological process driving chronic kidney disease (CKD) and end-stage renal disease (ESRD). Early diagnosis is essential for timely intervention, yet traditional methods like renal biopsy are invasive and present signif...

Multifactorial Biomarkers for "Talk and Deteriorate" after Head Trauma Identified Using Machine Learning.

Neurologia medico-chirurgica
Talk and Deteriorate refers to a clinical course where a patient is able to speak immediately after a traumatic brain injury but subsequently deteriorates in consciousness. Talk and Deteriorate outcomes are poor, and reliable prediction may help impr...

Development of a Novel Hydroxylamine-Based Stable Isotope Labeling Reagent for Profiling Aldehyde Metabolic Biomarkers in Diabetes Using LC-MS/MS and Machine Learning.

Analytical chemistry
Aldehyde compounds are significantly associated with diabetes mellitus. The metabolic profile of aldehydes can enhance understanding of the mechanisms underlying development of diabetes. This study employed a pair of stable isotope labeling (SIL) rea...

Decoding IBD progression: a dynamic biomarker atlas for personalized disease stratification.

Journal of translational medicine
BACKGROUND: Accurate staging is pivotal for tailoring treatment intensity, optimizing resource allocation, and improving long-term patient outcomes in IBD. The intestinal microbiota and transcriptional profiles emerge as critical determinants in IBD ...

Evaluation of biomarkers and immune microenvironment of gestational diabetes mellitus evidence from omics data and machine learning.

Scientific reports
This study aimed to identify core genes of Gestational diabetes mellitus (GDM) and explore its immune microenvironment. Using the limma package, we were able to identify differentially expressed genes (DEGs) between GDM and normal placental tissue. W...

Novel electroencephalographic biomarkers for the prediction of responders to an experimental glutamatergic agent in patients with schizophrenia.

Translational psychiatry
All medications currently used to treat schizophrenia, which exert their therapeutic effects by inhibiting dopaminergic neurotransmission, have their greatest efficacy against the positive symptoms of schizophrenia but have limited impact on negative...

Hierarchical random forest model, inflammation and oxidative stress as predictors of the atherogenic index of plasma and diabetes progression.

Scientific reports
Type 2 diabetes mellitus (T2DM) is a chronic metabolic disease that increases the risk of cardiovascular complications. The atherogenic index of plasma (AIP) is a risk marker for T2DM and cardiovascular disease on the basis of lipid profiles. T2DM an...

Impact of the oxidative balance score on cardiovascular-kidney-metabolic syndrome: A cross-sectional study with machine learning prediction.

PloS one
BACKGROUND AND AIM: The antioxidant diet and lifestyle are widely believed to prevent and even treat various diseases; however, their applicability to cardiovascular-kidney-metabolic (CKM) syndrome remains unknown. In this study, the correlation betw...