AIMC Topic: Biomarkers

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Machine Learning Approaches to the Prediction of Osteoarthritis Phenotypes and Outcomes.

Current rheumatology reports
PURPOSE OF REVIEW: Osteoarthritis (OA) is a complex heterogeneous disease with no effective treatments. Artificial intelligence (AI) and its subfield machine learning (ML) can be applied to data from different sources to (1) assist clinicians and pat...

Non-invasive Characterization of Glycosuria and Identification of Biomarkers in Diabetic Urine Using Fluorescence Spectroscopy and Machine Learning Algorithm.

Journal of fluorescence
The current study presents a steadfast, simple, and efficient approach for the non-invasive determination of glycosuria of diabetes mellitus using fluorescence spectroscopy. A Xenon arc lamp emitting light in the range of 200-950 nm was used as an ex...

Artificial intelligence-assisted repurposing of lubiprostone alleviates tubulointerstitial fibrosis.

Translational research : the journal of laboratory and clinical medicine
Tubulointerstitial fibrosis (TIF) is the most prominent cause which leads to chronic kidney disease (CKD) and end-stage renal failure. Despite extensive research, there have been many clinical trial failures, and there is currently no effective treat...

Highly Flexible Deep-Learning-Based Automatic Analysis for Graphically Encoded Hydrogel Microparticles.

ACS sensors
Graphically encoded hydrogel microparticle (HMP)-based bioassay is a diagnostic tool characterized by exceptional multiplex detectability and robust sensitivity and specificity. Specifically, deep learning enables highly fast and accurate analyses of...

Identification of key genes in spontaneous cerebral hemorrhage and prevention of disease damage: LASSO and SVM regression.

Preventive medicine
Prevention is more important than treatment, and the incidence of intracerebral hemorrhage can be effectively reduced by intervening on the risk factors of intracerebral hemorrhage. By studying the risk factors of spontaneous intracerebral hemorrhage...

Individual health-disease phase diagrams for disease prevention based on machine learning.

Journal of biomedical informatics
Early disease detection and prevention methods based on effective interventions are gaining attention worldwide. Progress in precision medicine has revealed that substantial heterogeneity exists in health data at the individual level and that complex...

Computer Vision-Based Artificial Intelligence-Mediated Encoding-Decoding for Multiplexed Microfluidic Digital Immunoassay.

ACS nano
Digital immunoassays with multiplexed capacity, ultrahigh sensitivity, and broad affordability are urgently required in clinical diagnosis, food safety, and environmental monitoring. In this work, a multidimensional digital immunoassay has been devel...

Systematical analysis of underlying markers associated with Marfan syndrome via integrated bioinformatics and machine learning strategies.

Journal of biomolecular structure & dynamics
Marfan syndrome (MFS) is a hereditary disease with high mortality. This study aimed to explore peripheral blood potential markers and underlying mechanisms in MFS via a series bioinformatics and machine learning analysis. First, we downloaded two MFS...

Pectoralis muscle predicts distant metastases in breast cancer by deep learning radiomics.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Sarcopenia is associated with a poor prognosis in patients with breast cancer (BC). Currently, there are few quantitative assessments carried out between muscle biomarkers and distant metastasis using existing methods.

Integrating inflammatory biomarker analysis and artificial-intelligence-enabled image-based profiling to identify drug targets for intestinal fibrosis.

Cell chemical biology
Intestinal fibrosis, often caused by inflammatory bowel disease, can lead to intestinal stenosis and obstruction, but there are no approved treatments. Drug discovery has been hindered by the lack of screenable cellular phenotypes. To address this, w...