AIMC Topic: Biomarkers

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Perspectives in Wearable Systems in the Human-Robot Interaction (HRI) Field.

Sensors (Basel, Switzerland)
Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human-machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for w...

Unmasking Critical Illness: Using Machine Learning and Biomarkers to See What Lies Beneath.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies

Multi-omics integration strategy in the post-mortem interval of forensic science.

Talanta
Estimates of post-mortem interval (PMI), which often serve as pivotal evidence in forensic contexts, are fundamentally based on assessments of variability among diverse molecular markers (including proteins and metabolites), their correlations, and t...

CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that pro...

Imaging biomarkers and radiomics in pediatric oncology: a view from the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project.

Pediatric radiology
This review paper presents the practical development of imaging biomarkers in the scope of the PRIMAGE (PRedictive In silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers) project, as a n...

Analysis of Prospective Genetic Indicators for Prenatal Exposure to Arsenic in Newborn Cord Blood of Using Machine Learning.

Biological trace element research
Using a machine learning methods, we aim to find biological effect biomarkers of prenatal arsenic exposure in newborn cord blood. From the Gene Expression Omnibus (GEO) database, two datasets (GSE48354 and GSE7967) pertaining to cord blood sequencing...

Research on texture images and radiomics in urology: a review of urological MR imaging applications.

Current opinion in urology
PURPOSE OF REVIEW: Tumor volume and heterogenicity are associated with diagnosis and prognosis of urological cancers, and assessed by conventional imaging. Quantitative imaging, Radiomics, using advanced mathematical analysis may contain information ...

Predicting brain age gap with radiomics and automl: A Promising approach for age-Related brain degeneration biomarkers.

Journal of neuroradiology = Journal de neuroradiologie
The Brain Age Gap (BAG), which refers to the difference between chronological age and predicted neuroimaging age, is proposed as a potential biomarker for age-related brain degeneration. However, existing brain age prediction models usually rely on a...

AI-integrated ocular imaging for predicting cardiovascular disease: advancements and future outlook.

Eye (London, England)
Cardiovascular disease (CVD) remains the leading cause of death worldwide. Assessing of CVD risk plays an essential role in identifying individuals at higher risk and enables the implementation of targeted intervention strategies, leading to improved...

Peripheral blood MicroRNAs as biomarkers of schizophrenia: expectations from a meta-analysis that combines deep learning methods.

The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry
OBJECTIVES: This study aimed at identifying reliable differentially expressed miRNAs (DEMs) for schizophrenia in blood meta-analyses combined with deep learning methods.