AIMC Topic: Biomarkers

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Natural language processing techniques for studying language in pathological ageing: A scoping review.

International journal of language & communication disorders
BACKGROUND: In the past few years there has been a growing interest in the employment of verbal productions as digital biomarkers, namely objective, quantifiable behavioural data that can be collected and measured by means of digital devices, allowin...

A deep learning model for novel systemic biomarkers in photographs of the external eye: a retrospective study.

The Lancet. Digital health
BACKGROUND: Photographs of the external eye were recently shown to reveal signs of diabetic retinal disease and elevated glycated haemoglobin. This study aimed to test the hypothesis that external eye photographs contain information about additional ...

Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study.

Cell reports. Medicine
Deep learning (DL) can predict microsatellite instability (MSI) from routine histopathology slides of colorectal cancer (CRC). However, it is unclear whether DL can also predict other biomarkers with high performance and whether DL predictions genera...

Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.

Proteomics
The evolution of omics and computational competency has accelerated discoveries of the underlying biological processes in an unprecedented way. High throughput methodologies, such as flow cytometry, can reveal deeper insights into cell processes, the...

A comprehensive characterization of hippocampal feature ensemble serves as individualized brain signature for Alzheimer's disease: deep learning analysis in 3238 participants worldwide.

European radiology
OBJECTIVES: Hippocampal characterization is one of the most significant hallmarks of Alzheimer's disease (AD); rather, the single-level feature is insufficient. A comprehensive hippocampal characterization is pivotal for developing a well-performing ...

Predicting anterior cruciate ligament failure load with T* relaxometry and machine learning as a prospective imaging biomarker for revision surgery.

Scientific reports
Non-invasive methods to document healing anterior cruciate ligament (ACL) structural properties could potentially identify patients at risk for revision surgery. The objective was to evaluate machine learning models to predict ACL failure load from m...

Deep learning augmented ECG analysis to identify biomarker-defined myocardial injury.

Scientific reports
Chest pain is a common clinical complaint for which myocardial injury is the primary concern and is associated with significant morbidity and mortality. To aid providers' decision-making, we aimed to analyze the electrocardiogram (ECG) using a deep c...

The Current State of Susceptibility-Weighted Imaging and Quantitative Susceptibility Mapping in Head Trauma.

Neuroimaging clinics of North America
Susceptibility-weighted imaging (SWI) is a MR imaging technique suited to detect structural and microstructural abnormalities in traumatic brain injury (TBI). This review article provide an insight in to the physics principles of SWI and its clinical...

Diagnosing malignant distal bile duct obstruction using artificial intelligence based on clinical biomarkers.

Scientific reports
Diagnosing distal bile duct obstruction remains challenging. This study aimed to examine the diagnostic ability of artificial intelligence (AI) based on clinical biomarkers in diagnosing malignant distal bile duct obstruction. A total of 206 patients...