AIMC Topic: Biomarkers

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Applications of artificial intelligence and bioinformatics methodologies in the analysis of ocular biofluid markers: a scoping review.

Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie
PURPOSE: This scoping review summarizes the applications of artificial intelligence (AI) and bioinformatics methodologies in analysis of ocular biofluid markers. The secondary objective was to explore supervised and unsupervised AI techniques and the...

Comprehensive tissue deconvolution of cell-free DNA by deep learning for disease diagnosis and monitoring.

Proceedings of the National Academy of Sciences of the United States of America
Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. D...

New directions in psychiatric drug development: promising therapeutics in the pipeline.

Expert opinion on drug discovery
INTRODUCTION: Psychiatric disorders are a leading cause of disability worldwide, calling for an urgent need for new treatments, early detection, early intervention, and precision medicine. Drug discovery and development in psychiatry continues to exp...

The macular retinal ganglion cell layer as a biomarker for diagnosis and prognosis in multiple sclerosis: A deep learning approach.

Acta ophthalmologica
PURPOSE: The macular ganglion cell layer (mGCL) is a strong potential biomarker of axonal degeneration in multiple sclerosis (MS). For this reason, this study aims to develop a computer-aided method to facilitate diagnosis and prognosis in MS.

Artificial intelligence applications in prostate cancer.

Prostate cancer and prostatic diseases
Artificial intelligence (AI) applications have enabled remarkable advancements in healthcare delivery. These AI tools are often aimed to improve accuracy and efficiency of histopathology assessment and diagnostic imaging interpretation, risk stratifi...

OSCA-finder: Redefining the assay of kidney disease diagnostic through metabolomics and deep learning.

Talanta
Liquid chromatography-mass spectrometry (LC-MS) is a platform for urine and blood sample analysis. However, the high variability in the urine sample reduced the confidence of metabolite identification. Therefore, pre and post-calibration operations a...

Blood-based biomarkers of chronic inflammation.

Expert review of molecular diagnostics
INTRODUCTION: Diseases related to chronic persisting inflammation are amongst the largest sources of morbidity and health costs, yet biomarkers for early diagnosis, prognosis, and treatment response are not sufficiently effective.

Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake.

Neuroradiology
PURPOSE: Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (I-FP-CIT) single-photon emission computerized tomography (SPECT) can eval...

Artificial intelligence and laboratory data in rheumatic diseases.

Clinica chimica acta; international journal of clinical chemistry
Artificial intelligence (AI)-based medical technologies are rapidly evolving into actionable solutions for clinical practice. Machine learning (ML) algorithms can process increasing amounts of laboratory data such as gene expression immunophenotyping...