AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Translational Research, Biomedical

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An integrative knowledge graph for rare diseases, derived from the Genetic and Rare Diseases Information Center (GARD).

Journal of biomedical semantics
BACKGROUND: The Genetic and Rare Diseases (GARD) Information Center was established by the National Institutes of Health (NIH) to provide freely accessible consumer health information on over 6500 genetic and rare diseases. As the cumulative scientif...

Deep Learning-Based Segmentation and Quantification in Experimental Kidney Histopathology.

Journal of the American Society of Nephrology : JASN
BACKGROUND: Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiase...

The use of geroprotectors to prevent multimorbidity: Opportunities and challenges.

Mechanisms of ageing and development
Over 60 % of people over the age of 65 will suffer from multiple diseases concomitantly but the common approach is to treat each disease separately. As age-associated diseases have common underlying mechanisms there is potential to tackle many diseas...

Flow driven robotic navigation of microengineered endovascular probes.

Nature communications
Minimally invasive medical procedures, such as endovascular catheterization, have considerably reduced procedure time and associated complications. However, many regions inside the body, such as in the brain vasculature, still remain inaccessible due...

canSAR: update to the cancer translational research and drug discovery knowledgebase.

Nucleic acids research
canSAR (http://cansar.icr.ac.uk) is the largest, public, freely available, integrative translational research and drug discovery knowledgebase for oncology. canSAR integrates vast multidisciplinary data from across genomic, protein, pharmacological, ...

Driving success in personalized medicine through AI-enabled computational modeling.

Drug discovery today
The development of successful drugs is expensive and time-consuming because of high clinical attrition rates. This is caused partially by the rupture seen in the translatability of the drug from the bench to the clinic in the context of personalized ...

5335 days of Implementation Science: using natural language processing to examine publication trends and topics.

Implementation science : IS
INTRODUCTION: Moving evidence-based practices into the hands of practitioners requires the synthesis and translation of research literature. However, the growing pace of scientific publications across disciplines makes it increasingly difficult to st...

Classification Criteria for Spondyloarthritis/HLA-B27-Associated Anterior Uveitis.

American journal of ophthalmology
PURPOSE: The purpose of this study was to determine classification criteria for spondyloarthritis/HLA-B27-associated anterior uveitis DESIGN: Machine learning of cases with spondyloarthritis/HLA-B27-associated anterior uveitis and 8 other anterior uv...

Classification Criteria for Multiple Sclerosis-Associated Intermediate Uveitis.

American journal of ophthalmology
PURPOSE: The purpose of this study was to determine classification criteria for multiple sclerosis-associated intermediate uveitis.

How machine learning is impacting research in atrial fibrillation: implications for risk prediction and future management.

Cardiovascular research
There has been an exponential growth of artificial intelligence (AI) and machine learning (ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has been mainly driven by the confluence of two factors: the advances ...