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Using AI to understand the age of disease onset in Huntington's patients

A team from the Faculty of Medicine and Health Sciences and the Institute of Neurosciences at the University of Barcelona ...

Steatotic liver disease precisely assessed using 3D ultrafast vascular ultrasound

Steatotic liver disease (commonly called fatty liver disease) progresses silently. Even in the absence of noticeable symptoms ...
Rochester Institute of Technology

RIT researchers use machine learning to better understand the pathways of disease

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...
AZoRobotics

Detecting Alzheimer’s Early: Machine Learning’s Role in Neurological Imaging

See how machine learning is spotting Alzheimer’s years before symptoms begin—using brain scans to help guide earlier, more ...
Multiple Sclerosis News Today

Machine learning model can predict PIRA in first years of MS diagnosis

Machine learning can help predict whether people newly diagnosed with MS will experience disability worsening that occurs ...
Devdiscourse

AI could close Africa’s deadly diagnosis gap for diabetes and sickle cell disease if deployed equitably

Africa accounts for the majority of global births affected by the condition, yet universal newborn screening remains rare.
Devdiscourse

Data-driven neurology: AI systems close gap in Parkinson’s detection

According to the paper, artificial intelligence addresses a core weakness in Parkinson’s care: reliance on subjective ...
The Conversation

Tracking vampire worms with machine learning − using AI to diagnose schistosomiasis before the parasites causing it hatch in your blood

Trirupa Chakraborty is affiliated with Light Up non-profit organisation, based in India. The organisation does not have any connection with or benefits from this article. Aniruddh Sarkar has received ...