AI Sharpens Pathologists' Interpretation of Tissue Samples
Pathologists' examinations of tissue samples from skin cancer tumours improved when they were assisted by an AI tool. The assessments became more consistent and patients' prognoses were described more accurately. This is shown by a study led by Karolinska Institutet, conducted in collaboration with researchers from Yale University.
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Forging a Novel Therapeutic Path for Patients with Rett Syndrome Using AI
Rett syndrome is a devastating rare genetic childhood disorder primarily affecting girls. Merely 1 out of 10,000 girls are born with it and much fewer boys. It is caused by mutations in the MeCP2 gene on the X chromosome, leading to a spectrum of cognitive and physical impairments, including repetitive hand motions, speech difficulties, and seizures.
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AI Model Converts Hospital Records into Text for Better Emergency Care Decisions
UCLA researchers have developed an AI system that turns fragmented electronic health records (EHR) normally in tables into readable narratives, allowing artificial intelligence to make sense of complex patient histories and use these narratives to perform clinical decision support with high accuracy.
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Mayo Clinic's AI Tool Identifies 9 Dementia Types, Including Alzheimer's
Mayo Clinic researchers have developed a new artificial intelligence (AI) tool that helps clinicians identify brain activity patterns linked to nine types of dementia, including Alzheimer's disease, using a single, widely available scan - a transformative advance in early, accurate diagnosis.
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AI Detects Fatty Liver Disease with Chest X-Rays
Fatty liver disease, caused by the accumulation of fat in the liver, is estimated to affect one in four people worldwide. If left untreated, it can lead to serious complications, such as cirrhosis and liver cancer, making it crucial to detect early and initiate treatment.
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AI Matches Doctors in Mapping Lung Tumors for Radiation Therapy
In radiation therapy, precision can save lives. Oncologists must carefully map the size and location of a tumor before delivering high-dose radiation to destroy cancer cells while sparing healthy tissue. But this process, called tumor segmentation, is still done manually, takes time, varies between doctors - and can lead to critical tumor areas being overlooked.
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Using Data and AI to Create Better Health Care Systems
Academic medical centers could transform patient care by adopting principles from learning health systems principles, according to researchers from Weill Cornell Medicine and the University of California, San Diego. In this approach, information from electronic health records, clinical trials and day-to-day hospital operations is analyzed in real-time to uncover insights that continuously improve patient care.
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