Mount Sinai researchers use artificial intelligence technology

Mount Sinai researchers have used new artificial intelligence methods to examine the structural and cellular features of human brain tissue to help identify the causes of Alzheimer’s disease and other related disorders. The research team found that studying the causes of cognitive impairment using an unbiased AI-based method – in contrast to traditional markers such as amyloid plaques – revealed unexpected microscopic anomalies that can predict the presence of cognitive impairment. These results were published in the journal Acta Neuropathologica Communications On September 20.

“Artificial intelligence represents an entirely new paradigm for the study of dementia and will have a transformative impact on research into complex brain diseases, particularly Alzheimer’s disease,” said co-author John Crary, MD, PhD, professor of pathology, molecular and cellular medicine, neuroscience, and Artificial Intelligence and Human Health, at the Icahn School of Medicine at Mount Sinai. “A deep learning approach has been applied to predict cognitive impairment, a challenging problem for which there is currently no human-made histological diagnostic tool.”

Mount Sinai’s team identified and analyzed the basic structure and cellular features of two brain regions, the medial temporal lobe and frontal cortex. In an effort to improve the level of postmortem brain assessment to identify signs of disease, the researchers used a poorly supervised deep learning algorithm to examine slice images of human brain anatomy tissue from a pool of more than 700 elderly donors to predict presence or absence. of cognitive impairment. A weakly supervised deep learning approach is able to handle noisy, limited, or inaccurate sources to provide signals for classifying large amounts of training data in a supervised learning environment. This deep learning model was used to quantify a decrease in Luxol’s fast blue staining, which is used to quantify myelin, the protective layer around the brain’s nerves. Machine learning models identified a signal of cognitive impairment associated with decreased amounts of myelin staining; scattered in an irregular pattern across the tissues; It is concentrated in the white matter that affects learning and brain function. Both sets of models the researchers trained and used were able to predict the presence of cognitive impairment with better accuracy than random guesses.

In their analysis, the researchers believe that the decreased intensity of coloration in specific brain regions identified by AI may serve as a scalable platform for assessing the presence of brain impairment in other associated diseases. The methodology lays the foundation for future studies, which could include dissemination of artificial intelligence models on a larger scale as well as further slicing of the algorithms to increase their predictive accuracy and reliability. Ultimately, the team said, the goal of this neurological disease research program is to develop better tools for diagnosing and treating people with Alzheimer’s disease and related disorders.

“Leveraging AI allows us to look at more disease-relevant features, which is a powerful approach when applied to a system as complex as the human brain,” said co-author Kurt W. Farrell, Ph.D., assistant professor of pathology, molecular and cell. Existing medicine, neuroscience, artificial intelligence and human health, in Icahn Mount Sinai. “It is critical that more interpretation research be conducted in the areas of neuropathology and artificial intelligence, so that advances in deep learning can be translated to improve diagnostic and treatment approaches for Alzheimer’s disease and related disorders in a safe and effective manner.”

Lead author Andrew Mackenzie, MD, PhD, and co-resident of research in the Icahn Division of Psychiatry at Mount Sinai added: “Interpretation analysis was able to identify some, but not all, of the signals that AI models used to make predictions about cognitive impairment. As a result, additional challenges remain to deploy and interpret these powerful deep learning models in the field of neuropathology.”

Also contributing to this research were researchers from the University of Texas Health Science Center in San Antonio, Texas, University of Newcastle in Tyne, UK, Boston University School of Medicine in Boston, and UT Southwestern Medical Center in Dallas. The study was supported by funding from the National Institute of Neurological Disorders and Stroke, the National Institute on Aging, and the TAO Consortium by the Rainwater Charitable Foundation.

About the Mount Sinai Health System

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 43,000 employees working in eight hospitals, more than 400 outpatient clinics, nearly 300 laboratories, a school of nursing, and a leading school of medicine and higher education. Mount Sinai advances health for all people, everywhere, by meeting the most complex healthcare challenges of our time – discovering and applying new scientific learning and knowledge; developing safer and more effective treatments; Educating the next generation of medical leaders and innovators; and supporting local communities by providing high-quality care to all who need it.

Through the integration of hospitals, laboratories, and schools, Mount Sinai offers comprehensive healthcare solutions from birth to geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients’ medical and emotional needs at the center of all treatments. The health system includes approximately 7,300 primary and specialty care physicians; 13 joint outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are constantly ranked by US News & World ReportBest Hospitals, with high honors, ranking #1 in Geriatrics and Top 20 in Cardiology/Cardiac Surgery, Diabetes/Endocrinology, Gastroenterology/Gastrointestinal Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology / Lung Surgery, Rehabilitation and Urology. The New York Eye and Ear Clinic at Mount Sinai is ranked No. 12 in ophthalmology. US News & World ReportMount Sinai Kravis’ “Best Children’s Hospitals” ranks Children’s Hospital among the best in the country for many pediatric specialties. The Icahn School of Medicine at Mount Sinai is one of three medical schools that have been awarded with distinction by multiple indicators: it has been consistently ranked in the top 20 by US News & World ReportAligned with “Best Medical Schools” with A US News & World Report Honor Roll Hospital, and among the top 20 hospitals in the state for NIH funding and the top 5 in the country for many areas of basic and clinical research. NEWSWEEKThe World’s Best Smart Hospitals have ranked Mount Sinai Hospital #1 in New York City and in the top five globally, and Mount Sinai Morningside among the top 30 hospitals globally; NEWSWEEK Mount Sinai Hospital is also highly ranked in 11 specialties in the “Best Specialty Hospitals in the World” and in the “Best Physical Rehabilitation Centers in America”.

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