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Identification of clinical disease trajectories in neurodegenerative disorders with natural language processing

Medicine and Health

Identification of clinical disease trajectories in neurodegenerative disorders with natural language processing

N. J. Mekkes, M. Groot, et al.

Discover the fascinating world of neurodegenerative disorders as researchers Nienke J. Mekkes, Minke Groot, and their team unveil a groundbreaking method utilizing natural language processing on medical records. This study highlights 84 neuropsychiatric signs, revealing critical insights into misdiagnoses and clinical manifestations, opening new avenues for future research.

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Playback language: English
Abstract
This paper presents a novel approach to identifying clinical disease trajectories in neurodegenerative disorders using natural language processing (NLP) on medical records from 3,042 Netherlands Brain Bank donors. The study identified 84 neuropsychiatric signs and symptoms, revealing differences between frequently misdiagnosed disorders. Predictive modeling identified clinical subtypes indicative of varying neural substructure involvement. Integration with clinical diagnoses showed a significant proportion of misdiagnoses. This dataset allows researchers to study clinical manifestations across neurodegenerative disorders and link them to molecular and cellular features.
Publisher
Nature Medicine
Published On
Apr 01, 2024
Authors
Nienke J. Mekkes, Minke Groot, Eric Hoekstra, Alyse de Boer, Ekaterina Dagkesamanskaia, Sander Bouwman, Sophie M. T. Wehrens, Megan K. Herbert, Dennis D. Wever, Annemieke Rozemuller, Bart J. L. Eggen, Inge Huitinga, Inge R. Holtman
Tags
neurodegenerative disorders
natural language processing
medical records
clinical subtypes
misdiagnoses
neuropsychiatric signs
clinical manifestations

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