Artificial Intelligence Strategies for Early Intervention in Neurodegeneration addresses the challenges surrounding the implementation of AI-based diagnoses of neurological disorders. These challenges include the lack of large, high-quality datasets, the necessity for standardization of data collection and analysis protocols, technical hurdles in developing accurate and reliable AI algorithms, and the requirement for regulatory approval and integration into clinical workflows. The content provides guidance to researchers on how to develop and integrate AI algorithms and biomarker analysis into…mehr
Artificial Intelligence Strategies for Early Intervention in Neurodegeneration addresses the challenges surrounding the implementation of AI-based diagnoses of neurological disorders. These challenges include the lack of large, high-quality datasets, the necessity for standardization of data collection and analysis protocols, technical hurdles in developing accurate and reliable AI algorithms, and the requirement for regulatory approval and integration into clinical workflows. The content provides guidance to researchers on how to develop and integrate AI algorithms and biomarker analysis into their workflow, leading to a significant change in disease diagnosis. These techniques involve the analysis of physiological signals and images to identify patterns associated with specific diseases, and how AI algorithms can analyze medical imagery and movement and speech patterns to identify early signs of neurodegenerative diseases. The book advocates for non-invasive methods of diagnosis, which is significant progress in the field of patient-centered care by placing emphasis on the study of gait signals and other non-invasive indicators.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Victor Hugo C. de Albuquerque [M'17, SM'19] is a collaborator Professor and senior researcher at the Graduate Program on Teleinformatics Engineering at the Federal University of Ceará, Brazil, and at the Graduate Program on Telecommunication Engineering, Federal Institute of Education, Science and Technology of Ceará, Fortaleza/CE, Brazil. He has a Ph.D in Mechanical Engineering from the Federal University of Paraíba (UFPB, 2010), an MSc in Teleinformatics Engineering from the Federal University of Ceará (UFC, 2007), and he graduated in Mechatronics Engineering at the Federal Center of Technological Education of Ceará (CEFETCE, 2006). He is a specialist, mainly, in Image Data Science, IoT, Machine/Deep Learning, Pattern Recognition, Robotic.
Inhaltsangabe
1. Introduction to Neurodegenerative Diseases 2. Clinical Aspects and Advances in Neurodegenerative Diseases 3. Biomarkers for Non-Invasive Detection of Neuro Disease Detection 4. Non-Invasive Approaches for Neuro Disease Detection Using Artificial Intelligence and Gait Signal Data 5. The Potential of Gait Signal and Deep Learning Models for Accurate Neurological Disease Detection - A Case Study
1. Introduction to Neurodegenerative Diseases 2. Clinical Aspects and Advances in Neurodegenerative Diseases 3. Biomarkers for Non-Invasive Detection of Neuro Disease Detection 4. Non-Invasive Approaches for Neuro Disease Detection Using Artificial Intelligence and Gait Signal Data 5. The Potential of Gait Signal and Deep Learning Models for Accurate Neurological Disease Detection - A Case Study
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