de Albuquerque / Giri / Panigrahi | Artificial Intelligence Strategies for Early Intervention in Neurodegeneration | Buch | 978-0-443-36380-1 | sack.de

Buch, Englisch, Format (B × H): 191 mm x 235 mm

de Albuquerque / Giri / Panigrahi

Artificial Intelligence Strategies for Early Intervention in Neurodegeneration


Erscheinungsjahr 2025
ISBN: 978-0-443-36380-1
Verlag: Elsevier Science & Technology

Buch, Englisch, Format (B × H): 191 mm x 235 mm

ISBN: 978-0-443-36380-1
Verlag: Elsevier Science & Technology


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.
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Weitere Infos & Material


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


Bhandari, Samrat Singh
Samrat Singh Bhandari is a Professor in the Department of Psychiatry at Sikkim Manipal Institute of Medical Sciences. He earned his MBBS degree from Assam Medical College in 2004, followed by an MD in Psychiatry from Guwahati Medical College in 2008. Committed to expanding his expertise, Dr. Bhandari pursued a Fellowship in Epidemiology at the University of Florida in 2018. Beyond clinical practice, his diverse research interests include the epidemiology of drug use, biological bases of

schizophrenia and affective disorders, biomarkers in psychiatry, geriatric psychiatry, and community-based research. Dr. Bhandari is at the forefront of innovation, exploring the transformative potential of machine learning in psychiatry to enhance diagnostic precision, treatment efficacy, and predictive modeling. His global engagement is reflected in affiliations with prestigious organizations such as the Indian Psychiatric Society, the Indian Society of Geriatric Mental Health, the American Psychiatric Association, and the European Psychiatric Association. Dr. Bhandari actively contributes to psychiatric literature as an Associate Editor of the Open Journal of Psychiatry and Allied Sciences, and he serves on the editorial boards of several reputable journals. Acknowledging his impactful contributions, Dr. Bhandari has received awards and grants, including the prestigious National Institute of Health (NIH) Fogarty Fellowship. His dedication to advancing mental health awareness and research underscores his commitment to the well-being of individuals and communities.

Giri, Diksha
Diksha Giri is a researcher and academician based in Sikkim, India, known for her expertise in the field of Biomedical Signal Processing. She earned her Master's degree in 2017 and subsequently embarked on a promising career in academia. Currently pursuing her Ph.D. research at Sikkim Manipal University, Diksha is deeply immersed in the exploration of computerized non-invasive approaches for the analysis of neurological disorders, with a specific focus on Gait data analysis.

Bhoi, Akash Kumar
Dr. Akash Kumar Bhoi, holds degrees in B.Tech, M.Tech, and Ph.D., and has been contributing to the field of computer science and engineering. He assumed the role of Assistant Professor (Research) at the Department of Computer Science and Engineering, Sikkim Manipal Institute of Technology (SMIT), India, in 2012. In addition to his academic responsibilities, Dr. Bhoi extended his expertise during a research tenure as a Research Associate at the Wireless Networks (WN) Research Laboratory, Institute of Information Science and Technologies, National Research Council (ISTI-CRN) in Pisa, Italy, from January 20, 2021, to January 19, 2022. Dr. Bhoi further serves as the University Ph.D. Course Coordinator for "Research & Publication Ethics (RPE)." He is an active member of professional organizations such as IEEE, ISEIS, and IAENG, and holds associate membership with IEI and UACEE. He plays a significant role as an editorial board member and reviewer for esteemed Indian and international journals and regularly contributes as a reviewer. His research expertise encompasses a wide array of domains, including Biomedical Technologies, the Internet of Things, Computational Intelligence, Antenna technology, and Renewable Energy. Dr. Bhoi has a notable publication record, with multiple papers featured in national and international journals and conferences. Dr. Bhoi has played a pivotal role in the organization of international conferences and workshops, offering his expertise as a key contributor. Currently, he is involved in editing several books in collaboration with international publishers

Panigrahi, Ranjit
Ranjit Panigrahi is an accomplished academician and researcher in the field of Computer Applications, specializing in Biomedical Data Analysis and Cyber Security. He currently holds the position of Assistant Professor in the Department of Computer Applications at Sikkim Manipal Institute of Technology, located in Majitar, Sikkim, India. Dr. Panigrahi's academic journey began with a Master of Technology in Computer Sciences & Engineering from Sikkim Manipal Institute of Technology in 2013. He further pursued his passion for research and earned a PhD degree in Computer Applications from Sikkim Manipal University in March 2020. His doctoral thesis focused on the "Design & Development of a Host-Based Intrusion Detection System with Classification of Alerts," showcasing his expertise in the field of cybersecurity. As an esteemed member of the academic community, Dr. Panigrahi has demonstrated exceptional dedication and commitment to his profession. He has been actively involved in teaching and guiding students as an Assistant Professor in the Department of Computer Applications at Sikkim Manipal Institute of Technology since July 2010. Over the years, he has held different positions and responsibilities within the department and currently serves as the Head of the IT Council at the institute. His research contributions have garnered recognition and praise, evident from the numerous publications he has authored in reputed journals and conferences. Dr. Panigrahi has an impressive track record with many articles published in SCI and Scopus-indexed journals. Additionally, he has also contributed significantly to the academic community through the publication in many conference proceedings. He is a sought-after reviewer for various technical publications and has also chaired sessions at prominent international conferences. Beyond his academic achievements, Dr. Panigrahi is also actively engaged in intellectual property research and has secured five patents.

de Albuquerque, Victor Hugo Costa
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.


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