Machine Learning and Deep Learning in Neuroimaging Data Analysis

Inbunden, Engelska, 2024

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Machine learning (ML) and deep learning (DL) have become essential tools in healthcare. They are capable of processing enormous amounts of data to find patterns and are also adopted into methods that manage and make sense of healthcare data, either electronic healthcare records or medical imagery. This book explores how ML/DL can assist neurologists in identifying, classifying or predicting neurological problems that require neuroimaging. With the ability to model high-dimensional datasets, supervised learning algorithms can help in relating brain images to behavioral or clinical observations and unsupervised learning can uncover hidden structures/patterns in images. Bringing together artificial intelligence (AI) experts as well as medical practitioners, these chapters cover the majority of neuro problems that use neuroimaging for diagnosis, along with case studies and directions for future research.

Produktinformation

Utgivningsdatum2024-02-15
Mått178 x 254 x 12 mm
Vikt400 g
FormatInbunden
SpråkEngelska
Antal sidor124
FörlagTaylor & Francis Ltd
ISBN9781032190686

Tillhör följande kategorier

Systemvetenskap och AI inom Data och it
Elektronik och kommunikationer inom Naturvetenskap och teknik
Neurologi och klinisk neurofysiologi inom Medicin
Databaser inom Data och it

Anitha S. Pillai is a Professor in the School of Computing Sciences, Hindustan Institute of Technology and Science, India. She obtained a Ph.D. in the field of Natural Language Processing and has three decades of teaching/research experience. She has authored and co-authored several papers in national and international conferences/journals. She is also the Co-founder of AtINeu–Artificial Intelligence in Neurology, focusing on the applications of AI in neurological disorders.Prof. Bindu Menon is the senior consultant neurologist, Apollo Hospitals, Nellore, Andhra Pradesh, with a teaching experience of 20 years. She has over 90 publications in various international and national journals, and has presented 100 papers and edited 2 books; she has 14 chapters to her credit. She has been conferred with a fellowship from the American Academy of Neurology, World Stroke Organization, Royal College of Physicians (Edinburg), Indian Academy of Neurology, Geriatric Society of India, Indian College of Physicians and Global Association of Physicians of Indian Origin. She holds various positions and has several international and national awards. She is the founder of Dr. Bindu Menon Foundation and the Co-founder of AtINeu–Artificial Intelligence in Neurology.

1. Neuroimaging and Deep learning in Stroke Prabha Susy Mathew, Anitha S.Pillai, Ajith Abraham, and Di Biase Lazzaro. 2. Artificial intelligence in Stroke Imaging Lazzaro di Biase, Adriano Bonura, Pasquale Maria Pecoraro, Maria Letizia Caminiti and Vincenzo Di Lazzaro. 3. Applications of Machine Learning and Deep Learning Models in Brain Imaging Analysis Alwin Joseph, Chandra J, Bonny Banerjee, Madhavi Rangaswamy, and Jayasankara Reddy K. 4. A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis Sushil S. Kokare, and Revathy V. R. 5. A Framework for Brain Tumor Image Compression with Principal Component Analysis: Application of Machine Learning in Neuroimaging Subhagata Chattopadhyay. 6. Role of Artificial Intelligence in Neuroimaging for Cognitive Research Meenakshi Malviya, Alwin Joseph, Chandra J, and Pooja V. 7. Machine Learning And Deep Learning In Deep Brain Stimulation Targeting for Parkinson’s Disease Dr Vikash Agarwal, Ms Swarna M, and Dr. Dolly Mushahary.