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.
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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
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.
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.
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