This book offers a comprehensive and insightful exploration of biomarker discovery and electro-chemical signaling pathways in brain and cardio-oncology. The integration of these two fieldsfocusing on organs where electro-chemical signaling plays a crucial yet distinct rolesets this work apart from existing literature. The brains complex chemical signaling and the hearts electrical communication pathways are examined side by side, providing readers with a unique perspective that may yield new insights into the general field of electro-chemical biomarker discovery. Volume 1 of the book lays a solid foundation by thoroughly covering the fundamentals of oncology and biomarker science. Volume 2 builds on this by offering essential foundational information on biomarker discovery, particularly in oncology.
A Comprehensive Study of Machine Learning and Deep Learning Methods for
Medical Brain Imaging.- A Systematic Review of Brain Tumor Classification
from MRI Scans through the Last Decade.- Comparative Analysis of Logistic
Regression, Random Forest, XGBoost, LightGBM, and Voting Classifier for Early
Stroke Detection.- Machine Learning and Deep Learning for Multi-Omics and
Signal-Based Biomarker Discovery in CardioBrain Oncology: A Comprehensive
Survey.- Intelligent Brain Tumor Detection System Based on YOLOv8 Deep
Learning Model.- Spatial Transcriptomic Deep Learning and Gene-Based Machine
Learning for SLE Diagnosis: A Comparative Analysis.- CANCER SIGNALING
PATHWAYS AND CANCER BIOLOGY.- Computational Detection of Pigmented Skin
Cancer Using Machine Learning Techniques.- The Efficacy of Internet of
Medical Things (IoMT) and Cloud-Fog Computing in Monitoring Neuro-Oncology
Patients: A Systematic Literature Review.- Alzheimer's Disease Progression
Prediction with Machine Learning.- Deciphering TP53-Mediated Pathways in
Cancer Through Protein Interaction Analysis.- Accurate and Early Detection of
Dysarthria Using a Multimodal Deep Learning Methodology.-Advancing Lung
Cancer Detection Using Optimized Fine Tuning Data-Efficient Image
Transformers.
Dr. Saurav Mallik received Ph.D. from the Department of Computer Science and Engineering, Jadavpur University, Kolkata, India (2017). His Ph.D. works were conducted with the Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India. He is currently a research scientist with the University of Arizona, USA. Previously, he was a postdoctoral fellow in Harvard T. H. Chan School of Public Health, University of Texas Health Science Center at Houston, and University of Miami Miller School of Medicine, USA. He has co-authored more than 210 research articles with a Google H-index of 27. His research interests include computational biology, biostatistics, machine learning, and soft computing. He was the recipient of CSIR Research Associate, Government of India (2017), Emerging Researcher in Bioinformatics Award from Bioclues, India (2020). He is a member of IEEE, ACM, AACR, and BioClues. His research has been covered by various national and international media, TV channels, and newspapers.
Dr. Kanad Ray is the director, Amity Cognitive Computing and Brain Informatics Centre, professor of physics and electronics and communication, and head of physics at Amity University Rajasthan (AUR), India. He obtained M.Sc. and Ph.D. degrees in physics, respectively, from Calcutta University and Jadavpur University, India. Prof. Rays research interests include cognition, communication, electromagnetic field theory, wave propagation, microwave, and applied physics. He served as the editor of various Springer Book Series. He was an associated editor of various international reputed journals. He has established an MOU between Amity University Rajasthan and University of Montreal, Canada, for collaboration. He is an associated researcher of Université de Montréal, Canada, visiting professor/scientist to Benemérita Universidad Autónoma de Puebla, Mexico, Universiti Teknologi Malaysia (UTM), Malaysia, and Calcutta University, India. He organizes international conference series, viz., TCCE and TEHI as a general chair.
Dr. Mufti Mahmud is a professor in the information and computer science department at King Fahd University of Petroleum and Minerals (KFUPM), Saudi Arabia. Dr. Mahmud holds a Ph.D. in information engineering (bioengineering curriculum) from the University of Padova, Italy. He received a first-class B.Sc. in computer science from the University of Madras (India) and an M.Sc. in computer science from the University of Mysore (India) with distinction. He then pursued an M.S. in Nano and Micro Electromechanical Systems (NEMS/MEMS) at the University of Trento, Italy. With over 20 years of experience in academia and industry in the UK, Italy, Belgium, Bangladesh, and India, Dr. Mahmud has held several leadership positions, including member of the University Shadow Executive Team at Nottingham Trent University (NTU), UK, and coordinator of the Computer Science and Informatics (B11) Unit of Assessment for the Research Excellence Framework at NTU.
