Mohammad Sufian Badar - Böcker

Diagnosis and Analysis of COVID-19 using Artificial Intelligence and Machine Learning-Based Techniques offers new insights and demonstrates how machine learning (ML), artificial intelligence (AI), and (Internet of Things (IoT) can be used to diagnose and fight COVID-19 infection. Sections also discuss the challenges we face in using these technologies. Chapters cover pathogenesis, transmission, diagnosis, and treatment strategies for COVID-19, Artificial Intelligence and Machine Learning, and Blockchain /IoT Blockchain technology, examining how AI can be applied as a tool for detection and containment of the spread of COVID-19, and on the socioeconomic and educational post-pandemic impacts of the disease.This is a multidisciplinary resource for those engaged in researching COVID-19 and how emerging technologies are being used as tools for detection, transmission and treatment strategies.

Describes the molecular basis of pathogenesis, epidemiology, transmission mechanism, diagnostic approaches, and the mutational landscape of SARS-CoV-2Provides insights into post COVID-19 symptoms and consequencesDemonstrates how machine learning, AI, and IoT is used to diagnose and fight COVID-19 infectionExamines the use of Blockchain technology/IoT and interpretation and validation of data obtained from artificial intelligence

Diagnosis and Analysis of Glaucoma using AI and ML for Medical Imaging highlights the importance of early detection while also discussing and updating on current treatment options to slow disease progression, emphasizing the role of AI and ML in improving diagnosis and management. Sections explore causes, symptoms, diagnostic challenges, and treatment strategies for glaucoma, integrating insights on how artificial intelligence and machine learning models can enhance healthcare delivery. Practical case studies and discussions on how accessible AI tools can be utilized by healthcare workers, NGOs, students, and researchers to address diagnostic barriers prevalent in resource-limited settings are included. This targeted resource is aimed at increasing understanding of this often asymptomatic, progressive eye disease, particularly in developing countries. Healthcare professionals, students, and policymakers will find this resource valuable with its straightforward, easy to understand, curriculum-aligned content. Its emphasis on practical applications and awareness-building make it a valuable tool for advancing glaucoma care and fostering interdisciplinary collaboration in eye health.Demonstrates how AI and ML are applied in glaucoma diagnosis and managementEmploys clear, precise language that makes complex concepts accessible to readers without a computer science backgroundProvides detailed case studies and implementation guidelines, enabling researchers and practitioners to translate theoretical AI techniques into real-world diagnostic tools

Applying Artificial Intelligence to Computational Biology and Medical Informatics explores the transformative role of AI and machine learning in modern biomedical research and healthcare. The book covers foundational concepts in AI/ML, computational biology, and medical informatics, followed by in-depth chapters on medical imaging, network biology, chemoinformatics, and public health. Other sections address ethical and societal implications, interpretable AI, and real-world case studies, making complex topics accessible through clear language and structured content. Designed for early-career researchers, students, and professionals without prior expertise in computer science or health sciences, this book provides a progressive learning path from basic to intermediate levels.Readers benefit from practical examples, online resources, and a coherent chapter structure that supports both academic study and applied research.Introduces foundational concepts in AI, machine learning, computational biology, and medical informatics, enabling readers from diverse academic backgrounds to build a solid interdisciplinary understandingPresents real-world case studies and practical applications of AI/ML in disease diagnosis, treatment, and public health, fostering translational insights and research relevanceMaintains a coherent pedagogical structure that progresses from basic to intermediate levels, supporting both self-paced learning and integration into academic curricula

This textbook is an introductory guide to applied machine learning, specifically for biology students.

This textbook is an introductory guide to applied machine learning, specifically for biology students.

The reader will learn how to build a machine-learning model and analyze the data which is generated by the practical use cases of Blockchain in various smart cities sectors like Smart Health, Smart food, agriculture, smart transport, smart water management, smart waste management, smart energy management, etc.