System Design For Epidemics Using Machine Learning And Deep Learning
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System Design for Epidemics Using Machine Learning and Deep Learning
Author: G. R. Kanagachidambaresan
language: en
Publisher: Springer Nature
Release Date: 2023-02-01
This book explores the benefits of deploying Machine Learning (ML) and Artificial Intelligence (AI) in the health care environment. The authors study different research directions that are working to serve challenges faced in building strong healthcare infrastructure with respect to the pandemic crisis. The authors take note of obstacles faced in the rush to develop and alter technologies during the Covid crisis. They study what can be learned from them and what can be leveraged efficiently. The authors aim to show how healthcare providers can use technology to exploit advances in machine learning and deep learning in their own applications. Topics include remote patient monitoring, data analysis of human behavioral patterns, and machine learning for decision making in real-time.
Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases
Author: Rodriguez, Raul Villamarin
language: en
Publisher: IGI Global
Release Date: 2024-02-14
Within the context of global health challenges posed by intractable neurodegenerative diseases like Alzheimer's and Parkinson's, the significance of early diagnosis is critical for effective intervention, and scientists continue to discover new methods of detection. However, actual diagnosis goes beyond detection to include a significant analysis of combined data for many cases, which presents a challenge of several complicated calculations. Deep Learning Approaches for Early Diagnosis of Neurodegenerative Diseases stands as a groundbreaking work at the intersection of artificial intelligence and neuroscience. The book orchestrates a symphony of cutting-edge techniques and progressions in early detection by assembling eminent experts from the domains of deep learning and neurology. Through a harmonious blend of research areas and pragmatic applications, this monumental work charts the transformative course to revolutionize the landscape of early diagnosis and management of neurodegenerative disorders. Within the pages, readers will embark through the intricate landscape of neurodegenerative diseases, the fundamental underpinnings of deep learning, the nuances of neuroimaging data acquisition and preprocessing, the alchemy of feature extraction and representation learning, and the symphony of deep learning models tailored for neurodegenerative disease diagnosis. The book also delves into integrating multimodal data to augment diagnosis, the imperative of rigorously evaluating and validating deep learning models, and the ethical considerations and challenges entwined with deep learning for neurodegenerative diseases.
Computation of Artificial Intelligence and Machine Learning
The two-volume set, CCIS 2184-2185, constitutes the refereed proceedings of the First International Conference on Computation of Artificial Intelligence and Machine Learning, ICCAIML 2024, held in Jaipur, India, in January 18–19, 2024. The 60 papers included in these volumes were carefully reviewed and selected from 645 submissions. These papers focus on various subject areas within the field of Artificial Intelligence and Machine Learning, such as Neural Networks and Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Data Mining and Big Data Analytics, AI in Healthcare and Biomedical Applications, Autonomous Systems and Robotics, AI Ethics and Fairness, AI in Finance and Eco-nomics.