Lalitha Krishnasamy – författare

Neuromorphic Computing for Brain Computer Interfaces: Enhanced Synergies in Mind and Machine examines practical situations where interpretability is crucial, going beyond theoretical considerations and providing case studies and examples to illustrate how Brain Computer Interfaces could be implemented in the real world. The book encompasses novel concepts, cutting-edge research, frameworks, and tools that facilitate comprehension of neuromorphic computing models. It is an ideal, comprehensive reference for professionals, researchers, and students who want to grasp the fundamental concepts and most recent developments in brain-computer interfaces (BCIs) and neuromorphic computing.Provides an in-depth study of the principles, technology, and applications that drive neuromorphic computing and brain-computer interfacesOffers an interdisciplinary approach that includes cognitive science, neuroscience, artificial intelligence, and biomedical engineeringPresents actionable insights and methodologies that can be applied to real-world challenges by presenting practical implementations and case studies

The main aim of Healthcare 4.0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes by applying the data, information and knowledge in the healthcare domain.

Features:

Improves the quality of health data of a patient Presents a wide range of opportunities and renewed possibilities for healthcare systems Gives a way for carefully and meticulously tracking the provenance of medical records Accelerates the process of disease-oriented data and medical data arbitration Brings meaningful patient health outcomes Eradicates delayed clinical communications Helps the research intellectuals to step down further toward the disease and clinical data storage Creates more patient-centered services

The precise focus of this handbook is on the potential applications and use of data informatics in healthcare, including clinical trials, tailored ailment data, patient and ailment record characterization and health records management.

The main aim of Healthcare 4.0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes by applying the data, information and knowledge in the healthcare domain.

Features:

Improves the quality of health data of a patient Presents a wide range of opportunities and renewed possibilities for healthcare systems Gives a way for carefully and meticulously tracking the provenance of medical records Accelerates the process of disease-oriented data and medical data arbitration Brings meaningful patient health outcomes Eradicates delayed clinical communications Helps the research intellectuals to step down further toward the disease and clinical data storage Creates more patient-centered services

The precise focus of this handbook is on the potential applications and use of data informatics in healthcare, including clinical trials, tailored ailment data, patient and ailment record characterization and health records management.

The main aim of Healthcare 4.0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes by applying the data, information and knowledge in the healthcare domain.Features:Improves the quality of health data of a patientPresents a wide range of opportunities and renewed possibilities for healthcare systemsGives a way for carefully and meticulously tracking the provenance of medical recordsAccelerates the process of disease-oriented data and medical data arbitrationBrings meaningful patient health outcomesEradicates delayed clinical communicationsHelps the research intellectuals to step down further toward the disease and clinical data storageCreates more patient-centered servicesThe precise focus of this handbook is on the potential applications and use of data informatics in healthcare, including clinical trials, tailored ailment data, patient and ailment record characterization and health records management.

The main aim of Healthcare 4.0: Health Informatics and Precision Data Management is to improve the services given by the healthcare industry and to bring meaningful patient outcomes by applying the data, information and knowledge in the healthcare domain.Features:Improves the quality of health data of a patientPresents a wide range of opportunities and renewed possibilities for healthcare systemsGives a way for carefully and meticulously tracking the provenance of medical recordsAccelerates the process of disease-oriented data and medical data arbitrationBrings meaningful patient health outcomesEradicates delayed clinical communicationsHelps the research intellectuals to step down further toward the disease and clinical data storageCreates more patient-centered servicesThe precise focus of this handbook is on the potential applications and use of data informatics in healthcare, including clinical trials, tailored ailment data, patient and ailment record characterization and health records management.

This book is a comprehensive resource that delves into the integration of advanced artificial intelligence techniques within the context of modern industrial practices. It systematically explores how distributed deep learning methodologies can be effectively combined with explainable AI to enhance transparency in Industry 4.0 applications. In recent years, neural networks and other deep learning models have produced remarkable outcomes in a variety of fields, including image recognition, natural language processing, and decision-making. Concerns have been raised regarding the transparency and interpretability of these models as a result of their increasing intricacy. The demand for methodologies and approaches associated with explainable artificial intelligence (XAI) has consequently increased. The primary aim of XAI is to enhance the transparency and comprehensibility of deep learning model decision-making processes for stakeholders, irrespective of their technical expertise.