Big data analytics and machine intelligence in biomedical and health informatics : concepts, methodologies, tools and applications / edited by Sunil Kumar Dhal [and three others].

Format:

Book

Contributor:

Dhal, Sunil Kumar, editor.

Series:

Advances in Intelligent and Scientific Computing

Language:

English

Subjects (All):

Medical informatics.

Big data.

Artificial intelligence.

Physical Description:

1 online resource (350 pages)

Place of Publication:

Beverly, Massachusetts ; Hoboken, New Jersey : Scrivener Publishing : Wiley, [2022]

Summary:

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

Contents:

Front Matter

An Introduction to Big Data Analytics Techniques in Healthcare / Anil Audumbar Pise

Identify Determinants of Infant and Child Mortality Based Using Machine Learning: Case Study on Ethiopia / Sudhir Kumar Mohapatra, Srinivas Prasad, Getachew Mekuria Habtemariam, Mohammed Siddique

Pre-Trained CNN Models in Early Alzheimer's Prediction Using Post-Processed MRI / Kalyani Gunda, Pradeepini Gera

Robust Segmentation Algorithms for Retinal Blood Vessels, Optic Disc, and Optic Cup of Retinal Images in Medical Imaging / Birendra Biswal, T Raveendra, Dwiti Krishna Bebarta, P Geetha Pavani, PK Biswal

Analysis of Healthcare Systems Using Computational Approaches / Hemanta Kumar Bhuyan, Subhendu Kumar Pani

Expert Systems in Behavioral and Mental Healthcare: Applications of AI in Decision-Making and Consultancy / Shrikaant Kulkarni

A Mathematical-Based Epidemic Model to Prevent and Control Outbreak of Corona Virus 2019 (COVID-19) / Shanmuk Srinivas Amiripalli, Vishnu Vardhan Reddy Kollu, Ritika Prasad, Mukkamala SNV Jitendra

An Access Authorization Mechanism for Electronic Health Records of Blockchain to Sheathe Fragile Information / K Sowjanya Naidu, Srinivasa L Chakravarthy

An Epidemic Graph's Modeling Application to the COVID-19 Outbreak / Hemanta Kumar Bhuyan, Subhendu Kumar Pani

Big Data and Data Mining in e-Health: Legal Issues and Challenges / Amita Verma, Arpit Bansal

Basic Scientific and Clinical Applications / Manna Sheela Rani Chetty, C V Kiran Babu

Healthcare Branding Through Service Quality / Saraju Prasad, Sunil Dhal

Index

Notes:

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9781119792352

1119792355

9781119792376

1119792371

9781119792369

1119792363

OCLC:

1315739835