Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare
-
Saurav Kumar Mishra
Abstract
In the current situation, the world is facing a variety of diseases, and healthcare management is also facing various enabling challenges due to emerging diseases. As healthcare is essential to human existence, most cutting-edge techniques are employed to enhance healthcare. In the era of knowledge mining, informatics plays a crucial role in various branches of research, especially in the period of the technological world since there are constantly evolving computational resources, technology, and algorithms, computational biology driven out of research laboratories and into our everyday lives to deal with it and manage it within the allotted time. Due to advanced and high-tech emerging algorithms in bioinformatics, personal computers can have the power of supercomputers, reducing research costs and time, ensuring safe and effective methods, and accelerating the discovery of novel human and healthcare managementrelated outcomes. Based on the fusion of computers and biology, computational biology can be recognized as an information science discipline that can assist in comprehending the complexity of diseases and their underlying mechanisms using a variety of fundamental approaches. As every individual contains a distinctive genome and a high degree of individuality, achieving a healthcare system where each patient might get personalized medication is one of the greatest challenges humans are facing in the present era. Monitoring patterns of data, which undergoes analysis to facilitate the discovery of strategic and decision-making-relevant insights, is possible in healthcare, thanks to big data analytics technology, along with patient diagnostics, rapid epidemic recognition, and enhanced patient management. Therefore, this chapter aims to provide an indepth overview of bioinformatics, various tools and their applications, health informatics, and the health care system. Thus, this study aims to contribute to a technologically distinct perspective of advancements in bioinformatics and big data analysis methods that can be useful to healthcare.
Abstract
In the current situation, the world is facing a variety of diseases, and healthcare management is also facing various enabling challenges due to emerging diseases. As healthcare is essential to human existence, most cutting-edge techniques are employed to enhance healthcare. In the era of knowledge mining, informatics plays a crucial role in various branches of research, especially in the period of the technological world since there are constantly evolving computational resources, technology, and algorithms, computational biology driven out of research laboratories and into our everyday lives to deal with it and manage it within the allotted time. Due to advanced and high-tech emerging algorithms in bioinformatics, personal computers can have the power of supercomputers, reducing research costs and time, ensuring safe and effective methods, and accelerating the discovery of novel human and healthcare managementrelated outcomes. Based on the fusion of computers and biology, computational biology can be recognized as an information science discipline that can assist in comprehending the complexity of diseases and their underlying mechanisms using a variety of fundamental approaches. As every individual contains a distinctive genome and a high degree of individuality, achieving a healthcare system where each patient might get personalized medication is one of the greatest challenges humans are facing in the present era. Monitoring patterns of data, which undergoes analysis to facilitate the discovery of strategic and decision-making-relevant insights, is possible in healthcare, thanks to big data analytics technology, along with patient diagnostics, rapid epidemic recognition, and enhanced patient management. Therefore, this chapter aims to provide an indepth overview of bioinformatics, various tools and their applications, health informatics, and the health care system. Thus, this study aims to contribute to a technologically distinct perspective of advancements in bioinformatics and big data analysis methods that can be useful to healthcare.
Chapters in this book
- Frontmatter I
- About the book V
- Preface VII
- Foreword IX
- Contents XI
- List of contributors XV
- Chapter 1 The impact of blockchain technology on the healthcare system 1
- Chapter 2 The role of metaverse in transforming healthcare: blockchain approach 33
- Chapter 3 Blockchain-empowered metaverse healthcare systems and applications 61
- Chapter 4 Role of artificial intelligence in disease diagnosis 89
- Chapter 5 Machine learning for twinning the human body 105
- Chapter 6 Improving patient care and healthcare management using bigdata analytics presents several research challenges 131
- Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare 159
- Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment 189
- Chapter 9 Nanorobots in healthcare 209
- Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy 237
- Chapter 11 Integration of cognitive computing and AI for smart healthcare 267
- Chapter 12 An overview of recommender systems in the healthcare domain: significant contributions, challenges, and future scope 293
- Chapter 13 Advancements and challenges of using natural language processing in the healthcare sector 317
- Chapter 14 Intraocular pressure monitoring system for glaucoma patients using IoT and machine learning 343
- Chapter 15 A machine learning approach to voice analysis in Parkinson’s disease diagnosis 365
- Index 375
Chapters in this book
- Frontmatter I
- About the book V
- Preface VII
- Foreword IX
- Contents XI
- List of contributors XV
- Chapter 1 The impact of blockchain technology on the healthcare system 1
- Chapter 2 The role of metaverse in transforming healthcare: blockchain approach 33
- Chapter 3 Blockchain-empowered metaverse healthcare systems and applications 61
- Chapter 4 Role of artificial intelligence in disease diagnosis 89
- Chapter 5 Machine learning for twinning the human body 105
- Chapter 6 Improving patient care and healthcare management using bigdata analytics presents several research challenges 131
- Chapter 7 An emerging trends of bioinformatics and big data analytics in healthcare 159
- Chapter 8 Digital twins in medicine: leveraging machine learning for real-time diagnosis and treatment 189
- Chapter 9 Nanorobots in healthcare 209
- Chapter 10 Semantic-based approach for medical cyber-physical system (MCPS) with biometric authentication for secured privacy 237
- Chapter 11 Integration of cognitive computing and AI for smart healthcare 267
- Chapter 12 An overview of recommender systems in the healthcare domain: significant contributions, challenges, and future scope 293
- Chapter 13 Advancements and challenges of using natural language processing in the healthcare sector 317
- Chapter 14 Intraocular pressure monitoring system for glaucoma patients using IoT and machine learning 343
- Chapter 15 A machine learning approach to voice analysis in Parkinson’s disease diagnosis 365
- Index 375
