Chapter 4 A Review of Machine Learning Methods for Diagnosis and Classification of Thyroid Disease
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Sonia Rani
Abstract
The major challenge for society, especially medicinal science, is the accurate diagnosis of all diseases before treatment. This work aims to review and analyse the literature on detecting and classifying thyroid disorders using various artificial intelligence-based smart healthcare systems. This chapter describes symptoms of thyroid disease disorder and artificial intelligence techniques that play an important role in healthcare to solve thyroid disease diagnosis problems. In this study, several research studies of thyroid diagnosis with machine learning and deep learning methods have been presented to understand the problem of thyroid diagnosis. A brief overview of some research studies compared with the methods’ accuracy is also demonstrated in this chapter. The author has explored the studies of thyroid diagnosis and identified the tools and machine learning methods used for diagnosing and classifying thyroid disorders.
Abstract
The major challenge for society, especially medicinal science, is the accurate diagnosis of all diseases before treatment. This work aims to review and analyse the literature on detecting and classifying thyroid disorders using various artificial intelligence-based smart healthcare systems. This chapter describes symptoms of thyroid disease disorder and artificial intelligence techniques that play an important role in healthcare to solve thyroid disease diagnosis problems. In this study, several research studies of thyroid diagnosis with machine learning and deep learning methods have been presented to understand the problem of thyroid diagnosis. A brief overview of some research studies compared with the methods’ accuracy is also demonstrated in this chapter. The author has explored the studies of thyroid diagnosis and identified the tools and machine learning methods used for diagnosing and classifying thyroid disorders.
Chapters in this book
- Frontmatter I
- Preface V
- Acknowledgments VII
- Contents IX
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Part I: Introduction to Data Enabled Management
- Chapter 1 What Does Artificial Intelligence–Powered ChatGPT Bring to Academia? A Review 1
- Chapter 2 Education Policies Through Data Driven Decision Making: Accelerating Inclusive Education for People with Disabilities 15
- Chapter 3 The Role of Artificial Intelligence in the Emerging Digital Economy Era 33
- Chapter 4 A Review of Machine Learning Methods for Diagnosis and Classification of Thyroid Disease 51
- Chapter 5 A Question and Answering System Using Natural Language Processing and Deep Learning 65
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Part II: Role of AI and Big Data in Management Functions
- Chapter 6 The Reinvention of HRM Practices Through Artificial Intelligence: Opportunities and Challenges in the Digital World of Work 87
- Chapter 7 Challenges and Artificial Intelligence–Centered Defensive Strategies for Authentication in Online Banking 105
- Chapter 8 Catalyzing Human Potential: The Crucial Role of AI in Modern HR Management 119
- Chapter 9 Exploring How Artificial Intelligence is Changing the HRM Landscape: Refuting the Fiction with Reality! 131
- Chapter 10 Artificial Intelligence in HR: Employee Engagement Using Chatbots 147
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Part III: Application of AI in Different Sectors
- Chapter 11 An Empirical Analysis of Artificial Intelligence Applications of Manufacturing Companies in Turkey 165
- Chapter 12 A Comprehensive View of Artificial Intelligence (AI)–Based Technologies for Sustainable Development Goals (SDGs) 183
- Chapter 13 Leveraging Artificial Intelligence for Enhanced Risk Management in Banking: A Systematic Literature Review 197
- Chapter 14 Exploring the Influence of Artificial Intelligence on the Management of Hospitality and Tourism Sectors: A Bibliometric Overview 215
- Chapter 15 Artificial Intelligence in Healthcare Sector in India: Application, Challenges and a Way Forward 233
- Chapter 16 Application of Artificial Intelligence and Machine-Learning Algorithms for Forecasting Risk: The Case of the Indian Stock Market 249
- List of Figures 263
- List of Tables 265
- About the Editors 267
- Index 269
Chapters in this book
- Frontmatter I
- Preface V
- Acknowledgments VII
- Contents IX
-
Part I: Introduction to Data Enabled Management
- Chapter 1 What Does Artificial Intelligence–Powered ChatGPT Bring to Academia? A Review 1
- Chapter 2 Education Policies Through Data Driven Decision Making: Accelerating Inclusive Education for People with Disabilities 15
- Chapter 3 The Role of Artificial Intelligence in the Emerging Digital Economy Era 33
- Chapter 4 A Review of Machine Learning Methods for Diagnosis and Classification of Thyroid Disease 51
- Chapter 5 A Question and Answering System Using Natural Language Processing and Deep Learning 65
-
Part II: Role of AI and Big Data in Management Functions
- Chapter 6 The Reinvention of HRM Practices Through Artificial Intelligence: Opportunities and Challenges in the Digital World of Work 87
- Chapter 7 Challenges and Artificial Intelligence–Centered Defensive Strategies for Authentication in Online Banking 105
- Chapter 8 Catalyzing Human Potential: The Crucial Role of AI in Modern HR Management 119
- Chapter 9 Exploring How Artificial Intelligence is Changing the HRM Landscape: Refuting the Fiction with Reality! 131
- Chapter 10 Artificial Intelligence in HR: Employee Engagement Using Chatbots 147
-
Part III: Application of AI in Different Sectors
- Chapter 11 An Empirical Analysis of Artificial Intelligence Applications of Manufacturing Companies in Turkey 165
- Chapter 12 A Comprehensive View of Artificial Intelligence (AI)–Based Technologies for Sustainable Development Goals (SDGs) 183
- Chapter 13 Leveraging Artificial Intelligence for Enhanced Risk Management in Banking: A Systematic Literature Review 197
- Chapter 14 Exploring the Influence of Artificial Intelligence on the Management of Hospitality and Tourism Sectors: A Bibliometric Overview 215
- Chapter 15 Artificial Intelligence in Healthcare Sector in India: Application, Challenges and a Way Forward 233
- Chapter 16 Application of Artificial Intelligence and Machine-Learning Algorithms for Forecasting Risk: The Case of the Indian Stock Market 249
- List of Figures 263
- List of Tables 265
- About the Editors 267
- Index 269