Chapter 2 Integration of AI in the management of bone health
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Rishabha Malviya
Abstract
Artificial intelligence (AI) is a comprehensive concept that involves the use of computational systems to replicate intelligent behavior, thus reducing human intervention. AI in particular, has achieved substantial progress in perception tasks, enabling robots to more effectively represent and analyze intricate data. In the last few years, there has been a notable increase in the advancement and adoption of AI. Within the domain of orthopedics and traumatology, several investigations have been conducted employing AI techniques for detection of fracture. The research on AI pertaining to the detection and classification of fractures is now somewhat constrained. This chapter explores a concise explanation of the utilization of AI technology in context of fracture diagnosis, elucidating the many approaches and methodologies employed in this domain. AI has the capacity to improve healthcare, namely in the field of orthopedic surgery. The recent surge in research surrounding AI has generated optimism over the advancement of more effective risk stratification tools for personalizing orthopedics throughout all stages of care, ranging from diagnosis to therapy. In the foreseeable future, it is quite probable that AI-based technologies will provide assistance to orthopedic surgeons instead of displacing them. If computers take over everyday duties, physicians will have more time to practice medicine. Distinguishing between malignant and benign bone tumors presents complications in medical imaging. The expeditious advancement of AI methodologies has resulted in notable advancements in tasks related to picture identification, namely in the categorization and characterization of diverse cancers. This chapter will comprehensively examine the prospective clinical uses of AI systems in the diagnosis and treatment of bone disorders.
Abstract
Artificial intelligence (AI) is a comprehensive concept that involves the use of computational systems to replicate intelligent behavior, thus reducing human intervention. AI in particular, has achieved substantial progress in perception tasks, enabling robots to more effectively represent and analyze intricate data. In the last few years, there has been a notable increase in the advancement and adoption of AI. Within the domain of orthopedics and traumatology, several investigations have been conducted employing AI techniques for detection of fracture. The research on AI pertaining to the detection and classification of fractures is now somewhat constrained. This chapter explores a concise explanation of the utilization of AI technology in context of fracture diagnosis, elucidating the many approaches and methodologies employed in this domain. AI has the capacity to improve healthcare, namely in the field of orthopedic surgery. The recent surge in research surrounding AI has generated optimism over the advancement of more effective risk stratification tools for personalizing orthopedics throughout all stages of care, ranging from diagnosis to therapy. In the foreseeable future, it is quite probable that AI-based technologies will provide assistance to orthopedic surgeons instead of displacing them. If computers take over everyday duties, physicians will have more time to practice medicine. Distinguishing between malignant and benign bone tumors presents complications in medical imaging. The expeditious advancement of AI methodologies has resulted in notable advancements in tasks related to picture identification, namely in the categorization and characterization of diverse cancers. This chapter will comprehensively examine the prospective clinical uses of AI systems in the diagnosis and treatment of bone disorders.
Chapters in this book
- Frontmatter I
- Preface V
- Foreword VII
- Contents IX
- Chapter 1 Cardiovascular disease diagnosis using AI-based imaging 1
- Chapter 2 Integration of AI in the management of bone health 23
- Chapter 3 AI for remote patient monitoring in healthcare 53
- Chapter 4 Engaging AI in emergency medicine for better patient care 91
- Chapter 5 Application of AI in ENT (otorhinolaryngology) care 109
- Chapter 6 Integration of AI in brain tumor surgery 125
- Chapter 7 AI in dentistry: role and application 155
- Chapter 8 Managing OPD with AI: implementation and utilization 181
- Chapter 9 Elder patient care and monitoring through AI 203
- Chapter 10 AI and pregnancy: an unexpected alliance 227
- Chapter 11 Implementation of AI in pathology 247
- Index 269
Chapters in this book
- Frontmatter I
- Preface V
- Foreword VII
- Contents IX
- Chapter 1 Cardiovascular disease diagnosis using AI-based imaging 1
- Chapter 2 Integration of AI in the management of bone health 23
- Chapter 3 AI for remote patient monitoring in healthcare 53
- Chapter 4 Engaging AI in emergency medicine for better patient care 91
- Chapter 5 Application of AI in ENT (otorhinolaryngology) care 109
- Chapter 6 Integration of AI in brain tumor surgery 125
- Chapter 7 AI in dentistry: role and application 155
- Chapter 8 Managing OPD with AI: implementation and utilization 181
- Chapter 9 Elder patient care and monitoring through AI 203
- Chapter 10 AI and pregnancy: an unexpected alliance 227
- Chapter 11 Implementation of AI in pathology 247
- Index 269
