Diagnosing Musculoskeletal Conditions using Artificial Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging
- 1st Edition - November 16, 2024
- Latest edition
- Editors: Rakesh Kumar, Meenu Gupta, Ajith Abraham, Paul Antony
- Language: English
Bone deformations can lead to musculoskeletal disorders and negatively impact on individual quality of life. Early and accurate detection of bone deformation is crucial for… Read more
Description
Description
Bone deformations can lead to musculoskeletal disorders and negatively impact on individual quality of life. Early and accurate detection of bone deformation is crucial for effective medical intervention. Diagnosing Musculoskeletal Conditions Using Artificial Intelligence and Machine Learning to Aid Interpretation of Clinical Imaging outlines a comprehensive approach that integrates Artificial Intelligence (AI) and Machine Learning (ML) techniques to identify bone deformations promptly and accurately. By leveraging advanced image analysis and pattern recognition, this approach aims to revolutionize the field of orthopedic diagnostics. This book covers challenges, technologies, applications, and future trends of AI and ML in Bone Deformation, addressing advanced and innovative techniques, frameworks, methodologies, and practical implementations of machine learning to get early predictions of Bone deformation. Written by experts in the field for researchers, surgeons, students, and instructors interested in musculoskeletal conditions.
Key features
Key features
- Presents fundamental concepts and analysis of machine learning algorithms and diagnoses in bone deformation
- Addresses human health issues related to bone deformation using a different machine learning algorithm
- Provides innovative, new approaches for machine learning in musculoskeletal conditions with its future directions
Readership
Readership
Researchers, healthcare practitioners, undergraduate students, postgraduate students
Table of contents
Table of contents
1. An Introductory approach for Bone Deformities, Osteoarthrosis, Osteoporosis, and Spondylosis of Spine using Machine Learning
2. Identification and Classification of Musculoskeletal Conditions using Artificial Intelligence and Machine Learning
3. Early-stage detection of osteoarthritis of the joints (hip and knee) using Machine Learning
4. Bone cancer classification and detection using Machine Learning techniques
5. Identification of the risk of osteoporosis in older Vietnamese women using Artificial Intelligence and Machine Learning
6. Identification of Paget's Disease in the Human body using Artificial Intelligence and Machine Learning
7. Identification of Osteonecrosis using Artificial Intelligence and Machine Learning
8. Identification and Classification of Rheumatoid Arthritis using Artificial Intelligence and Machine Learning
9. Early detection approach for Analysis of Osteoarthritis using Artificial Intelligence and Machine Learning
10. Pre-analysis of ankylosing spondylitis using Machine Learning
11. Analysis and identification of gout flares using Machine Learning
12. Impact of Amyloidosis on Bones and its relationship with dementia
13. Real-world application of Machine learning in Bone Deformities identification
14. Conclusion
2. Identification and Classification of Musculoskeletal Conditions using Artificial Intelligence and Machine Learning
3. Early-stage detection of osteoarthritis of the joints (hip and knee) using Machine Learning
4. Bone cancer classification and detection using Machine Learning techniques
5. Identification of the risk of osteoporosis in older Vietnamese women using Artificial Intelligence and Machine Learning
6. Identification of Paget's Disease in the Human body using Artificial Intelligence and Machine Learning
7. Identification of Osteonecrosis using Artificial Intelligence and Machine Learning
8. Identification and Classification of Rheumatoid Arthritis using Artificial Intelligence and Machine Learning
9. Early detection approach for Analysis of Osteoarthritis using Artificial Intelligence and Machine Learning
10. Pre-analysis of ankylosing spondylitis using Machine Learning
11. Analysis and identification of gout flares using Machine Learning
12. Impact of Amyloidosis on Bones and its relationship with dementia
13. Real-world application of Machine learning in Bone Deformities identification
14. Conclusion
Product details
Product details
- Edition: 1
- Latest edition
- Published: November 20, 2024
- Language: English
About the editors
About the editors
RK
Rakesh Kumar
Dr. Rakesh Kumar is working as a Professor in the Department of Computer Science Engineering at Chandigarh University, Punjab, India. He did his Ph.D. from Punjab Technical University, Jalandhar, in Computer Science and Engineering in 2017. He has published many authored books with reputed publishers. His research interests are IoT, Machine Learning, and Natural Language Processing. A total of 19+ Years of Academic / Research Experience with more than 100 Publications in various National/International Conferences and Journals. He also organized three international conferences under the banner of IEEE Explore and AIP publisher.
Affiliations and expertise
Professor, Chandigarh UniversityMG
Meenu Gupta
Dr. Meenu Gupta is a Professor in the Department of Computer Science and Engineering, University Centre for Research and Development, Chandigarh University, Punjab, India. She is Head of Conferences and Research Outreach (Engineering Cluster) and a member of the academic leadership team at UIE–CSE. Dr. Gupta completed her Ph.D. in Computer Science and Engineering at Ansal University, Gurgaon, in 2020. She has also been a Postdoctoral Fellow at the MIR Lab in the USA. Her research interests include Machine Learning, Intelligent Systems, Data Mining, Artificial Intelligence, Image Processing, Smart Cities, Data Analysis, and Brain–Machine Interaction (BMI). She has served as a reviewer for multiple peer-reviewed journals. Dr. Gupta is a Senior Member of IEEE and a Life Member of ISTE and IAENG. She has held roles within IEEE, including positions in the IEEE Delhi Section and as an officer connected with the IEEE Robotics and Automation Society (RAS) Delhi Section.
Affiliations and expertise
Chandigarh University, Punjab, IndiaAA
Ajith Abraham
Dr. Ajith Abraham is the Pro Vice-Chancellor for Academics, Research, Incubation, and International Relations at Bennette University. He is also the Founding Director of Machine Intelligence Research Labs (MIR Labs), a global non-profit scientific network that connects academia and industry to support research and innovation. He is also serving as Vice Chancellor of Sai University, Chennai.
His research interests include artificial intelligence and machine intelligence, cyber-physical systems, the Internet of Things (IoT), network security, Web intelligence, sensor networks, and data mining. He serves as Chair of the IEEE Systems, Man, and Cybernetics Society Technical Committee on Soft Computing and has held editorial leadership roles, including Editor-in-Chief of Engineering Applications of Artificial Intelligence.
Dr. Abraham earned his Ph.D. in Computer Science from Monash University, Australia.
Affiliations and expertise
Sai University, Tamil Nadu, IndiaPA
Paul Antony
Dr. Paul Antony is working as Senior and Lead consultant in Department of Orthopaedics at Apollo Super speciality Hospital Muscat, Oman. He did his postgraduate degree from Christian Medical college, Ludhiana from Panjab University in 1998 and did his SICOT & AO fellowship in shoulder and knee surgeries from Germany . He has more than 24 years experience in the field of arthroplasty and arthroscopic surgeries of shoulder, knee and hip joints.
Affiliations and expertise
Sr Consultant, Dept of Orthopaedics, Apollo Super Specialty Hospital, IndiaView book on ScienceDirect
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