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Elsevier

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

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

  • 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

Researchers, healthcare practitioners, undergraduate students, postgraduate students

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

Product details

  • Edition: 1
  • Latest edition
  • Published: November 20, 2024
  • Language: English

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 University

MG

Meenu Gupta

Dr. Meenu Gupta (Stanford/Elsevier’s Top 2% Scientist 2025) is a Professor and Head of Conferences & Research Outreach (Engineering Cluster) in the UIE-CSE Department at Chandigarh University, India. She is currently pursuing her Postdoctoral Fellowship at the MIR Lab, USA, and holds a Ph.D. in Computer Science and Engineering from Ansal University, Gurgaon (2020). With over 17 years of teaching and research experience, her expertise spans Machine Learning, Intelligent Systems, Data Mining, Artificial Intelligence, Image Processing, Smart Cities, Data Analysis, and Brain–Machine Interaction (BMI). Dr. Gupta has edited 22+ books and authored four engineering books. She has published over 250 research papers in reputed international journals and conferences, along with 45+ book chapters. She actively serves as a reviewer for several high-impact journals, including Big Data, Artificial Intelligence Review, Scientific Reports, CMC, and Digital Health. She is a Senior Member of IEEE, Life Member of ISTE and IAENG, and currently an Executive Committee Member of IEEE Delhi Section as well as Advisor of the IEEE RAS Chapter. She is elected as secretary-IEEE Robotics and Automation Society (RAS) Chapter Delhi Section. Dr. Gupta has also organized numerous conferences technically sponsored by IEEE Delhi Section, IEEE CIS, AIP, CRC and others, contributing significantly to advancing research outreach and collaborations.

Affiliations and expertise
Associate Professor, Department of Computer Science and Engineering University Centre of Research and Development Chandigarh University, Punjab, India

AA

Ajith Abraham

Ajith Abraham, PhD (2001) in artificial intelligence from Monash University, Australia, is the Vice Chancellor of Sai University, India. Prior to joining Sai University, he held senior positions at several prominent institutions and was the founding director of Machine Intelligence Research Labs, a nonprofit scientific network for innovation and research excellence headquartered in Seattle, United States. Dr. Abraham has led or co-led research projects valued at over $110 million, funded by organizations in the United States, the European Union, Italy, the Czech Republic, France, Malaysia, China, and Australia. He has worked in multidisciplinary environments for more than 35 years and is a prolific co-author of research publications in artificial intelligence and its industrial applications. Several of his works have been translated into Chinese and Russian, and one of his books has been translated into Japanese. Dr. Abraham is consistently featured in the Stanford/Elsevier list of the world’s top 2% most-cited scientists. From 2016 to 2021, he served as Editor-in-Chief of Engineering Applications of Artificial Intelligence (EAAI), one of the longest-standing journals in the field (founded in 1988). He has also served on the editorial boards of more than 15 international journals indexed by Thomson ISI.

Affiliations and expertise
Vice Chancellor and Dean, School of Artificial Intelligence, Sai University, Chennai, Tamil Nadu, India

PA

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, India

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