⥠Quick Summary
A recent literature review highlights the transformative role of artificial intelligence (AI) in the diagnosis and treatment of orthopedic diseases. By analyzing 348 publications, the study reveals that AI techniques significantly enhance diagnostic accuracy and treatment outcomes in musculoskeletal disorders.
ð Key Details
- ð Dataset: 348 publications from 2019 to 2024
- ð§Đ Focus areas: Machine Learning, Orthopedic Diagnostics, Virtual Reality
- âïļ Methodology: Systematic narrative review
- ð Key findings: AI improves analysis of MRI, CT, and X-ray images
ð Key Takeaways
- ðĪ AI techniques such as machine learning and deep learning are pivotal in orthopedics.
- ð Diagnostic accuracy has seen a marked improvement with AI applications.
- ðĄ Virtual reality is emerging as a valuable tool in orthopedic diagnostics.
- ðĨ AI’s effectiveness spans various imaging modalities including MRI and X-ray.
- ð Review period covered publications from 2019 to 2024.
- ð 89 publications were selected for detailed analysis from the initial 348.
- ð Study conducted using data from Scopus and PubMed databases.
ð Background
The integration of artificial intelligence into healthcare has opened new avenues for improving patient care, particularly in the field of orthopedics. Traditional diagnostic methods often rely on subjective interpretations, which can lead to inconsistencies. The advent of AI technologies promises to enhance the precision and reliability of orthopedic diagnostics and treatments.
ðïļ Study
This literature review systematically evaluated 348 publications focusing on the application of AI in orthopedic medicine. The authors aimed to synthesize findings related to the effectiveness of various AI methods, including machine learning and deep learning, in diagnosing and treating musculoskeletal diseases. A total of 89 publications were selected for in-depth analysis to assess the primary AI techniques employed and their outcomes.
ð Results
The review revealed that AI significantly enhances the analysis of MRI, CT, and X-ray images. The application of machine learning and deep learning techniques has led to improved diagnostic accuracy, which in turn contributes to better treatment results for patients with orthopedic conditions. The findings underscore the potential of AI to transform orthopedic diagnostics and therapeutic strategies.
ð Impact and Implications
The implications of this study are profound. By leveraging AI technologies, healthcare professionals can achieve greater diagnostic accuracy and improve treatment outcomes for patients suffering from orthopedic diseases. This advancement not only enhances patient care but also paves the way for more personalized treatment approaches in the field of orthopedics. The integration of AI into clinical practice could lead to a paradigm shift in how orthopedic diseases are diagnosed and managed.
ðŪ Conclusion
The literature review highlights the significant potential of artificial intelligence in revolutionizing the diagnosis and treatment of orthopedic diseases. As AI technologies continue to evolve, their integration into clinical practice promises to enhance diagnostic precision and improve patient outcomes. Continued research and development in this area are essential to fully realize the benefits of AI in orthopedics.
ðŽ Your comments
What are your thoughts on the role of AI in orthopedic medicine? We invite you to share your insights and engage in a discussion! ðŽ Leave your comments below or connect with us on social media:
USE OF ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS AND TREATMENT OF ORTHOPEDIC DISEASES: LITERATURE REVIEW.
Abstract
INTRODUCTION: Artificial intelligence techniques such as machine learning have made it possible to create neural networks for the recognition of MRI and X-ray images, which has improved the diagnosis and treatment of orthopedic diseases. The purpose of our review was to synthesize and analyze publications on the use of artificial intelligence in the diagnosis and treatment of diseases of the musculoskeletal system.
MATERIALS AND METHODS: Utilizing a systematic narrative review method, we evaluated 348 publications from 2019 to 2024, with 201 of these being openly accessible. These publications were sourced from the Scopus and PubMed databases, focusing on key terms such as “Machine Learning”, “Orthopedic Diagnostics”, “Virtual Reality”, and “Diseases of the Musculoskeletal System”. We selected 89 publications for detailed analysis to identify the primary AI methods employed in orthopedics and to assess their diagnostic and therapeutic efficacy. During the literature analysis, the main areas were determined: the main methods of artificial intelligence used in orthopedics and the results of their application for diagnosis and treatment.
RESULTS: The analysis of publications showed the effectiveness of the use of AI in the analysis of MRI, CT and X-ray images. Techniques used by AI, such as machine learning, deep learning, virtual reality, and their effectiveness in performing diagnostic and treatment procedures were considered.
CONCLUSIONS: The use of artificial intelligence in the diagnosis and treatment of orthopedic diseases demonstrated an increase in diagnostic accuracy, which contributed improvement of treatment results.
Author: [‘Prudnikov Y’, ‘Yuryk O’, ‘Sosnov M’, ‘Stashkevych A’, ‘Martsyniak S’]
Journal: Georgian Med News
Citation: Prudnikov Y, et al. USE OF ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS AND TREATMENT OF ORTHOPEDIC DISEASES: LITERATURE REVIEW. USE OF ARTIFICIAL INTELLIGENCE IN THE DIAGNOSIS AND TREATMENT OF ORTHOPEDIC DISEASES: LITERATURE REVIEW. 2024; (unknown volume):19-31.