|LETTER TO EDITOR
|Year : 2020 | Volume
| Issue : 1 | Page : 46-47
Big data applications in orthopaedics
Abid Haleem1, Mohd Javaid1, Ibrahim Haleem Khan2, Raju Vaishya3
1 Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi, India
2 Department of Computer Science and Engineering, Jamia Hamdard, New Delhi, India
3 Department of Orthopaedics, Indraprastha Apollo Hospital, New Delhi, India
|Date of Submission||22-Sep-2019|
|Date of Acceptance||12-Oct-2019|
|Date of Web Publication||30-Jun-2020|
Dr. Mohd Javaid
Department of Mechanical Engineering, Jamia Millia Islamia, New Delhi
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Haleem A, Javaid M, Khan IH, Vaishya R. Big data applications in orthopaedics. J Orthop Spine 2020;8:46-7
Big data is a term used for humongous and heterogeneous or complex unsorted data, from which useful information may be extracted and analyzed using different nontraditional data processing software. This technology has been used for capturing, storing, analysis, crunching, mining, sharing, transfer, and visualization of data. Its applications are applied for predictive analysis in the medical and its associated fields, like Orthopaedics, where the big data are applied to provide personalized treatment. Big data can store data in large volume in different forms (such as images, text, audio, and video), and rapidly generate data to meet the demand and the quality of data. It is used to reduce risk, waste, and automatically report patient data.
In orthopaedics, big data have gained importance in the past two decades. It has helped to create various musculoskeletal registries related to spine surgery, ligament reconstruction, total joint replacement, trauma, and other orthopaedics procedures. It is now becoming popular due to its superiority on the better prediction of a surgery. The main benefits of big data in orthopaedics are better research trails, reduced variability, and helps surgeons to understand patient conditions.
This technological revolution collects the data electronically from previous orthopaedics operations, medical reports, available literature, and even images. This technology has great potential to support the clinical decision, surveillance of disease, and proper management of health. It can be managed by different combinations of software, hardware, which is helpful for laboratory, medical imaging, electronic patient record-keeping, research and development, and information systems.
The big data field is growing, and in the field of orthopaedics, it has extensive applications. It is applied for a deeper understanding of the outcome of procedures, patient-related treatment, and for an early detection of a disease. [Table 1] elaborates the contemporary beneficial applications of big data in orthopaedics.
Big data are useful for the prevention and control of disease to better health management.
The main limitation of this technology is the requirement of specific skills and training, which increases the cost. In orthopaedics, accurate data are required to solve different challenges and issues. Software and hardware cost is another issue to store data.
In the future, big data will be used to detect bone and joint infections and other body parts. By analyzing a given record, it can suggest a better clinical decision support system for the selection of medical tools and appropriately needed devices. Thus, this technology is becoming popular to generate biomedical data and helps provide personalized medicine, patient health, identifying diseases, and better outcomes.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Liang Y, Kelemen A. Big data science and its applications in health and medical research: Challenges and opportunities. J Biom Biostat. 2016;7:307.
Javaid M, Haleem A. Industry 4.0 applications in medical field: A brief review. Curr Med Res Pract 2019:9:102-9.
Schilling PL, Bozic KJ. The big to do about “big data”. Clin Orthop Relat Res 2014;472:3270-2.
Raghupathi W, Raghupathi V. Big data analytics in healthcare: Promise and potential. Health Inf Sci Syst 2014;2:3.