|Year : 2021 | Volume
| Issue : 1 | Page : 1-2
Artificial intelligence: Where do we stand?
Alok Chandra Agrawal
Department of Orthopaedics, AIIMS, Raipur, Chhattisgarh, India
|Date of Web Publication||16-Jun-2021|
Dr. Alok Chandra Agrawal
Department of Orthopaedics, AIIMS, Raipur, Chhattisgarh
Source of Support: None, Conflict of Interest: None
|How to cite this article:|
Agrawal AC. Artificial intelligence: Where do we stand?. J Orthop Traumatol Rehabil 2021;13:1-2
Artificial intelligence (AI) is a new technology soon going to become a routine in the orthopedic armamentarium. AI can be described as the ability of a computer to comprehend data and decide on an interpretation, which has been agreed by a majority of users as being correct. In other words, the ability of a machine to simulate the human brain in various predecided applications to help humans in day-to-day works is AI. With the use of AI, patient care can be improved in the diagnostic, research, management, and analytic field. AI can promote the practicing efficiency of the orthopedic surgeons by giving them a software app that guides them to a conclusion or guideline for confirming a diagnosis, deciding management guidelines specific to patient lifestyles and comorbidities, permitting data based on these apps for research, and thus giving Hi-Tech treatment to patients also in low-cost settings. This also permits the minimal standards of medical care in all orthopedic establishments.
John McCarthy coined the term AI in the mid-1950s, which he defined as the science and engineering of making intelligent machines. He is also honored by the designation “Father of Artificial Intelligence.”
Haleem et al. 2020 have chalked out specific applications of AI in orthopedics as follows:
- Accurate analysis of skeletal radiographs for minute details, including fracture healing
- Simulator-based training before live patients like the ArthromentorR, which teaches all steps of arthroscopy of the knee, shoulder, hip, and ankle and suggestions of alternative methods of internal fixation in a specific fracture situation
- In the form of online apps, it helps in patient assessment for the decision about surgery or its outcome scores. For example, the Oxford Knee Score is a tool for deciding total knee arthroplasty or the FRAXR tool to decide chances of a fracture in an osteoporotic patient
- Use of robots for THR (Total Hip Replacement)/TKR (Total Knee Replacement) or spine surgery with inherent accuracy compared to human efforts
- Given data may help plan a discharge, and the excellent surgery done may reduce hospital stay and boost the patient's confidence
- It can create intelligence in monitors and machines in the form of automation so that treatment may get altered on its own on fixed protocols.
Although AI is revolutionizing modern orthopedic surgery, its use is yet to be made universal and perfect. The limitations of AI include the high capital cost, the time needed for its use (both in preparation and intraoperatively), the variable reliability of AI technologies, and the absence of long-term follow-up studies. Furthermore, in cases of misdiagnosis or maloperation, it becomes difficult to assess whether the doctor is irresponsible or the robot supplier company has to make the payments. At present, there is a long learning curve, and only simple procedures are being done, which can be done effortlessly without the robot too. It will be a long journey where human clinicians will be unable to control or override the machine procedures made by an AI device. Ethical concerns too are to be resolved before making proper governance and patient-protective legislation.
AI provides solutions to factors leading to physician burnout and medical mistakes. However, challenges regarding the ethical deployment, regulation, and the clinical superiority of AI over traditional statistics and decision-making remain to be resolved.,
Many modern doctors are worried about becoming worthless with AI and robotics taking an upper edge, but one should remember the potential of creative thinking and emotions that are unique to humans and will keep them superior. Although the engineering branches will be good at collecting and interpreting data, this data may be limited or biased at times for financial benefits. AI may take care of the biomechanics, statistics, and measurements, but the biology of the human body and the power of healing remain unpredictable and so good clinicians will remain always needed not only for supervision but also for treatment and for inventions so that the average/old/busy clinicians also do the treatment in a uniform and economical manner.
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