Paper in Focus

Article: Artificial intelligence in orthopaedic surgery Authors: Lisacek-Kiosoglous AB, Powling AS, Fontalis A, Gabr A, Mazomenos E, Haddad FS Journal: Bone & Joint Research Year: 2023 Volume/Issue: 12(7):447–454 DOI:10.1302/2046-3758.127.BJR-2023-0111.R1
PMCID: PMC10329876
PMID: 37423607

Opening Editorial: Editor’s Perspective

Artificial intelligence is quickly becoming one of the most important conversations in modern medicine. In orthopaedics, this discussion is especially relevant because the specialty relies heavily on imaging, procedural planning, surgical decision-making, patient outcomes, rehabilitation, and long-term follow-up.

This issue of Conversations in Orthopaedics focuses on the growing role of artificial intelligence in orthopaedic surgery. The paper by Lisacek-Kiosoglous and colleagues provides a broad overview of how AI is currently being explored in orthopaedics, including diagnostic imaging, fracture recognition, bone tumour detection, predictive modeling, patient-reported outcome measures, rehabilitation monitoring, and surgical training.

However, the importance of AI is not only in what it can do. It is also in how it should be adopted. As AI tools become more common, orthopaedic surgeons, trainees, researchers, and healthcare systems must consider questions of accuracy, bias, validation, ethics, transparency, and preservation of the physician-patient relationship.

AI should not be viewed as a replacement for the orthopaedic surgeon. Rather, it may become a tool that supports clinical reasoning, improves efficiency, expands access, and helps physicians make more informed decisions. The future of AI in orthopaedics will depend not only on technological advancement but also on responsible implementation.

Why This Paper Matters

Orthopaedic surgery is especially well-positioned for AI integration. The field depends on imaging, measurable outcomes, procedural planning, biomechanics, and large clinical datasets. AI may help with fracture detection, diagnostic support, implant planning, postoperative monitoring, outcome prediction, and administrative workflow.

This paper matters because it provides a realistic overview of both the promise and the limitations of AI in orthopaedics. It does not present AI as a perfect solution. Instead, it emphasizes that AI tools must be developed, tested, validated, and applied carefully before they are trusted in real-world clinical practice.

For students and trainees, this article is valuable because it introduces the major ways AI may affect the future of orthopaedic care. For practicing surgeons, it raises important questions about clinical responsibility, workflow, data quality, bias, and patient trust.

As orthopaedics continues to evolve, understanding AI will become increasingly important for anyone involved in clinical care, research, education, or surgical innovation.

Study Overview

This article is a narrative review discussing artificial intelligence and its role in orthopaedic surgery. The authors describe AI as a broad term that includes technologies capable of producing useful outputs from data without relying on traditional human cognition alone.

The article discusses several major areas of AI application in orthopaedics, including diagnostic imaging, fracture recognition, bone tumour detection, predictive modeling, patient-reported outcome measures, mortality and length-of-stay prediction, rehabilitation monitoring, surgical training, and research/data science.

The authors also emphasize that AI has important limitations. These include bias, lack of transparency, poor validation, data quality concerns, and the risk of overreliance on systems that may not yet be ready for independent clinical decision-making.

Key Concepts From the Article

AI as a Supportive Tool in Orthopaedic Care

AI is not meant to replace clinical judgment. Instead, it may serve as a supportive tool that helps clinicians process information more efficiently.

In orthopaedics, this could include identifying fractures on radiographs, recognizing imaging patterns, predicting outcomes, supporting documentation, or helping organize patient data.

The most valuable use of AI may be in areas where large amounts of information must be reviewed quickly and accurately. However, the final responsibility for patient care remains with the physician.

Imaging and Diagnosis

One of the clearest applications of AI in orthopaedics is imaging. Orthopaedic practice depends heavily on radiographs, CT scans, MRI, and other imaging studies.

AI systems may help detect fractures, classify pathology, identify subtle findings, and support diagnostic decision-making. This may be especially useful in busy clinical settings where imaging volume is high.

AI could potentially help reduce missed findings, improve triage, and support earlier diagnosis. However, imaging must always be interpreted in the context of the patient’s history, physical exam, symptoms, and goals of care.

A radiograph alone does not tell the entire story of the patient.

Predictive Models and Patient Outcomes

Another major area discussed in the article is predictive modeling. AI can analyze large datasets to estimate outcomes such as complication risk, mortality risk, length of stay, revision risk, and patient-reported outcome measures.

This has important implications for orthopaedic surgery because many treatment decisions require balancing risks, benefits, patient expectations, and long-term outcomes.

Predictive models may eventually help surgeons counsel patients more effectively and personalize treatment plans. However, these models must be carefully validated before they are used to influence clinical decision-making.

Rehabilitation and Follow-Up

AI may also play a role after surgery. Wearable devices, remote monitoring systems, and digital rehabilitation platforms could allow clinicians to track recovery outside the clinic.

This could be useful for monitoring range of motion, activity levels, gait patterns, rehabilitation compliance, and signs of delayed recovery.

In the future, AI may help identify patients who need earlier intervention, closer follow-up, or a modified rehabilitation plan. This could improve care between visits and help clinicians recognize problems before they become more serious.

Surgical Training and Education

AI may also influence orthopaedic education. Simulation, image-based learning, surgical planning tools, and feedback systems may help trainees develop skills more efficiently.

For medical students and residents, AI may become part of how anatomy, imaging, surgical decision-making, and procedural planning are taught.

However, trainees must still develop independent clinical judgment. AI should strengthen education, not replace the foundational learning required to become a thoughtful clinician.

Clinical Relevance

The clinical relevance of this article is significant because AI is no longer only a future concept. Many AI tools are already being explored in healthcare, and orthopaedics is one of the specialties where the applications are especially clear.

In daily orthopaedic practice, AI may eventually influence how imaging is reviewed, how fractures are recognized and classified, how surgical plans are developed, how implant positioning is predicted, how outcomes are measured, how postoperative recovery is monitored, how documentation and administrative tasks are completed, and how patients are counseled about risk and expected recovery.

For clinicians, the central question is not whether AI will enter orthopaedics. The more important question is how it will be integrated responsibly.

Strengths of the Article

One strength of this article is that it provides a broad overview of AI across multiple areas of orthopaedic surgery. It does not focus on only one subspecialty or one narrow use of AI.

Another strength is that the authors discuss both the benefits and the limitations of AI. This balanced approach is important because conversations about AI can sometimes become either overly optimistic or overly skeptical.

The article also emphasizes the importance of validation, reporting standards, and awareness of bias. These points are essential because AI tools can only be clinically useful if they are reliable, transparent, and tested across diverse patient populations.

Limitations and Considerations

Although AI has strong potential, several limitations remain.

First, AI systems depend on the quality of the data used to train them. If datasets are incomplete, biased, or not representative of diverse patient populations, the resulting AI model may produce unreliable or inequitable recommendations.

Second, many AI tools require external validation before they can be trusted in clinical practice. A model that performs well in one institution may not perform the same way in another setting.

Third, AI can create challenges related to transparency. If clinicians cannot understand how a model concludes, it becomes difficult to know when to trust or question that conclusion.

Finally, AI must not weaken the physician-patient relationship. Orthopaedic care is not only technical. It also involves communication, trust, shared decision-making, empathy, and individualized care.

Discussion

The future of AI in orthopaedics should be approached with both excitement and caution. AI may reduce administrative burden, improve diagnostic efficiency, support surgical planning, and help personalize patient care.

At the same time, AI introduces new responsibilities for clinicians. Orthopaedic surgeons will need to understand the strengths and weaknesses of AI tools. They will need to ask whether a tool has been validated, whether it applies to their patient population, whether it improves outcomes, and whether it supports rather than replaces clinical reasoning.

This article encourages a thoughtful approach. AI should be viewed as part of the future of orthopaedic surgery, but its success will depend on responsible implementation.

Interview Feature

A Conversation with Dr. Hassan Mir

To explore these ideas further, I spoke with Dr. Hassan Mir, Professor of Orthopaedic Surgery and Medical Education and Director of Orthopaedic Trauma Research at the University of South Florida (USF) and the Florida Orthopaedic Institute.

Our discussion touched on leadership, research, healthcare economics, and the growing role of artificial intelligence in orthopaedic trauma.

You hold both an MD and an MBA, and previously served as Chief Financial Officer of the Orthopaedic Trauma Association. How has formal business training shaped the way you approach clinical leadership and research?

Dr. Mir: I think that having an MBA teaches you to think in terms of the entire system rather than isolated problems. When we take care of patients, we’re often presented with individual situations, and you have to focus on the individual patient. But when you’re in a leadership role, you have to think about how your decisions affect the entire organization, the people, and ultimately patient care beyond just the individual patient.

So whether I’m leading a research program, managing a clinical service, or leading an academic program, I think a lot of the principles are the same, and I learned that through obtaining an MBA. You want to focus on improving quality, measuring what you’re doing, and that way you can show that you’re being successful. You want to be a good steward of resources, and that doesn’t necessarily mean cutting costs, but investing wisely in things that actually improve the environment for your team and improve patient care.

As Director of Orthopaedic Trauma Research at USF and the Florida Orthopaedic Institute, what do you see as the most pressing, unanswered question in orthopaedic trauma today?

Dr. Mir: We still have challenges with improving outcomes for all of our patients. You can have two patients come in with a very similar injury, treated in a similar fashion surgically, but they have vastly different outcomes.

I think we need to look beyond just our surgical techniques, which is often the focus because we love surgery, we love operating. But if you look at the overall picture in trying to help patients regain function, return to work, and return to life, our research needs to focus more on the overall recovery and well-being of our patients — looking at the full biopsychosocial model.

You sit at the intersection of clinical practice, research, and medical education. How do you balance these roles, and how do they inform one another?

Dr. Mir: I’m not really sure that they’re separate roles and separate jobs. As you take care of patients, and if you really track your outcomes, that generates research questions. Then, if you analyze your outcomes and publish and present that, it leads to a research career.

Beyond that, teaching and training medical students, residents, fellows, and even practicing surgeons forces you to stay current. They constantly question you and make sure that you have good, solid reasoning for what you’re doing clinically as you’re passing it on to the next generation.

What advice would you give residents and students who want to build a strong research portfolio in orthopaedic trauma early in their career?

Dr. Mir: I think, unfortunately, that for a lot of students it’s become a bit of an arms race, just trying to get numbers and more and more publications to get into the field. But what becomes more impactful is asking good questions rather than just trying to publish papers.

Really doing your homework on that question — especially with all the AI tools we have now — trying to see what’s already been done on the subject, if anything. Even if something has been looked at before, if you critically analyze the literature and look at how you can improve upon what’s been done, or sometimes even repeat what’s been done, that’s where you truly add value. So you want to plan on the front end before just jumping into projects.

I think it’s important for residents and those planning an academic career to think of this as a marathon, not a sprint. You don’t build a career in one year. You build it over time with sustained effort and persistence. There are a lot of roadblocks along the way that you have to overcome.

Your CFO experience gives you a financial lens few surgeons have. How should the next generation of orthopaedic surgeons think about the business and economics of musculoskeletal care?

Dr. Mir: I think it’s important for every practicing orthopaedic surgeon to understand the basics of healthcare economics. I’ve taught a lot of courses and given lectures for residents, fellows, and even medical students on the orthopaedic aspects of financial practice.

At a minimum, a physician should understand the environment we work in and the healthcare system, no matter what practice setting it is. You have to understand what pays for the mission — the old saying is, “no margin, no mission.” If you don’t understand how the institution is funded, and on the personal level how you’re paid, then you’re really doing yourself and your practice a disservice.

Artificial intelligence is rapidly entering orthopaedic trauma, from imaging analysis to fracture classification and outcome prediction. Where do you see the most promise, and where do you remain cautious?

Dr. Mir: AI is rapidly evolving in every aspect of medicine — whether it’s around the surgical care of patients, working them up preoperatively, helping us in the operating room with safer, more precise surgery, or postoperatively helping improve their outcomes with algorithms and apps. I think it’s really impacting everything we do on the patient care side.

On the research, education, and practice side, there are also multiple developments helping us be more efficient and better in every way. I’d caution, though, that I don’t think it’s at the level yet — and I’m not sure it should ever fully — replace clinical judgment, whether in non-procedural or procedural fields. I don’t think AI or robotics are ready to replace us fully. We should think of AI as tools that we can utilize to make us better, but not necessarily as our replacements.

How do you see the relationship between academic research and industry evolving in orthopaedic trauma over the next decade?

Dr. Mir: I’ve been pretty fortunate to have worked in research and academics and developed relationships with industry over the years. I think it’s really critical for surgeons to work with industry partners to help develop implants and technology and to help advance the field.

Whether it comes to digital health, data science, or AI, all of these require collaboration with industry. But the key is to maintain integrity and transparency, and to make sure you’re answering clinical questions in a meaningful way — doing things that improve the field and not just focusing solely on promoting products.

What excites you most about the future of orthopaedic trauma care and research?

Dr. Mir: Over time we keep getting better with our data, our imaging, biologics, and AI, and this is going to lead to improvements in patient care and the ability to deliver more personalized care so we can get everyone’s outcomes the best that we can.

The only way we know we’re getting those outcomes the best we can is by measuring outcomes that actually matter to patients — getting back to work, recovering, being independent, enjoying their lives. While technology is important, the real goal is to maximize our patients’ outcomes and recoveries, especially after orthopaedic trauma.

Finally, what advice would you offer medical students and trainees who hope to become leaders in academic orthopaedic surgery?

Dr. Mir: The first thing is show up, and when you show up, you want to build a reputation for integrity and reliability. I think everybody who goes into orthopaedic surgery wants to be an expert clinician, an expert surgeon. But if you really want to be a leader in academic orthopaedic surgery, you have to develop expertise beyond the operating room — whether that’s research, leadership, education, or business. All of those things can help you develop your niche within academic medicine. Showing up, being trustworthy, and being reliable will lead to more and more opportunities.

Key Takeaways

Artificial intelligence is becoming increasingly relevant to orthopaedic surgery, particularly in imaging, predictive modeling, rehabilitation, surgical planning, documentation, and education.

AI has the potential to improve efficiency, reduce administrative burden, and support more personalized care.

The use of AI in orthopaedics must be approached responsibly, with attention to validation, bias, transparency, patient privacy, and clinical oversight.

AI should support physician decision-making, not replace the judgment, experience, and empathy of the orthopaedic surgeon.

Medical students and trainees should begin learning about AI now, because future physicians will need to understand both the capabilities and limitations of emerging technologies.

Future Directions

Future research should focus on validating AI tools across different patient populations, healthcare systems, and clinical settings. It will also be important to determine whether AI improves not only technical performance, but also patient outcomes, access to care, workflow efficiency, and physician-patient communication.

As AI tools become more common, orthopaedic education may also need to evolve. Future trainees should be prepared to critically evaluate AI systems, understand their limitations, and use them responsibly in patient care.

The future of orthopaedic surgery will likely involve collaboration between surgeons, engineers, data scientists, educators, and patients. The most successful AI tools will be those that solve real clinical problems while preserving the human connection at the center of medicine.

Closing Perspective

Artificial intelligence represents one of the most important technological developments in modern medicine. In orthopaedics, its role is still developing, but the potential applications are significant.

The article by Lisacek-Kiosoglous and colleagues provides an important framework for understanding where AI currently stands and where it may be heading. It reminds us that AI is not simply a tool for automation, but a technology that may reshape how clinicians think about diagnosis, planning, outcomes, education, and access.

Still, the future of AI in orthopaedics must remain centered on the patient. The goal should not be to replace the physician, but to strengthen the physician’s ability to deliver thoughtful, efficient, evidence-based, and compassionate care.

As the field continues to advance, the most important conversations will not only be about what AI can do, but about how orthopaedic surgeons can use it wisely.

Orthopaedic Resource Acknowledgment

I also want to offer a sincere acknowledgment of Orthobullets for its continued role as a valuable educational resource in orthopaedics. Conversations in Orthopaedics is always looking to highlight meaningful resources that support learning, discussion, and professional growth within the field.

To be clear, this acknowledgment is not intended to suggest a formal partnership or collaboration unless such an arrangement is fully approved. Rather, it is meant to respectfully recognize Orthobullets as a resource that many within the orthopaedic community continue to learn from and engage with.

Reference

Lisacek-Kiosoglous AB, Powling AS, Fontalis A, Gabr A, Mazomenos E, Haddad FS. Artificial intelligence in orthopaedic surgery. Bone Joint Res. 2023;12(7):447–454. doi:10.1302/2046-3758.127.BJR-2023-0111.R1.