Artificial Intelligence in Surgery: Potential and Problems

Artificial intelligence (AI), like most industries, is diffusing in sick care. Applications in surgery are emerging and can generally be categorized as :

1. Surgical training and education.
   
   
2. Preoperative assessment and diagnosis and clinical decision support.
   
   
3. Intraoperative surgical performance and quality improvement.
   
   
4. Smart OR's and environment.
   
   
5. Postoperative care and complication risk assessment and predication.
   
   
6. Workflow improvement, like OR start time and turnover efficiencies.
   
   
7. Surgical robotics.
   
   
8. VR and AR and 3-D printing.
   
   
9. Telerobotic and tele-proctored surgery.
   
   
10. Human subject trial recruitment and execution.

Many of these applications are in the research or demonstration phase and will take a while to become the standard of care or achieve widespread dissemination and implementation.

Biomedical AI-Entrepreneurship describes the practice of creating AI products and services to solve bioscience (drugs and devices) and clinical problems. As such, it is the pursuit of opportunity under conditions of uncertainty using scarce resources with the goal of creating user defined value through the design, development and deployment of biomedical innovations that use a predominantly AI backbone, platform or foundation that have a VAST business model. It is a subsegment of digital health products and services.

The use of AI in medicine is evolving rapidly. Here are some updates:

1. Educational platforms, meetings, conferences and magazines.
   
   
2. Robust investment into development and M/A.
   
   
3. Coherent applications combining AI, medtech and biopharma.
   
   
4. Increasing concerns and attention to the ethical, societal, education, manpower development and economic impact of AI in medicine.
   
   
5. How AI is contributing to the 4th industrial revolution.
   
   
6. The intersection of AI and robotics.
   
   
7. The intersection of AI and blockchain.
   
   
8. The impact and perils of decentralized, DIY medicine.
   
   
9. Cybersecurity and confidentiality concerns. If you are not worried yet, read this too.
   
   
10. Concerns and strategies to make transparent algorithms and mitigate AI bias and "eliminate black box bias".
    
    
11. Stories and organizations about physician AI entrepreneurs.
    
    
12. Regulatory, legal and reimbursement challenges.

13. Convergence of AI into medical device and biopharma Current emerging applications appear to fall into three main categories:

Management of chronic diseases – Companies are using machine learning to monitor patients using sensors and to automate the delivery of treatment using connected mobile apps (Example: Diabetes and automated insulin delivery).

Medical imaging – Companies are integrating AI-driven platforms in medical scanning devices to improve image clarity and clinical outcomes by reducing exposure to radiation (Example: GE Healthcare CT scans for liver and kidney lesions).

AI and Internet of Things (IoT) – Companies are integrating AI and IoT to better monitor patient adherence to treatment protocols and to improve clinical outcomes (Example: Philips Healthcare solution for continuous monitoring of patients in critical condition).  

As artificial intelligence projects roll out, organizations will need to rethink the definition of the “work” that people will do. The future of work will become one of the largest agenda items for policy makers, corporate executives and social economists, says Sanjay Srivastava, chief digital officer at Genpact, a professional services firm focusing on digital transformation. Here is how doctors and patients can win the 4th industrial revolution.

What is the secret sauce of successful innovators like AItrepreneurs? They strive to innovate in ways that would have a major impact on markets and society, e.g changing sick care to health care or making the sick care workforce more efficient and effective, and they revamped how their organizations pursued innovation and brought their capabilities together in a single “architecture.” That will mean medtech transforming to techmed will require changing how to collaborate with doctors and patients.

Will AI put society on autopilot? Will surgeons lose their skills in the age of automation?

Here are some of the barriers we will need to overcome.

Those products and services that add value, particularly those that drive down costs and do not interfere with workflow, have a higher chance of success. Those that don't will be relegated to the shiny new object pile and red bagged for disposal.

Arlen Meyers, MD, MBA is the President and CEO of the Society of Physician Entrepreneurs and at Twitter@ArlenMD.