AI in surgery: potential and problems

GUEST POST from Arlen Meyers

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

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 AIntrepreneurhship 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:

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

14. Smart speakers in the OR and examining rooms

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 AIntrepreneurs? 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?Where is the evidence that robotic surgery adds value and when?

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

Why is the gap between companies’ AI ambition and their actual adoption so large? The answer is not primarily technical. It is organizational and cultural. A massive skills and language gap has emerged between key organizational decision makers and their “AI teams.” It is a barrier that promises to stall, delay, or sink algorithmic innovations. And it is growing, not shrinking. The problem is that healthcare professionals are from Venus and technologists are from Mars. They have different mindsets and how they communicate.

Here are emerging data security and risk management trends.

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.

Sign up here to join 17,000+ leaders getting Human-Centered Change & Innovation Weekly delivered to their inbox every week.