The Emerging Role of AI and Technology in Medicine

The Rapid Expansion of AI in Medicine1

9,673 publications on AI indexed via PubMed in the last 3 years (2020-2022), which is higher than the total of all years prior (8,304 publications between 1967-2019)

Number of yearly publications on PubMed regarding AI was almost 9x higher in 2022 than 10 years prior in 2012

Over

500

AI-enabled medical devices are FDA approved

AI vs Machine Learning vs Deep Learning: What’s the Difference?2,3

AI refers to computer programs, or algorithms, that use data to simulate human intelligence in making decisions or predictions.

The computer analyzes data and makes decisions from a set of rules or instructions created and given to it.

Machine learning involves the AI algorithm teaching itself how to analyze and interpret data.

The algorithm may pick up on patterns that humans may miss.

Their ability to learn and interpret data improves as they are exposed to more information.

Deep learning is a subset of machine learning that uses multilayered networks like the human brain does.

They mimic how our brain cells take in, process, and react to signals from the rest of our body.

The AI will self-discover features unknown or unanticipated by humans.

Risk Prediction

Predict risk of developing disease, or risk of outcomes (ex. hospitalizations)

Appointments Virtual care (telehealth)

Benefits

Record-keeping Electronic medical records Medications via E-pharmacies Smartphones or web-based apps to record symptoms or medication use

Benefits

Accessibility

Increasing accessibility for remote and undeserved populations

Improved Outcomes

Patients get more personalized care

Accuracy and Reliability

More accurate, reliable and precise diagnoses

1. U.S. Food & Drug Administration. Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices [Internet]. FDA; 2022. Available from: https://www.fda.gov/medical-devices/software-medical-device-samd/ artificial-intelligence-and-machine-learning-aiml-enabled-medical-devices

2. Jaber N. Can artificial intelligence help see cancer in new ways? [Internet]. 2022 [cited 2023 May 14]. Available from: https://www.cancer.gov/news-events/cancer-currents-blog/2022/artificial-intelligence-cancer-imaging

3. Shreve JT, Khanani SA, Haddad TC. Artificial Intelligence in oncology: Current capabilities, future opportunities, and ethical considerations. American Society of Clinical Oncology Educational Book. 2022 Jun 10;(42):842–51. doi:10.1200/edbk_350652

Monitoring Wearables to monitor physical activity or heart rate (ex. Fitbits or smartwatches)

Treatment Identifying the best treatment Predicting response to treatment

Challenges

Generalizability

Can the algorithm be generalized to broader populations?

Bias

Will lack of diversity used in training datasets bias the algorithm?

Transparency

How can doctors and patients understand how the algorithm came to a conclusion?

Retraining

Can the algorithm need to be retrained every time there’s new equipment?

Regulation

How will changes to existing algorithms be monitored?

4. Davenport T, Kalakota R. The potential for artificial intelligence in healthcare. Future Healthcare Journal. 2019 Jun;6(2):94–8. doi:10.7861/futurehosp.6-2-94 5.