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AI and Wearable Devices for Type 2 Diabetes — Level B1 — a person holding a smart phone next to an electronic device

AI and Wearable Devices for Type 2 DiabetesCEFR B1

6 Dec 2025

Adapted from U. Buffalo, Futurity CC BY 4.0

Photo by Towfiqu barbhuiya, Unsplash

Level B1 – Intermediate
4 min
211 words

A team at the University at Buffalo published a comprehensive meta-review in NPJ Digital Medicine. The researchers screened about 5,000 peer‑reviewed studies and selected 60 that examined the integration of AI and wearable technology in diabetes care. Wearables such as continuous glucose monitors provide frequent readings, and AI models can recognise patterns and predict glucose changes before they happen.

The review reports several benefits. AI-enhanced wearables can predict glucose changes up to one to two hours ahead, which may help people keep steadier glucose control and receive personalised guidance that reflects daily routines, activity and sleep. These systems can also reduce clinician workload by organising large data streams and flagging what needs attention. For people with prediabetes, early use of wearables plus AI could support lifestyle changes and perhaps delay progression to diabetes.

However, the review lists key limitations: research is uneven, many AI models act as "black boxes," sample sizes are limited and demographic coverage is narrow. The authors say larger studies, better validation and more transparent models are needed before AI-enabled wearables become routine in clinical care. The study was supported by the American Diabetes Association, the National Institute of Diabetes and Digestive Kidney Disease, and the National Institute for Minority Health and Health Disparities.

Difficult words

  • integrationbringing parts together to work as one
  • wearablean electronic device worn on the body
    wearables
  • recognisesee or find patterns in information
  • personalisedmade to match a person's needs or life
  • cliniciana health professional who treats patients
  • prediabetesa health condition before diabetes develops
  • demographicrelating to groups of people by characteristics
  • validationtesting to make sure results are accurate

Tip: hover, focus or tap highlighted words in the article to see quick definitions while you read or listen.

Discussion questions

  • Would you consider using a wearable that predicts glucose changes? Why or why not?
  • What concerns do you have about AI models that act like "black boxes" in medical care?
  • How might organising large data streams with AI change the work of clinicians in your country?

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