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Thyroid CancerNCT07234539

Evaluation of an Artificial Intelligence-enabled Clinical Assistant to Support Thyroid Cancer Management

A study testing AI-enabled clinical assistant in people with Thyroid Cancer and Large Language Models, run by The University of Hong Kong at 2 sites in Hong Kong.

Enrolling by invitation

Enrolling by invitation. The study team selects and invites participants, usually from an existing group of patients.

Sites and contacts
Official record
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Trial summary

This study aims to evaluate the clinical feasibility of adopting artificial intelligence (AI)-based models to improve clinical management of thyroid cancer. Read more about this study

Who is it for?
Ages 18 years and olderHealthy volunteers can take part
Conditions the study is for
Thyroid Cancer, Large Language Models
What is being tested?
AI-enabled clinical assistant
Could I receive a placebo?
No, everyone receives an active treatment
How many people
76 participants
Where
2 sitesHong Kong
Study dates
2 Oct 2025to 30 Apr 2027
Phase
Interventional
Are there results?
Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 years and older
  • All sexes
  • Healthy volunteers accepted
  • Adult, Older adult

Who may be able to join

  • Consenting medical students
  • Consenting clinicians who are directly involved in the care of thyroid cancer patients, including endocrine surgeons, endocrinologists, oncologists, and pathologists.

Who cannot join

  • Medical students and clinicians who had reviewed the clinical notes or were involved in the processing of the clinical notes prior to the commencement of trial

Trial locations and contacts

2 sites in 1 country. Contact the study team or a site near you to ask about taking part.

Hong Kong2 sites

  • Department of Surgery, School of Clinical Medicine, The University of Hong Kong

    Hong Kong

  • School of Public Health, The University of Hong Kong

    Hong Kong

Other trials in Hong Kong

About this study

Official title: A Randomized Controlled Trial to Evaluate an Artificial Intelligence-enabled Clinical Assistant Leveraging Large Language Models for Thyroid Cancer Staging and Risk Stratification Among Medical Students and Clinicians

This study aims to evaluate the clinical feasibility of adopting artificial intelligence (AI)-based models to improve clinical management of thyroid cancer.

Read the detailed description

With recent advancements in technology, AI has become widely applicable to visual text recognition in clinical settings. AI-powered text recognition is emerging as a highly efficient, sustainable, and cost-effective tool for decision making and personalised medicine. Numerous studies have employed natural language processing (NLP) algorithms, particularly large language models (LLMs), to convert unstructured free-text from clinical consultation notes within electronic health records (EHR) into structured data, thus enriching individual clinical profiles in the EHR databases. Over time, these AI models have continuously improved their predictive accuracy and performance through self-learning (or unsupervised learning). While AI models had made a significant impact in oncology practices overseas, their utility for text recognition in oncology remains limited in Hong Kong. This proposed study aims to evaluate the clinical feasibility of adopting AI-based models to improve time efficiency, accuracy, and end-users' confidence in diagnostic assessment and risk prediction, compared against traditional workflows without AI assistant for thyroid cancer management.

Being tested
AI-enabled clinical assistant
Keywords
Thyroid Cancer, large language models, LLMs, natural language processing, NLP
Medical subject headings
Thyroid Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • AI-enabled clinical assistantOther

    Participants will provide the caner staging and risk category of each thyroid cancer patient as well as the participants' confidence for the above diagnostic assessments with AI-enabled clinical assistant as the intervention. The AI assistant is powered by LLMs and comprises a clinical dashboard. The clinical dashboard displays the original clinical notes and summarizes cancer staging and risk category of each thyroid cancer patient generated from the backend processing of the clinical assistant. Supporting evidence from original clinical notes is also highlighted for participants' verification.

Study groups in NCT07234539
Study groupRoleWhat they receive
AI-enabled clinical assistantExperimentalParticipants will provide the caner staging and risk category of each thyroid cancer patient as well as the participants' confidence for the above diagnostic assessments with AI-enabled clinical assistant as the intervention. The AI assistant is powered by LLMs and comprises a clinical dashboard. The clinical dashboard displays the original clinical notes and summarizes cancer staging and risk category of each thyroid cancer patient generated from the backend processing of the clinical assistant. Supporting evidence from original clinical notes is also highlighted for participants' verification.
Receives: Other: AI-enabled clinical assistant
Manural chart reviewNo interventionParticipants will provide the caner staging and risk category of each thyroid cancer patient as well as the participants' confidence for the above diagnostic assessments with manual chart review.

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Efficiency

    The time required to complete reviewing one set of clinical notes is compared between intervention and non-intervention groups

    Measured: Between intervention group and non-intervention group. Cross-over in 4-26 weeks

Secondary outcomes (2)

  1. Accuracy of Cancer Staging and Risk Stratification by Participants Compared with Ground Truth across Intervention and Non-intervention Groups

    The study will compare the accuracy of cancer staging and risk category assessed by the participants across the intervention group with AI assitance and non-intervention group without AI asssitance.

    The participants will review the clinical notes and assess the cancer staging and risk category for each thyroid cancer patient with or without the AI assistant. Participant provided assessments will be compared against the ground truth established by the clinical investigators of the study to guage the accuracy which is quantified as the percentage of correctly graded cancer staging and risk stratification. The accuracy will be compared between the intervention group and non-intervention groups using t-tests to evaluate the clinical impact of the AI assistant.

    Measured: Between intervention group and non-intervention group. Cross-over in 4-26 weeks

  2. Participants' Confidence in Cancer Staging and Risk Stratification as Assessed by a 0-10 Scale Questionnaire

    The study will compare the participants' confidence in grading cancer staging and risk category between the intervention group with AI assistance and non-intervention group without AI-assistance.

    After evaluating each thyroid cancer case for providing cancer staging and risk category, participants will complete a short questionnaire rating their confidence in providing their assessments on a scale from 0 (lowest) to 10 (hightest). Meanw confidence score will be compared between the intervention group and non-intervention group to evaluate the clinical impact of the AI assitant.

    Measured: Between intervention group and non-intervention group. Cross-over in 4-26 weeks

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted18 Nov 2025
  2. Study start2 Oct 2025
  3. Primary completion31 Mar 2027 (estimated)
  4. Study completion30 Apr 2027 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Interventional
Phase
Phase N/A
Primary purpose
Health services research
Allocation
Randomised
Intervention model
Crossover
Masking
Single blind
Who is masked
Outcomes assessor
Enrolment
76 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT07234539
Sponsor's protocol ID
UW24-319-RCT
Status last verified
Jul 2026
First submitted
29 Sep 2025
Last updated
21 Jul 2026
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
Yes: Only anonymized IPD used in results publications will be shared so that re-identification of individuals is not possible.

Publications

  • Fung MMH, Tang EHM, Wu T, Luk Y, Au ICH, Liu X, Lee VHF, Wong CK, Wei Z, Cheng WY, Tai ICY, Ho JWK, Wong JWH, Lang BHH, Leung KSM, Wong ZSY, Wu JT, Wong CKH. Developing a named entity framework for thyroid cancer staging and risk level classification using large language models. NPJ Digit Med. 2025 Mar 1;8(1):134. doi: 10.1038/s41746-025-01528-y.

    PubMed 40025285

Questions about this trial

What is this clinical trial studying?

A study testing AI-enabled clinical assistant in people with Thyroid Cancer and Large Language Models, run by The University of Hong Kong at 2 sites in Hong Kong.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: enrolling by invitation, as of the sponsor's last update on 21 Jul 2026. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 2 sites in Hong Kong. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

Efficiency (time frame: Between intervention group and non-intervention group. Cross-over in 4-26 weeks). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT07234539, which also lists 1 linked publication.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 21 Jul 2026.

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