Thyroid most cancers AI assistant developed in Hong Kong

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Thyroid most cancers AI assistant developed in Hong Kong

A big language model-powered AI assistant developed in Hong Kong has demonstrated excessive accuracy in thyroid most cancers staging and danger classification.

A crew of researchers from the Li Ka Shing School of Drugs of the College of Hong Kong (HKUMed), the InnoHK Laboratory of Information Discovery for Well being, and the London Faculty of Hygiene and Tropical Drugs performed the research which constructed what may very well be the world’s first AI assistant for classifying thyroid most cancers stage and danger classes.  

FINDINGS

The AI mannequin leverages 4 open-source LLMs, specifically Mistral by French startup Mistral AI, Meta AI’s Llama mannequin, Google’s Gemma, and Qwen by China-based Alibaba Cloud, to analyse free-text medical paperwork, together with medical notes, pathology studies, and operation information. 

It gives most cancers staging and danger classification primarily based on the extensively used eighth version of the American Joint Committee on Most cancers’s (AJCC) TNM most cancers staging system and the American Thyroid Affiliation (ATA) classification system.

The mannequin was skilled with and validated in opposition to open-access pathology studies from The Most cancers Genome Atlas Programme. It was additionally validated in opposition to some 35 pseudo-cases created by endocrine surgeons.  

Based mostly on findings printed in npj Digital Drugs, the AI assistant achieved total accuracy of 92.9%-98.1% within the AJCC most cancers staging and 88.5%-100% within the ATA danger classification. 

“We performed additional comparative assessments with a ‘zero-shot method’ in opposition to the most recent variations of DeepSeek – R1 and V3, in addition to ChatGPT-4o. We had been happy to seek out that our mannequin carried out on par with these highly effective on-line LLMs,” added the research’s lead, HKUMed professor Joseph Wu Tsz-kei.

WHY IT MATTERS

Most cancers staging and danger classification are achieved to information remedy choices and predict affected person survival. Often achieved manually, this job can take a lot time, the analysis crew mentioned, and they also began growing the AI assistant.

Contemplating its excessive accuracy, researchers counsel that the AI instrument might assist reduce the time clinicians spend on pre-consultation preparation by half. 

Prof Wu additionally shares that they built-in offline functionality into their AI assistant to permit its deployment with out the necessity for sharing or importing delicate affected person info.

“The AI mannequin is flexible and may very well be readily built-in into varied settings in the private and non-private sectors, in addition to native and worldwide healthcare and analysis institutes,” added Dr Matrix Fung Man-him of HKUMed, who additionally led the research. 

The analysis crew now plans to additional validate their AI assistant with a bigger real-world dataset earlier than it may be deployed in hospitals and different medical settings.

THE LARGER TREND

There have been improvements in Hong Kong just lately which have additionally leveraged massive language fashions and generative AI to boost the effectivity of illness prognosis and administration. 

Early this 12 months, HKU engineers launched their genAI-based system for label-free tumour imaging, which they proposed as an economical option to do single-cell evaluation. 

Over on the Chinese language College of Hong Kong, engineers have built-in DeepSeek right into a blood stress administration system, which might scale its rollout, particularly in rural and distant areas, because it doesn’t require expensive tools.

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