A big language model-powered AI assistant developed in Hong Kong has demonstrated excessive accuracy in thyroid most cancers staging and threat classification.
A workforce of researchers from the Li Ka Shing College 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 carried out the examine which constructed what may very well be the world’s first AI assistant for classifying thyroid most cancers stage and threat classes.
FINDINGS
The AI mannequin leverages 4 open-source LLMs, particularly 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 scientific paperwork, together with scientific notes, pathology stories, and operation data.
It gives most cancers staging and threat 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 stories from The Most cancers Genome Atlas Programme. It was additionally validated in opposition to some 35 pseudo-cases created by endocrine surgeons.
Primarily based on findings revealed 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 threat classification.
“We carried out additional comparative checks with a ‘zero-shot strategy’ in opposition to the most recent variations of DeepSeek – R1 and V3, in addition to ChatGPT-4o. We have been happy to seek out that our mannequin carried out on par with these highly effective on-line LLMs,” added the examine’s lead, HKUMed professor Joseph Wu Tsz-kei.
WHY IT MATTERS
Most cancers staging and threat classification are executed to information remedy choices and predict affected person survival. Normally executed manually, this process can take a lot time, the analysis workforce stated, and they also began creating the AI assistant.
Contemplating its excessive accuracy, researchers counsel that the AI device may assist minimize 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 data.
“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 examine.
The analysis workforce now plans to additional validate their AI assistant with a bigger real-world dataset earlier than it may be deployed in hospitals and different scientific settings.
THE LARGER TREND
There have been improvements in Hong Kong lately which have additionally leveraged giant language fashions and generative AI to boost the effectivity of illness analysis and administration.
Early this 12 months, HKU engineers launched their genAI-based system for label-free tumour imaging, which they proposed as an economical technique 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 may scale its rollout, particularly in rural and distant areas, because it doesn’t require expensive tools.
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