The four AI Tools designed by the University of Hong Kong are designed to cover more than 30 indications. Credit: Shutterstock / Jimmy Chan.

The Hong Kong University of Science and Technology (HKUST) has announced the development of four AI models designed to assist in care across 30 types of cancers and diseases, powered by the university’s AI supercomputing facility.

The four new AI-driven models include MOME, a breast cancer diagnostic tool designed to distinguish malignant from benign breast lumps using MRI scans, with the University claiming the AI can achieve accuracy levels comparable to radiologists with five or more years of experience. It was created with the intent of providing an alternative to the more intrusive diagnostic form of biopsies and can predict a patient’s responses to neoadjuvant chemotherapy.

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The second of the new tools is the mSTAR Pathology Assistant Tool, designed to assist pathologists by reducing workloads by streamlining or automating several tasks, including up to 40 diagnostic and prognostic tasks. The system works by directly modelling whole slide images and augmenting them with multimodal knowledge, a concept that involves combining different types of data and learning styles to create a more comprehensive understanding.

Hao Chen, assistant professor in the Department of Computer Science and Engineering and project lead, said: “We hope our AI tools will serve as valuable assistants for doctors, improving diagnostics, personalising treatment plans, and streamlining different tasks.

“Building on our success, we are developing a wide range of AI applications targeting various clinical tasks, particularly precision oncology, and computer-assisted intervention, while continuously enhancing our models with more data and modalities. By collaborating closely with clinical partners, we aim to drive improvements in patient care over the long term.”

The third AI tool, MedDr, is a multimodal language model able to answer questions, generate medical reports, and provide initial diagnoses based on medical images to help clinicians make decisions faster. The fourth, XAIM, is a model designed to help healthcare workers feel more comfortable with adopting AI models by explaining how medical AI models reach their decisions.

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The announcement comes after it was found that medtech companies are liable to lose 4% of their annual revenue as a result of inefficiencies, with AI set to remedy one of the primary causes of physician burnout. Elsewhere in the field of AI tools, BrainSpec has found that its magnetic resonance spectroscopy (MRS) platform can detect previously undetectable brain injuries.

AI is set to be one of the biggest economic drivers in the medtech space over the next few years according to GlobalData’s AI in Healthcare report.