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Incorporating Clinical Rules into AI for Prostate Cancer Diagnosis

Published on:

14 May 2024

Primary Category:

Computer Vision and Pattern Recognition

Paper Authors:

Tiantian Zhang,

Manxi Lin,

Hongda Guo,

Xiaofan Zhang,

Ka Fung Peter Chiu,

Aasa Feragen,

Qi Dou


Key Details

Adapts language model to MRI data and guidelines without extra parameters

Incorporates guidelines via instructions for feature generation

Distills instruction-guided features into diagnosis model

Improves model accuracy on clinical data

Enhances model alignment with expert knowledge

AI generated summary

Incorporating Clinical Rules into AI for Prostate Cancer Diagnosis

This paper proposes a new approach to integrate clinical guidelines into AI models for prostate cancer diagnosis, without needing extra annotations or model parameters. It adapts a large multi-modal language model using a two-stage process: first to handle MRI inputs, then to incorporate the guidelines as instructions. By distilling these instruction-guided features into the diagnosis model, it aligns the model with expert knowledge in the guidelines. Evaluated on real clinical data, this approach improved model accuracy and clinical applicability.

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