AI digital twin platform advances personalized cancer treatment planning
A research team at The Hong Kong Polytechnic University (PolyU) has developed a patient-centric "Artificial Intelligence (AI) Virtual Patient Simulation System," overcoming the limitations of conventional static diagnosis.
A team of researchers at The Hong Kong Polytechnic University has created an advanced Artificial Intelligence (AI) system that creates a virtual representation of a patient, known as a digital twin. This system integrates various types of patient data, such as genomic information, medical imaging, and clinical records, to provide a continuously updated and dynamic model of the patient's condition.
By tracking changes in real-time and predicting the potential effectiveness of different cancer treatments, the AI system assists healthcare professionals in making more precise and personalized treatment plans. The system consists of a platform for healthcare professionals and a patient-facing mobile application, which collaboratively enables doctors to monitor patient conditions, assess treatments, and patients to actively participate in their own health management.
In a study published in Medical Image Analysis, the researchers developed a new multimodal deep learning framework called Visual-Global Relation Fusion Network (ViGNet) specifically for predicting immunotherapy response in non-small cell lung cancer patients. Their framework combines visual features from histopathological images with clinical data like gene expression profiles, resulting in an 82.55% discrimination performance in predicting immunotherapy response, surpassing previous methods.
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