Technical Name Artificial intelligence assisted prediction system of Hepatocellular carcinoma treatment efficacy and post treatment recurrence.
Project Operator National Taiwan University
Project Host 梁嘉德
Using several machine learning techniques and deep learning algorithms, we are progressing the development of liver treatment tracking and recurrence prediction models.
Combined with the data processing algorithm, and using the complete database of National Taiwan University Hospital as a data source, a set of auxiliary diagnostic modules for the treatment effectiveness and postoperative recurrence prediction of liver cancer was established.
Scientific Breakthrough
Due to the team's new plan approved for 108 years, it is currently in the early stage of database establishment.
At present, there is no scientific breakthrough information related to technology. We follow up to establish a predictive recurrence model for liver cancer, and we look forward to breakthrough technology development.
Industrial Applicability
As technology advances, the AI field is applied to a wider range of medical judgments.
Successful development of the system will not only greatly reduce the burden on doctors, but also help doctors improve the accuracy of recurrence prediction.
Because of the higher efficiency and correctness of judgment, this can improve the likelihood of being cured by the patient.
Keyword Hepatocellular carcinoma RFA liver cancer treatment artificial intelligence SVM Neural Network deep learning NLP Liver Cancer database
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