NCKU and Harvard Collaborate and Use AI to Read and Predict Colorectal Cancer and is Featured in International Journal-國立成功大學永續發展SDGs

NCKU and Harvard Collaborate and Use AI to Read and Predict Colorectal Cancer and is Featured in International Journal

SDG3

NCKU and Harvard Collaborate and Use AI to Read and Predict Colorectal Cancer and is Featured in International Journal

Synergy Correlation

 
The incidence of colorectal cancer in Taiwan is the highest in the world, and the mortality rate is the second highest among all cancers in Taiwan. In fact, early detection and treatment of colorectal cancer has a good cure rate. After more than 2 years of collaboration with the medical team of Harvard University, the team led by Prof. Jung-Hsien Chiang (Scopus) at NCKU has successfully developed an AI algorithm to detect and predict colorectal cancer, including prediction of key genetic aberrations, genetic expression, and survival, as well as identification of clear correlation with pathological sections. The research results were published in the international journal Nature Communications in April 2023 ( Full content ).


Professor Chiang said that artificial intelligence to assist in medical treatment is one of the research phenomena today, but so far not many models have been able to build a complete AI interpretation and prediction for specific diseases. The model established by NCKU and Harvard is dominated by Westerners as the patient data. The team of NCKU has planned to conduct localized research with Taiwanese people and collaborated with domestic medical centers (e.g NCKU Hospital) to implement this colorectal cancer prediction system.


Professor Chiang pointed out that this cross-country study is expected to open up the vanguard of digital transformation of hospitals, and if it can be used in actual medical treatment, it will significantly improve the accuracy and speed of diagnosis by pathologists, and can effectively solve the problem of shortage of pathologists or not accumulating enough experience, as well as help physicians to design a more personalized medical plan for patients, and monitor the condition and progress during treatment to ensure the success rate of treatment.


In this cross-country study, the information required for the AI algorithm, such as pathological sections of colorectal cancer patients, genetic expression profiles, patient treatment and survival tracking, all came from the United States. Prof. Chiang revealed that one of the keys to AI algorithms is to have huge data, and the richness of the data in this collaboration can only be described as massive, spanning a timeline of 1 to 20 years and even 28 years of patient tracking data.


The information team at NCKU has contributed their "Golden Brain". There are 6 members in the team, besides Prof. Chiang, the other 5 are all his students. During the two to three years of research, the team members encountered many challenges, such as the need to supplement the lack of professional knowledge in cancer, the period of encountering bottlenecks in the design of algorithms, and even the blackout of computer calculation day and night. Fortunately, the team did not give up and persevered, and was able to obtain good results.


Professor Chiang said that he was a co-corresponding author of the research results in the journal Nature Communications, and the first five authors were all his students, which shows the power of research in the field of information technology at NCKU.


More Information

  Chiang, Junghsien
  https://www.scopus.com/authid/detail.uri?authorId=7201425280

  Histopathology images predict multi-omics aberrations and prognoses in colorectal cancer patients
  Tsai, P.-C., Lee, T.-H., Kuo, K.-C., ...Ogino, S., Yu, K.-H., Nature Communications, 2023, 14(1), 2102

Prof. Jung-Hsien Chiang (center, first row) and the information team

Team of NCKU and Harvard having online meeting

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國立成功大學SDGs離岸團隊擁有全球風能維護團隊5年的全球風控中心,並擁有5年的第一套商業套化輪播式光達設備;除建立捲簾式的移動監控技術,與ECN展示現歐洲海事外展能力。建築複合功能設計團隊與建築外置經驗塔在介紹節能建築的同時,驗證建站技術也在技術中心及平台上進行技術測試,分享階段平台成果試驗成果未來生結合應用的架構,以作為開發系統的架構。