participants
NTU Med God-A data platform for precision medicine
CyberKnife uses a high-energy X-ray machine on a robotic arm to precisely deliver radiation beams that destroy tumor cells and stop tumor growth while avoiding damage to healthy tissue.
Before treatment, need to create a personalized treatment plan to evaluate the unique shape, size and location of the tumor, as well as the tissue and structures that need to be protected.
Clinical challenge:
1-CyberKnife mostly is used for tiny tumor
2-It is a very time-consuming process, It will take hours for two professionals (one doctor and one medical physicist) to perform the computer planning, and for complicated case, it will take a day to create the plan for a patient
In order to enhance the workflow, we want to train the AI to identify the location of brain tumors and contour it.
Through this challenge, we hope to encourage participants to learn from each other and optimize the training process to get the best model performance as possible.
Welcome to join us! Action now!
Organizer:
台大醫神-精準醫療人工智慧輔助決策系統(NTU Med God-A data platform for precision medicine )
Co-organizers
科技部補助全幅健康照護中心(MOST All Vista Healthcare Center)
商之器科技(EBM Technologies )
台大醫院神經外科(The Neurosurgery in NTUH)
國立台灣大學生醫電子與資訊學研究所(Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University)
威強電工業電腦(IEI Integration Corp.)
威聯通科技(QNAP Systems, Inc.)
The Ministry of Science and Technology All Vista Healthcare Center (MAHC), a research center launched in March 2018 and fully supported by Taiwan government, is dedicated to AI applications in medicine and healthcare. The MAHC aims to establish a world level platform to facilitate explorations of AI model-driven or data-driven technology for medical and healthcare, through which any technology targeted for medical AI applications can be quickly developed and validated. The MAHC is expected to lead and promote domestic research teams specialized in biomedical and healthcare fields and in turn to improve the health and well-being of people in Taiwan.
There are currently 11 project teams, affiliated with top academics and medical centers in Taiwan, under the MAHC. Based on the research topics, the projects can be categorized into five areas: mental healthcare, medical imaging, decision support, precision drug use, and AI-ethical, legal, and social impact (AI-ELSI).
In addition to working with research groups from domestic institutions in Taiwan, the MAHC is forming collaborations/partnerships with internationally renowned academics such as Stanford University, Harvard Medical School and its affiliates, and University of Toronto (Canada) for the advancement of medical AI research. Moreover, the MAHC is also working with industrial partners to promote commercialization and entrepreneurship.
We anticipate that the MAHC become a top-notch cluster for digital health and medicine so that medical achievements enhanced by the AI techniques in Taiwan can be more easily recognized worldwide.
1st place: One team $USD 2,000 (tax included)+ QNAP NAS*1 (value USD300)
2nd place: One team $USD 1,700 (tax included)+ QNAP NAS*1 (value USD300)
3rd place: One team $USD 1,300 (tax included)+ QNAP NAS*1 (value USD300)
4th place: One team $USD 1,000 (tax included)+ QNAP NAS*1 (value USD300)
Remark1: After submission of AI model and inference source code,the top 4 winners will receive the prize money after the deduction of tax. (vary by country)
Start from Mar 17, 2021
DATES | Events |
Jun 25, 2021 | Team merge date |
Jun 25, 2021 | Submit end date |
If any question, you may leave a message in this forum,
or contact iEi PM Jessica <jessicalin@ieiworld.com>
DATES | Events |
Jul 3, 2021 | Team merge date |
Jul 3, 2021 | Submit end date |
Remark1: Freeze leaderboard while challengers can still summit results to update scores. The winner will be revealed on Award Announcement Day!
Remark2: Top 10 teams: 8-minute oral presentation (pls send slides before Sept.25)
Rules:
The maximum number of uploading is 5 times per day
Max 5 challengers in one team, at least one student