About us
Improving the healthcare experience with AI algorithms
Algorithms are at the heart of diagnostic medicine. Through this, healthcare organizations can be provided with pre-analyzed data on individual risk and deliver data science-driven medical care.
In order to prevent major serious diseases in, TALOS is developing a high-performance AI learning model through insights and research from experts in the field. It is our goal to help individuals increase disease awareness and healthcare institutions to increase screening efficiency for all.
With our team of top medical experts and professionals, our vision is to innovate the health care experience with medical artificial intelligence and spearhead the industry to create social and economic value.
The Creators of TALOS Corp.
Tackeun Kim, MD, MSc
CEO
MD, Seoul National University College of Medicine
MSc in Neuroscience, Seoul National University School of Medicine
Current Director of Information Technology,
Korean Society for Digital Convergence Neurosurgery
Former Associate Professor of Neurosurgery,
Seoul National University Bundang Hospital
Former Professor of Medical Artificial Intelligence Center,
Seoul National University Bundang Hospital
Former Visiting Professor,
KAIST Graduate School of Artificial Intelligence
Jin-Deok Joo, MD, PhD
Deputy CEO
MD, Chonnam National University College of Medicine
PhD, Sungkyunkwan University
Current Associate Professor of Neurosurgery,
Jeju National University Hospital
Former Professor of Neurosurgery,
Seoul National University Bundang Hospital
Our Journey
2021-03-29
Faculty Startup Approval
Obtained startup approval through faculty startup review by the Seoul National University Startup Review Committee
2021-05-06
TALOS Corp. Registration
Promoters: Tackeun Kim, Jin-deok Joo, Jaehyuk Heo, Sangjun Park, Jeonggil Jung
2021-08-10
Seed Round Investment
KRW 300M
2021-09-14
Seed Round Investment
KRW 200M
2022-03-11
22021 1st Datathon Bundang Seoul National University Hospital Big Data Center
Grand Prize (1st Place)
2022-03-11
Seoul National University Bundang Hospital K-Bio Health Selection of Projects Funding
Healthcare Innovation Park, K-Bio Center
2022-05-13
TIPS Selection
R&D period:2022.05~2024.04
AI-based cerebral cardiovascular disease risk assessment
2022-09-30
Selected for the Gangnam-gu Job Startup Hub Center
160 Yeoksam-ro, Gangnam-gu, Seoul, Korea Job Startup Hub Center
2022-11-02
Venture Certification
2022-12-01
Selected for TIPS startup commercialization
Agreement period: 2022.11 ~ 2023.08
ANRISK, AI-based cerebral aneurysm risk prediction platform
2023-06-08
Participated in Medical Taiwan 2023
June 8th~10th
2023-07-25
2023 Healthcare Big Data Startup Competition
Grand Prize (Minister of Health and Welfare Award)
2023-08-30
CHALLENGE! K-Startup 2023 Innovation Startup League (General League)
Grand Prize (Minister of Startup Promotion Award)
2023-10-20
The 11th Pan Government Data Startup Competition
Grand Prize (Presidential Award)
2023-12
Series A Funding – 3.8 billion KRW
Premier Partners, BA Partners, Medinno Partners
2024-04-02
Logo Renewal
2024-05-31
LINA 50+ Awards
Creative Innovation – 1st place
2024-09-11
Participated in Medical Fair Asia 2024
September 11th~13th
2024-11-06
Leisure-Friendly Certification
Certification received by the Ministry of Culture, Sports and Tourism
2025-02-13
ANRISK® Trademark Registration Complete
Received from the Korean Intellectual Property Office
2025-05-15
Selected as one of KAIST’s 12 AI Innovation Companies
Recognized in the “AI Pioneer” category by the KAIST School of Business and Technology Management
Our Patents & Research Publications
Device and Method for Predicting Intracranial Aneurysm Risk
- Apparatus for Predicting Intracranial Aneurysm Using Retinal Fundus Image and Method for Providing Intracranial Aneurysm Prediction Results Using the Same
- Diagnostic Aids System for Obstructive Sleep Apnea Using Cephaloradiographs and Method for Providing Diagnostic Aids thereof
- Diagnostic Aids Method and Device for Cardioembolic Cerebral Infarction Using Chest Radiographs
- Device and Method for Identifying Anatomical Location Using Flexible Bronchoscopy Images
- Prediction of intracranial Aneurysm Risk using Machine Learning
Scientific reports 10, no. 1 (2020): 1-10 - Validation of prediction algorithm for risk estimation of intracranial aneurysm development using real-world data
Scientific reports 13, (2023) - Incidence and risk factors of intracranial aneurysm: a national cohort study in Korea
International Journal of Stroke 11, no. 8 (2016): 917-927 - Machine learning for detecting moyamoya disease in plain skull radiography using a convolutional neural network
EBioMedicine 40 (2019): 636-642 - Stroke prevention by direct revascularization for patients with adult-onset moyamoya disease presenting with ischemia
Journal of Neurosurgery 124, no. 6 (2016): 1788-1793