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, CEO
Former) Professor of Neurosurgery, Seoul National University Bundang Hospital
Graduated from Seoul National University
Current Director of Computing at the 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 at KAIST Graduate School of Artificial Intelligence
Jin-Deok Joo, Deputy CEO
Professor of Neurosurgery, Jeju National University Hospital
Graduated from Chonnam National University
Current Assistant Professor of Neurosurgery at Jeju National University Hospital
Former Professor of Neurosurgery at 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
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