Contact us


    Collection and Use of Personal Information. *


    Integrate AI and the human
    intelligence to optimize patient

    Deep Bio

    Deep Bio was founded with the transformative mission: To advance patient outcomes by driving innovation in technology, while empowering clinicians by providing the tools to make critical decisions. We envision a world where clinicians are empowered with technology designed to unlock personalized insights and enhance healthcare delivery, so they can focus more on what they do best: caring for their patients.

    Solving Unmet Medical
    Needs with the Power of AI

    1 Challenges

    Pathology is a field of medicine where specimen samples such as organ, body tissue, or body fluids are examined to diagnose presence and severity of disease including cancer. In current practice, pathologists examine glass slides of processed specimens, using microscopes.

    Traditional Pathology Workflow

    • Step 1 Biopsy is performed on a patient with clinical suspicion of cancer.
    • Step 2 Tissue specimen is processed, mounted and stained on glass slides for examination.
    • Step 3 A pathologist examines the glass slides on a microscope and issues a final diagnosis that determine the follow up and treatment care for the patient.

    Traditional Pathology Workflow (for Prostate Cancer)

    • Step 1 Prostate needle biopsy is performed on a patient with clinical suspicion of prostate cancer.
    • Step 2 Tissue specimen is processed, mounted and stained on glass slides for examination.
    • Step 3 A pathologist examines the glass slides on a microscope and issues a diagnosis based on the Gleason Scoring System.

    Major Challenges 1

    Shortage of pathologists and the resultant increase in workload

    In the US, the number of active pathologists dropped by 18% from 2007 to 2017. In South Korea, only 7 graduates enrolled in pathology residency where 65 slots were available in 2020

    Major Challenges 2

    Discordance among pathologists in diagnosis

    With varying levels of talent and experience, pathologists notice different things and have different perspectives on what is important which results in inconsistency and discordance among pathologists in diagnoses.

    2 Technology

    We are a world leader in technological capability based on deep learning.


    Since its establishment, Deep Bio has committed to integrating state-of-the-art technology into clinical workflows for improved patient care.


    Our in-house medical experts and machine learning engineers combine their domain knowledge to bring the AI-driven transformation in the field of medicine.


    Deep Bio has retained its No.1 position in the Camelyon Challenge (Global image analysis competition for categorizing lymph node metastasis) since its first submission in 2019.

    3 Solutions

    Dedicated to tackling the challenges in pathology and improving diagnostic workflow, Deep Bio is developing and implementing deep learning-based cancer diagnostic support software.

    about img about img


    DeepDx® Prostate is a clinically-validated AI solution for prostate core needle biopsy tissue image analysis. Whole-slide images (WSIs) of H&E-stained biopsy tissue specimens are analyzed for prostate cancer, Gleason scores, and grade groups. Extensively tested at US CLIA labs (over 700k cores between 2019 and 2021), DeepDx® Prostate can alleviate the shortage of pathologists and the resultant increase in workload, while reducing diagnostic subjectivity and variability.

    Benefits of using DeepDx®

    Benefit 1

    Accuracy in quantifying the areas of interest in ratios

    Benefit 2

    Quality check for any potential missed areas of interest

    Benefit 3

    Consistency and reproducibility of diagnoses

    Deep Bio's deep learning-based cancer diagnostic support software minimizes the risk of human error from manual handling and subjectivity of pathologist assessment resulting in decreased turnaround time, more precise and consistent diagnostic results, and improved reproducibility. Precise classification and quantification of different morphological patterns and cells offer new insights and relationships that can help medical professionals optimize their decisions and determine the best treatment options for patients.


    We are a team dedicated to
    innovating traditional

    Sun Woo Kim

    Chief Executive Officer

    Sun Woo Kim, the founder and CEO of Deep Bio Inc., has a proven track record of over 20 years in executive management as well as computer science expertise. He founded Deep Bio based on the firm belief that AI can revolutionize healthcare and address some of the existing challenges, starting with improved diagnostic processes. Prior to founding Deep Bio, he served as the Chief Technology Officer of Pinion Industries, an automotive software and security start-up, which was acquired by Hyundai Motors in 2014. He was also the deputy director of Korea Telecommunications, the largest telecommunications company in Korea, where he led the global venture capital team.

    Grant Carlson

    Chief Commercial Officer

    Grant Carlson boasts 30 years in molecular diagnostics, anatomic pathology, and life sciences. As former Chief Commercial Officer at PathAI Diagnostics, he led US sales and marketing for one of the largest pathology laboratories in the U.S. His dynamic leadership at NeoGenomics and Dianon Systems fueled rapid growth through strategic partnerships and innovative commercialization. He is a co-inventor on 5 US patents on methods for diagnosing prostate cancer and benign disease.

    Su-Hyun Lee

    Chief Financial Officer

    Su-Hyun Lee, a seasoned financial professional and certified public accountant, boasts 17 years of diverse experience. He has played pivotal roles in IPO, M&A, and financial planning at Samil PwC’s TS-FAS and Samsung Securities IPO teams. Additionally, his expertise spans IR, M&A, and IPO preparations from MegazoneCloud’s strategic planning team. As CFO at semiconductor equipment firm HPSP, he contributed to the successful IPO.

    Tae Yeong Kwak

    Chief Technical Officer

    Tae Yeong Kwak has unmatched expertise across a span of computer programming subspecialties, including algorithm design, computer systems design, and big data analysis. Prior to joining Deep Bio, he was at Netmarble, Korea’s biggest mobile gaming company, where he directed their AI Lab and also managed big data analysis and systems operations. At Naver Corporation, the first company in Korea to launch an online platform, he led the natural language processing machine learning team.

    Yong Hyun Hwang

    Chief Architect Officer

    Yong Hyun Hwang has over 20 years of experiences working for multinational companies such as Google, Microsoft, Qualcomm, and Oracle as a software engineer and a researcher. Yong Hyun Hwang holds extensive knowledge, capability and experiences in innovating, architecting and designing new infrastructures and toolsets to improve existing workflow and developer proficiency. At Google, he led and completed a project that saves Google data center more than $150 million per year.

    Hye Yoon Chang

    Medical Officer

    Dr. Hye Yoon Chang, Deep Bio’s Medical Officer, brings more than twenty years of experience as a board-certified pathologist specializing in anatomic pathology. She holds a medical degree and a Ph.D. from Korea University, the nation’s top institution in medical research, where she also completed her residency. Hye Yoon has authored numerous papers on ground-breaking research in clinical pathology and serves as a member of the Korean Pathology Society and Korean Cytology Society.



    user img

    I can instantly check the results from DeepDx® Prostate with a simple click of a button -sometimes revealing small areas of concern that I would have missed had I not had the tool running in the background.

    user img

    In particular, it (DeepDx® Prostate) reduces inter-and intra-observer variability. In hospitals without pathology residents, using DeepDx® Prostate for screening will allow pathologists to spend more time and energy on their research

    user img

    This tool is very helpful for quality assurance in that it enables the pathologist to re-look at areas that they did not annotate originally, but that the AI algorithm did, and determine if there are additional areas of interest that require their attention