Medical AI company
Deep Bio
Seoul-based developer of DeepDx AI software for digital pathology analysis of prostate and breast specimens.
Company overview
Deep Bio develops AI diagnostic support software for digital pathology. Its DeepDx Prostate products analyse H&E-stained prostate specimens (core needle biopsy, radical prostatectomy and TURP) to detect and grade areas of interest, and DeepDx Breast products cover resection and sentinel lymph node biopsy specimens. It also offers the DeepDx Viewer.
- Headquarters
- Seoul, South Korea
- Company type
- AI Technology Developer
In its own words: “DeepDx® Prostate is a clinically validated and CE-marked AI diagnostic support software for prostate cancer.” source
AI products and platforms
- DeepDx ProstateAI-powered
AI analysis of digitized H&E prostate slides to detect and localize areas of interest by Gleason pattern
Product page ↗ - DeepDx BreastAI-powered
AI analysis of breast resection and sentinel lymph node biopsy slides
Product page ↗
Technology categories
Clinical applications
- prostate biopsy review
- lymph node metastasis detection
Regulatory information
- DeepDx Prostate approved by Korea MFDS and CE marked source
As stated by the company or the cited regulator page. Authorisation is specific to a product, version and market; confirm the current status with the company and the regulator. About medical device regulation
Official sources
Last verified 29 October 2026 against the sources above.
Questions about Deep Bio
Does Medical AI have to explain how it reaches its outputs?
Not always in a technical sense, but transparency about the product is increasingly expected. Many machine learning models cannot give a simple step-by-step reason for each output, so regulators focus on clear information for users: intended use, inputs, how the model was developed and tested, performance, and known limitations.
In the US, one of the criteria for clinical decision support to fall outside device regulation is that a healthcare professional can independently review the basis for its recommendations. FDA has also published transparency principles for machine learning devices with Health Canada and MHRA.
For buyers, a vendor's ability to document how its model works and where it fails is often more useful than heat maps or confidence scores alone.
What are whole-slide images in digital pathology?
A whole-slide image (WSI) is a high-resolution digital scan of an entire glass pathology slide, which can be viewed and navigated on screen at different magnifications, much like a microscope.
WSIs are very large files, often gigabytes per slide, so digital pathology needs fast scanners, substantial storage, network capacity and viewing software. They are the input for pathology AI.
FDA describes a whole slide imaging system as an automated digital slide creation, viewing and management system intended as an aid to the pathologist to review and interpret digital images of surgical pathology slides. Formats vary between scanner vendors, and DICOM has been extended to support whole-slide imaging, which helps interoperability between scanners, archives and AI tools.
What is automation bias, and why does it matter for clinical AI?
Automation bias is the tendency of people to over-rely on a suggestion from an automated system, either following an incorrect output or missing something because the system did not flag it.
FDA's Clinical Decision Support Software guidance (issued January 2026) discusses automation bias and notes it increases in urgent situations where there is not enough time to consider other information. This is one reason FDA does not consider software intended for critical, time-sensitive decisions to meet the criteria for non-device CDS.
Organizations reduce automation bias through user training, clear display of the basis and limits of an output, workflows that keep independent clinical review, and monitoring of how the tool is actually used.