Medical AI company
AI Medical Service
Tokyo-based developer of endoscopy AI that supports detection of gastric and other GI cancers during endoscopic examinations.
Company overview
AI Medical Service Inc. develops AI software that supports diagnostic imaging in gastrointestinal endoscopy, with a focus on early detection of gastric cancer. Its endoscopic image diagnosis support software gastroAI model-G3 has received manufacturing and marketing approval in Japan. The company is headquartered in Toshima-ku, Tokyo, and established a US branch in New York in 2023.
- Headquarters
- Tokyo, Japan
- Founded
- 2017 source
- Company type
- AI Technology Developer, Research or Emerging Startup
- Status
- Startup
In its own words: “AI Medical Service, Inc. is a medical AI startup that develops image diagnosis support AI (artificial intelligence) such as "Gastric Cancer Differentiation AI" under the mission of "saving patients around the world - to zero missed cancer cases with endoscopy AI".” source
AI products and platforms
- gastroAI model-G3AI-powered
Endoscopic image diagnosis support software for gastric cancer
Product page ↗
Technology categories
Clinical applications
- upper GI endoscopy
Markets served
- Japan
- Thailand
Regulatory information
- Manufacturing and marketing approval in Japan for endoscopic image diagnosis support software gastroAI model-G3 source
- Regulatory approval from Thailand FDA for its gastric AI-based endoscopic diagnosis support system 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 AI Medical Service
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 is AI image reconstruction and denoising?
AI image reconstruction and denoising use deep learning to produce clearer images from raw scanner data or to reduce noise and artifacts, for example in CT or MRI. Vendors often position these tools as supporting lower-dose or faster scanning protocols.
Unlike detection software, these tools change the image the clinician reads rather than adding a finding. Questions to ask include:
- Is the function built into the scanner or a separate software product?
- Which scanners, protocols and body regions is it authorized for?
- How was diagnostic image quality evaluated, and could fine detail be lost or altered?
These functions are typically regulated as part of the imaging device or as image processing software, depending on the product and market.
What is AI-powered medical image analysis?
AI-powered medical image analysis uses machine learning, often deep learning, to process images and return outputs such as detected regions, segmentations, measurements, quantitative scores or classifications.
It is used beyond radiology, including in cardiology (echocardiography), pathology (whole-slide images), dentistry (intraoral and panoramic radiographs), ophthalmology (retinal photographs and OCT) and dermatology. Outputs may be shown as overlays, structured results or notifications.
Because the software analyzes medical images, in the US it does not meet the criteria for non-device clinical decision support, and image analysis with a medical purpose is commonly regulated as a device. The Medical Imaging AI category in the Medical AI directory covers these companies.