Kyocera co-developing AI to diagnose skin diseases via smartphone pics

skin diseases smartphone
Image credit: Gordana Sermek /

Kyocera announced that its subsidiary, Kyocera Communication Systems (KCCS) has started joint research with the University of Tsukuba to develop an artificial intelligence (AI) system capable of detecting melanoma and other skin diseases by analyzing digital images of a patient’s skin.

In Japan, the number of skin cancer patients approximately doubled from 1999 through 2014, according to Japan’s Ministry of Health, Labour and Welfare Because skin cancer treatment outcomes are substantially improved by early diagnosis, better diagnostic technologies are in great demand.

Recent developments in AI, image recognition, and IT infrastructure are facilitating great advances in the ability to analyze digital images. In the medical field, where digital imaging is already an essential diagnostic tool, AI-based image recognition offers the potential to diagnose skin diseases from digital images, which KCCS says will offer great advantages over conventional practices, which now often depend on the knowledge and experience of a physician.

In addition to helping dermatology specialists, AI-based image recognition could allow accurate diagnoses in rural and remote areas lacking a local clinician, using pictures from smartphones or digital cameras to greatly improve healthcare outcomes.

KCCS is now working with Professor Manabu Fujimoto and Assistant Professor Yasuhiro Fujisawa (both of the Department of Dermatology, Faculty of Medicine, University of Tsukuba) to develop an image-recognition system accurate enough to distinguish several types of skin malignancies, including melanoma. The next phase of their project will aim for image-based diagnostic support of any skin disease.

kyocera AI skin diseases
Image credit: Kyocera

The project utilizes a database of more than 20,000 clinical images accumulated over 20 years by the University of Tsukuba Hospital’s Department of Dermatology. KCCS will bring AI-based image-processing expertise accumulated through Labellio, a cloud-based web service that allows any user to create a simple “drag-and-drop” image classifier powered by deep learning.

KCCS and the University of Tsukuba will conduct joint research from March 2017 through March 2018, aiming toward a commercial application in the fiscal year ending March 2020.

Furthermore, they plan to develop a system capable of identifying more than 2,000 different skin diseases from digital images by combining their respective resources and expertise in the future.

EDITED TO ADD [8/31]: An earlier version of this press release said the project utilizes a database of more than 200 clinical images accumulated over 20 years by the University of Tsukuba Hospital’s Department of Dermatology. Kyocera has corrected that figure – it’s actually “more than 20,000”.

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