News

Deep learning model detects diabetic eye diseases accurately

Finnish AI researchers have developed a deep learning system that may help detecting diabetic eye diseases, which could make doctors’ work easier and reduce healthcare costs
Syväoppimismenetelmä auttaa tunnistamaan diabeteksen aiheuttamia silmäsairauksia.

A new deep-learning trained tool can detect how serious two diabetic eye diseases are by looking at photographs of the inside of a patient’s eye. The research findings, published in Nature Scientific Reports show the tool can accurately guess the severity of diabetic retinopathy, and macular edema. Diabetic retinopathy is one of the most common symptoms of diabetes that can lead to severe vision loss if left untreated. Macular edema refers to swelling under a specific part of the retina caused by diabetic retinopathy.

The deep learning model identified referable diabetic retinopathy comparably or better than presented in previous studies, although only a very small data set of 29 000 images was used for its training. The model turned out to be more accurate in identifying diseases when the training images of back of the patients’ eyes were of high quality and resolution.

“The deep learning model could process the images automatically, and thereby either support the work of the medical doctors or identify the diseases more independently”, says researcher Jaakko Sahlsten.

Results suggest that such deep learning system could increase the cost-effectiveness of screening and diagnosis and that the system could be applied to clinical examinations requiring finer grading.

”Currently, doctors use classification systems and their personal experience to decide if a patient needs a referral to a specialist when analyzing the images of their patient’s eyes. This process has strict guidelines in the terms of accuracy, at least in Finland and in the UK, which the model is able to surpass with a high margin” says researcher Joel Jaskari.

Currently, retinal imaging is the most widely used method for screening and detecting retinopathy, and medical experts evaluate the severity and the degree of retinopathy in people with diabetes based on images of the patient’s eyes.

Diabetes is a globally prevalent disease and the number of patients with diabetes is rapidly increasing.  As the number of patients increases, so too will the number of retinal images which need analysis. It is hoped that an automated system that would either assist medical experts or work as a full diagnostic tool could alleviate the situation.

“The high quality image archives of the Finnish healthcare system have enabled this work and encourages us to study the applicability of artificial intelligence-based approaches to diabetes-related and non-diabetic diseases and complications”, says Professor Kimmo Kaski.

The research group consisted of researchers from Aalto University Department of Computer Science, Finnish Center for Artificial Intelligence FCAI and medical doctors from Digifundus Ltd – a Finnish provider of diabetic retinopathy screening and monitoring services –, and Central Finland Central Hospital.

Link to the research article: https://doi.org/10.1038/s41598-019-47181-w 

  • Published:
  • Updated:
Share
URL copied!

Read more news

A green laser light shining on a sample stage between two magnets
Press releases, Research & Art Published:

New nanoscale device for spin technology

Spin waves could unlock the next generation of computer technology, a new component allows physicists to control them
Apulaisprof. Emma-Riikka Myllymäki
Research & Art Published:

Emma-Riikka Myllymäki: Why company reporting needs to be excellent

By producing high-quality reports on both their business and sustainability impacts, companies build trust and aid stakeholder decision-making.
SSD21 banner
Research & Art Published:

Our un­will­ing­ness to sac­ri­fice com­fort: 3 ta­boos pre­vent­ing sustainable trans­form­a­tion

Why is it so difficult for us to change our current practices for more sustainable ones? Are there any explicit taboos that hinder decision-making? Sustainability Science Days, Finland’s largest event in sustainability science, addresses sustainability challenges, including both taboos and innovative ways of promoting sustainability.
Kerrostalo ja kallioita
Cooperation, Press releases, Research & Art Published:

The SUBURBAN PRIDE project examines the relationship between mental images of suburbs and the built environment

The multidisciplinary project combines history of architecture, sociology, and research in critical cultural heritage and landscape architecture. The purpose of the project, based on research and workshops, is to build a sustainable future for suburbs.