Artificial intelligence promising for CA, retinopathy diagnoses

December 12, 2017

(HealthDay)—A deep learning algorithm can detect metastases in sections of lymph nodes from women with breast cancer; and a deep learning system (DLS) has high sensitivity and specificity for identifying diabetic retinopathy, according to two studies published online Dec. 12 in the Journal of the American Medical Association.

Babak Ehteshami Bejnordi, from the Radboud University Medical Center in Nijmegen, Netherlands, and colleagues compared the performance of automated deep learning algorithms for detecting metastases in hematoxylin and eosin-stained tissue sections of of women with with pathologists' diagnoses in a diagnostic setting. The researchers found that the area under the receiver operating characteristic curve (AUC) ranged from 0.556 to 0.994 for the algorithms. The lesion-level, true-positive fraction achieved for the top-performing algorithm was comparable to that of the pathologist without a time constraint at a mean of 0.0125 false-positives per normal whole-slide image.

Daniel Shu Wei Ting, M.D., Ph.D., from the Singapore National Eye Center, and colleagues assessed the performance of a DLS for detecting referable diabetic retinopathy and related eye diseases using 494,661 retinal images. The researchers found that the AUC of the DLS for referable diabetic retinopathy was 0.936, and sensitivity and specificity were 90.5 and 91.6 percent, respectively. For vision-threatening diabetic retinopathy, the AUC was 0.958, and sensitivity and specificity were 100 and 91.1 percent, respectively.

"In this evaluation of retinal images from multiethnic cohorts of patients with diabetes, the DLS had and specificity for identifying and related eye diseases," Ting and colleagues write.

Several authors from the Bejnordi study disclosed financial ties to the pharmaceutical and medical device industries. Several authors from the Ting study hold patents related to the system used in the study.

Abstract/Full Text -
Ting (subscription or payment may be required)

Explore further: Study examines use of deep machine learning for detection of diabetic retinopathy

More information: Abstract/Full Text - Benjordi (subscription or payment may be required)
Editorial (subscription or payment may be required)

Related Stories

Study examines use of deep machine learning for detection of diabetic retinopathy

November 29, 2016
In an evaluation of retinal photographs from adults with diabetes, an algorithm based on deep machine learning had high sensitivity and specificity for detecting referable diabetic retinopathy, according to a study published ...

Will 'AI' be part of your health-care team?

December 12, 2017
(HealthDay)—Artificial intelligence is assuming a greater role in many walks of life, with research suggesting it may even help doctors diagnose disease.

New screening tool can identify diabetic retinopathy

October 16, 2017
(HealthDay)—A new screening tool can adequately detect risk of diabetic retinopathy in adults with diabetes in low-income communities in Mexico, according to a study published in the October issue of Preventing Chronic ...

UWF retinal imaging process could reduce practice burden

June 5, 2015
(HealthDay)—Real-time ultrawide field (UWF) retinal image evaluation by nonphysician imagers can accurately detect diabetic retinopathy (DR) and help reduce center image grading burden, according to a study published online ...

Researchers use deep learning to create an algorithm to detect a common diabetic eye disease

April 28, 2017
Researchers from the Byers Eye Institute at Stanford University have found a way to use artificial intelligence to fight a complication of diabetes that affects the eyes. This advance has the potential to reduce the worldwide ...

Risk of falls up with mild, moderate diabetic retinopathy

November 19, 2017
(HealthDay)—Among Asians, individuals with mild and moderate diabetic retinopathy (DR) are more likely to have fallen, and greater perceived barriers to diabetes self-management (DSM) are associated with the severity of ...

Recommended for you

An orange a day keeps macular degeneration away: 15-year study

July 12, 2018
A new study has shown that people who regularly eat oranges are less likely to develop macular degeneration than people who do not eat oranges.

Injectable electronics offer powerful new tool in understanding how retinal cells work

June 28, 2018
Charles Lieber and his group are rewriting the rules of how scientists study retinal cells, and they're doing it with a single injection.

Why the eye could be the window to brain degeneration such as Alzheimer's disease

June 26, 2018
Researchers from Queen's University Belfast have shown for the first time that the eye could be a surrogate for brain degeneration like Alzheimer's disease (AD).

Microglia protect sensory cells needed for vision after retinal detachment

June 18, 2018
A research team at Massachusetts Eye and Ear has shown that microglia, the primary immune cells of the brain and retina, play a protective role in response to retinal detachment. Retinal detachment and subsequent degeneration ...

161 genetic factors for myopia identified

June 15, 2018
The international Consortium for Refractive Error and Myopia (CREAM) recently published the largest-ever genetic study of myopia in Nature Genetics. Researchers from the Gutenberg Health Study at the Medical Center of Johannes ...

Normal eye dominance is not necessary for restoring visual acuity in amblyopia

June 7, 2018
Amblyopia, commonly known as "lazy eye," is a visual disorder common in children. The symptoms often are low acuity in the affected or "lazy" eye and impaired depth perception. Researchers have long believed that the impaired ...

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.