Artificial Intelligence Technology To Analyze Kidney Disease

by Julia Samuel on  January 12, 2018 at 12:41 PM Research News
RSS Email Print This Page Comment bookmark
Font : A-A+

Using a computer model based on artificial intelligence (AI) the ability to quantify the extent of kidney damage and predict the life remaining in the kidney, now is possible.
Artificial Intelligence Technology To Analyze Kidney Disease
Artificial Intelligence Technology To Analyze Kidney Disease

Nephropathology is a specialization that analyzes kidney biopsy images. While large clinical centers in the U.S. might greatly benefit from having 'in-house' nephropathologists, this is not the case in most parts of the country or around the world.

Show Full Article


According to the research team, the application of machine learning frameworks, such as convolutional neural networks (CNN) for object recognition tasks, is proving to be valuable for classification of diseases as well as reliable for the analysis of radiology images including malignancies.

To test the feasibility of applying this technology to the analysis of routinely obtained kidney biopsies, the research team performed a proof of principle study on kidney biopsy sections with various amounts of kidney fibrosis (also commonly known as scarring of tissue). The machine learning framework based on CNN relied on the pixel density of digitized images, while the severity of disease was determined by several clinical laboratory measures and renal survival.

CNN model performance then was compared with that of the models generated using the amount of fibrosis reported by a nephropathologist as the sole input and corresponding lab measures and renal survival as the outputs. For all scenarios, CNN models outperformed the other models.

"While the trained eyes of expert pathologists are able to gauge the severity of disease and detect nuances of kidney damage with remarkable accuracy, such expertise is not available in all locations, especially at a global level. Moreover, there is an urgent need to standardize the quantification of kidney disease severity such that the efficacy of therapies established in clinical trials can be applied to treat patients with equally severe disease in routine practice," explained corresponding author Vijaya B. Kolachalama, PhD, assistant professor of medicine at Boston University School of Medicine.

"When implemented in the clinical setting, our work will allow pathologists to see things early and obtain insights that were not previously available," said Kolachalama.

The research team believes their model has both diagnostic and prognostic applications and may lead to the development of a software application for diagnosing kidney disease and predicting kidney survival.

"If healthcare providers around the world can have the ability to classify kidney biopsy images with the accuracy of a nephropathologist right at the point-of-care, then this can significantly impact renal practice. In essence, our model has the potential to act as a surrogate nephropathologist, especially in resource-limited settings," said Kolachalama.

Source: Eurekalert

Post a Comment

Comments should be on the topic and should not be abusive. The editorial team reserves the right to review and moderate the comments posted on the site.
Notify me when reply is posted
I agree to the terms and conditions

Recommended Reading

News A - Z

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

News Search

Premium Membership Benefits

Medindia Newsletters

Subscribe to our Free Newsletters!

Terms & Conditions and Privacy Policy.

Stay Connected

  • Available on the Android Market
  • Available on the App Store

News Category

News Archive