How is Google AI (Artificial Intelligence) transforming Healthcare?

How is Google AI (Artificial Intelligence) transforming Healthcare?

How is Google AI (Artificial Intelligence) transforming Healthcare?

by Gorilla Jobs in Facts & Figures 23/05/2018

How is Google AI (Artificial Intelligence) transforming Healthcare?

Artificial Intelligence or (AI) is poised to transform medicine, delivering new, assistive technologies that will empower doctors to better serve their patients.

Machine learning has dozens of possible application areas, but healthcare stands out as a remarkable opportunity to benefit people — and Google is working closely with clinicians and medical providers, they are developing tools that they hope will dramatically improve the availability and accuracy of medical services.

Deep learning has already revolutionized the field of computer vision, making practical, in-your-pocket technologies out of what seemed like science fiction just a few years ago.

If these new computer vision systems can reach human-level accuracy in identifying dog breeds or cars, might those same systems be capable of learning to identify disease in medical images?

Over the last few years, Google has been working with doctors and clinicians to explore this question, and their research has shown that this is indeed possible — and not just in some far off future, but today.

Two of the areas Google is the most excited about and where they have made the most progress in research to date are ophthalmology and digital pathology.

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Google AI

Diagnosing Diabetic Eye Disease

In the area of ophthalmology, Google began exploring computer-aided diagnostic screening for a disease of the eye called diabetic retinopathy.

Diabetic retinopathy is the fastest-growing cause of preventable blindness globally. The condition is normally diagnosed by a highly trained doctor examining a retinal scan of the eye. If caught early, effective treatments are available, but if undetected, the disease progresses into irreversible blindness, and in much of the world, there simply are not enough doctors available to support the volume of screening required to protect the population.

Google has been collaborating closely with doctors and international healthcare systems, they developed a state-of-the-art computer vision system for reading retinal fundus images for diabetic retinopathy and determined their algorithm’s performance is on par with U.S. board-certified ophthalmologists.

Google has recently published some of their research in the Journal of the American Medical Association and summarized the highlights in a blog post.

It’s early days, and Google has still a lot of work to do to bring the benefits of this research to patients, but ultimately, Google hopes to help real doctors and clinics expand global screening capacity to cover all at-risk individuals in the world.

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Detection of Diabetic Eye Disease

Figure 1. Examples of retinal fundus photographs that are taken to screen for DR. The image on the left is of a healthy retina (A), whereas the image on the right is a retina with referable diabetic retinopathy (B) due a number of hemorrhages (red spots) present. Picture Credits: https://ai.googleblog.com/2016/11/deep-learning-for-detection-of-diabetic.html

Assisting Pathologists in Detecting Cancer

In the field of digital pathology, Google has focused their initial research on algorithms that might assist pathologists in detecting breast cancer in lymph node biopsies.

Reviewing pathology slides is a complex task that requires years of training, expertise, and experience. Even with this extensive training, there can be substantial variability in the diagnoses given by different pathologists for the same patient — which isn’t surprising given the massive amount of information that pathologists must review in order to make an accurate diagnosis.

To address these issues of limited time and diagnostic variability, Google built an automated detection algorithm that can naturally complement pathologists’ workflow. Their algorithm was designed to be highly sensitive to make it easier for pathologists to find even small instances of breast cancer metastasis in lymph node biopsies. You can learn more about their findings in this paper and blog post.

Google was encouraged by these results, but they think they’re just the beginning. There’s a significant opportunity for AI to improve the accuracy and availability of healthcare, and Google hopes that their research will serve as one of many demonstrations of that potential.

As part of this ongoing exploration, Google has also been partnering with healthcare providers to see how machine learning might predict healthcare events. You can read more about our research collaborations in this blog post.

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Pathologist

Source: https://ai.google/research/teams/brain/healthcare-biosciences

Summary:

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