Microsoft developing AI tool to diagnose cervical cancer faster

Image Source : news.microsoft.com

World Health Organization (WHO) estimates that cervical cancer is the fourth most frequent cancer among women worldwide. India accounts for 16% of global cervical cancer patients and an increase in demand for cervical cancer demand has been worryingly seen.

SRL Diagnostics is the largest diagnostics laboratory in India and they receive around 100,000 pap smear samples every year. A cytopathologist in their Mumbai laboratory alone screens around 200 slides for cervical cancer every day in addition to 100 other slides for other types of cancer.

To solve the problem of the low proportion of cytopathologists available, SRL Diagnostics partnered with Microsoft to create an AI network that would have an API to enable screening out of normal slides, so that the cytopathologists could concentrate on the abnormal slides. This would give a huge boost in the overall speed of screening as only 2% of all samples turn out to be abnormal and need deeper analysis.

To develop the AI algorithm, cytopathologists studied digitally scanned versions of Whole Slide Imaging (WSI) slides manually and recorded their observations, which in turn was used as training data for the AI model. Initially only one cytopathologist was assigned by SRL Diagnostics but since each WSI consists of 1800 tile images, this task proved to be too burdensome for an individual. The matter of subjectivity was also something the AI algorithm had to adjust for.

A digitally scanned image of a WSI slide, used to train the AI model. | Source : news.microsoft.com

“Different cytopathologists examine different elements in a smear slide in a unique manner even if the overall diagnosis is the same. This is the subjectivity element in the whole process, which many a time is linked to the experience of the expert,” reveals Dr. Arnab Roy, Technical Lead New Initiatives & Knowledge Management, SRL Diagnostics

To address the burden of volume, five cytopathologists were assigned to the task across multiple labs in different locations. This lead to thousands of tile images of cervical smear being annotated. Discordant and concordant notes were created for each sample image. Each sample image with discordant notes from a minimum of three cytopathologists were then sent to senior cytopathologists. This is how the issue of subjectivity was handled.

This is the first such AI-Device-Labs setup in the Histopathology space in this part of the world and impacts the entire spectrum of stakeholders. For patients, it reduces the turnaround time for diagnosis and onset of treatment. It lends better productivity and accuracy to the efforts of cytopathologists. For doctors, it offers insights that inspire more qualitative treatment decisions. 

“With the growing burden of cancer, there is a need to quickly and accurately analyze the samples to help clinicians arrive at a diagnosis faster and with a higher degree of objectivity. The work done by the SRL-Microsoft consortium in developing deep learning-based algorithms as an assistive tool in a relatively short span of time, speaks volumes about the capabilities of both the partners. This particular cervical cancer AI API shall be useful in screening liquid-based cytology slide images, unlocking precious dead-time of the pathologists enabling them to report more cases and/or focus more on complicated cases,” adds Arindam Haldar, CEO, SRL Diagnostic.

In August this year SRL Diagnostics launched an internal preview of the API. In a span of three to six months the AI model will be put through rigorous clinical validation protocols. More than half a million anonymized digital tile images will be used in this exercise, making it one of the largest of its kind. Following internal validation, the API will be used in external cervical cancer diagnostics, including hospitals and other diagnostic centers.

This is one of the latest news about Microsoft using the power of AI to solve real world problems in India. Last week they had announced how their HAMS project was helping to automate driving tests in India. You can read about that project here.

Microsoft research AI project HAMS automates driver's license tests in India

Image Source : Microsoft News

As AI starts to increasingly pervade into every aspect of our lives, we have been hearing about more and more cases of where they are getting implemented to solve real world problems effectively. One such case is Microsoft's research AI Project named HAMS which is short for "Harnessing Automobiles for Safety". This project was initially conceived to monitor drivers and their driving with an aim to improve road safety.

“The main challenge in the traditional driver’s license test is the burden placed on the human evaluators and the resulting subjectivity that a candidate faces. Automation using HAMS technology can not only help relieve evaluators of the burden but also make the process objective and transparent for candidates,” says Venkat Padmanabhan, Deputy Managing Director, Microsoft Research India, who started the HAMS project in 2016.

HAMS utilizes the front and rear camera's of a smartphone mounted on the windscreen in conjunction with other sensors to not only monitor the vehicle's precise trajectory and the road in front but also the driver's gaze. For instance, it checks whether the driver scanned their mirrors before effecting a lane change, and even more rudimentary, whether the person taking the test is the same as the one who registered for it. The comprehensiveness of the test can be judjed by the fact that it also monitors things such as time taken, number of stoppages and number of retries while performing manoeuvres such as parallel parking.

Today, if you take the driver’s license test at the Dehradun RTO, you will be doing so in just the company of a smartphone affixed to your car’s windshield. HAMS, running on the smartphone and on an edge server onsite at the testing track, will do the rest and produce a detailed report shortly after you finish navigating through the test manoeuvres.

“The successful deployment of the HAMS-based driver license testing at the Dehradun RTO is a significant step towards the Transport Department’s goal of providing efficient, world-leading services to the citizens of Uttarakhand. We are proud to be among the pioneers of the application of AI to enhance road safety,” said Shri Shailesh Bagauli, IAS, Secretary, Government of Uttarakhand.

Here is a video of HAMS in action:

  

Although the comprehensiveness of the tests will ensure that we get better and safer driver on the roads but it a distinction has to be made between testing a driver for safety and testing a driver for skill. In the parallel parking example sighted the driver's skill is being tested. The time taken and the number of re-tries would at most cause inconvenience to others rather than hamper their safety. On the other hand strictest scrutiny must be done for things like maintaining lane, braking, lane changing, timing of using indicators, etc. as these are factors related to safety.