Mandi, Nov 27 (IANS) Researchers at the Indian Institute of Technology, Mandi, have developed an artificial intelligence-powered point-of-care device to screen with high accuracy cervical cancer cases by analysing microscopy images.
The project has been taken up in collaboration with Aindra Systems, Bengaluru.
The research team comprised Anil Sao and Arnav Bhavsar, Associate Professors, School of Computing and Electrical Engineering, and Srishti Gautam and Krati Gupta.
The team, along with the industry collaborators, has developed AI-based algorithms that enables the device to undertake automatic screening for cervical cancer, according to a statement by the IIT-Mandi.
Cervical cancer is among the deadliest forms of cancer, and early detection and treatment are vital for the patient.
The gold standard in screening for cervical cancer is the Pap Smear test, in which cells extracted from the cervix are examined by specialists using a microscope.
While the Pap smear test undoubtedly helps in early detection, it involves subjective analysis and is associated with risks of false diagnoses. According to studies, Pap Smear test's accuracy is 60-85 per cent.
“The difference between a conventional system and Aindra's point-of-care system is that the latter is portable and can be taken to the potential patients. In the conventional system, the people have to visit the pathology laboratory to get themselves screened,” Bhavsar said.
Adarsh Natrajan, Harinarayanan and Nirmal Jith from Aindra Systems collaborated on the device's design and development.
They have applied for international patent for the device and algorithm in 2016 and the research has been published in many international journals.
The prototype of device is undergoing clinical trial at Kidwai Memorial Hospital, Bengaluru; Manipal Hospital, Karnataka; and Raja Rajeswari Medical College and Hospital, Bengaluru.
The accuracy of the prototypes has been around 88 per cent.
The IIT-Mandi team analysed Pap Smear images provided by Aindra and characterised them into ‘normal' and ‘potentially cancerous' cases. They developed a computer program that could differentiate between the two.