IIT Delhi researchers design AI-based low-power electronic hardware system to detect Malaria, Tuberculosis, Intestinal Parasite, and Cervical Cancer in few milliseconds

New Delhi: Artificial Intelligence and deep learning research have enabled techniques leading to development of innovative solutions for a wide variety of applications.
In a similar landmark/crucial development, a team of IIT Delhi researchers designed and demonstrated AI-based low-power electronic hardware system that can help with detection of Malaria, Tuberculosis, Intestinal Parasite, and Cervical Cancer in few milliseconds.
IITD researchers’ work is focused on building an intelligent Neuromorphic system which can be used for healthcare access in resource-constrained areas with limited access to human specialists.
Microscopy is particularly well adapted to low-resource, high disease burden areas, being both simple and versatile; even for diagnostic tasks for which newer technologies are available the cost of specialised equipment may render it impractical in such places.
In contrast to alternatives such as rapid diagnostic tests, however, microscopy-based diagnosis does depend on the availability of skilled technicians, of which there is a critical shortage.
As a result, diagnoses are often made on the basis of clinical signs and symptoms alone, which is error-prone and leads to higher mortality, drug resistance, and the economic burden of buying unnecessary drugs. There is therefore need for alternatives, which can help in providing the access to quality diagnosis that is currently routinely unavailable.
The IITD researchers have demonstrated a proof-of-concept (PoC) low-power rapid AI hardware implementation based microscopy diagnostic support system for four different diseases: Malaria, Tuberculosis, Cervical Cancer and Intestinal Parasite Infection.
Prof. Manan Suri, Department of Electrical Engineering, IIT Delhi, said:
“While several software AI models exist for healthcare and diagnostic related applications, need of the hour is to efficiently map these models on portable dedicated low-power, low-cost hardware to enable edge-AI systems accessible to all in low resource environment”.
Malaria is a life-threatening mosquito-borne blood disease and nearly half of the world’s population is at risk of malaria. Tuberculosis (TB) is one of the top 10 causes of death worldwide. Rapid screening of TB is possible, but the service accessibility is still poor in rural areas and require specialized equipment that are not readily available.
Cervical Cancer is the fourth most common cancer in women, and seventh overall, with an estimated 528,000 new cases and 266,000 reported deaths worldwide.
Intestinal parasites infect the gastrointestinal tract of humans. They have a consistent external and internal morphology throughout the different stages of development that is egg, larva and adult stages.
The approach demonstrated by the researchers is portable, low-power and can classify with high accuracy in detection of the diseases.
The long-term impact and goal of this work will be to enable potential future deployment of the platform in rural and resource-constrained areas and improve the access to diagnostic health-care.
The research team led by Prof Manan Suri, Dept of Electrical Engineering, IITD, had presented this work at two flagship healthcare conferences i.e., IEEE BioCAS-2018 in Cleveland, USA and IEEE BioCAS-2017 in Torino, Italy.
The student researchers working on this project (Khushal Sethi, Narayani Bhatia, Vivek and Shridu Verma) were awarded two Summer Undergraduate Research Awards (SURA), by IIT Delhi, in 2017 and 2018 respectively.
The work was showcased at Rashtrapati Bhawan and also received the prestigious Gandhian Young Technology Innovation Award (GYTI) in 2018.