IIT-Delhi develops AI-based system to detect malaria, TB, CANCER

IIT-Delhi develops AI-based system to detect malaria

IIT-Delhi develops AI-based system to detect malaria- New Delhi: Researchers at the Indian Institute of Technology  (IIT), Delhi have developed artificial intelligence (AI) based low-power electronic hardware systems that can help detect malaria, Tuberculosis, intestinal parasites, and cervical cancers. Research is focused on creating a neuromorphic system that can be used to reach healthcare in resources-Critical areas with limited access to human- specialists.

“while many software AI mode exist for health and diagnostic related applications, the need of the hour is to efficiently map these models portable dedicated low-power, low-cost hardware, all in low-resource environments. To enable the accessible AGE-AI system. “ professor Manan Suri, Department of Electrical Engineering, IIT Delhi Said.

IIT-Delhi develops AI-based system to detect malaria, TB, CERVICAL CANCER

Suri, who is leading the team of researchers, said that microscopy is Particularly suited to low- resources, high disease load areas; both are simple and versatile; also for Clinical work. However, New Technologies are available for Diagnosis, the cost of special equipment can be impractical at such places, he said.

“Contrary to choices such as fast clinical trials, however, a microscopy-based diagnosis depends on the availability of skilled technicians, one of which is a significant reduction. As a result, clinical signs are often diagnosed on the basis. The symptom alone, which is prone to error and leads to the financial burden of buying higher mortality, drug resistance, and unnecessary medicines, “said Professor.

“Therefore, there are alternatives that can help provide access to quality diagnostics that are currently unavailable,” he said. For the latest updates, you can visit www.indiatimelines.com.

Professor Manan Suri, Department of Electrical Engineering, IIT-Delhi, said: “While many software AI models are present for health and diagnostic applications, the need for hours to efficiently reduce these models to portable low-power To mapped – Cost hardware to enable quick access to everyone in low-resource environments. ”

Professor Suri, the long-term impact and goal of this work, has to enable future deployment of the platform in rural areas for better acreage for high-level clinical health care.


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