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IIT Delhi scientists develop AI-based system to detect malaria, TB, cervical cancer
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  • IIT Delhi scientists develop AI-based system to detect malaria, TB, cervical cancer

IIT Delhi scientists develop AI-based system to detect malaria, TB, cervical cancer

Press Trust of India • March 27, 2019, 09:31:52 IST
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The microscopy tool is particularly suited to diagnose conditions in low-resource, disease burdened areas.

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IIT Delhi scientists develop AI-based system to detect malaria, TB, cervical cancer

Researchers at the Indian Institute of Technology (IIT) have developed artificial intelligence (AI)-based low-power electronic hardware systems that can help detect malaria, tuberculosis, intestinal parasite and cervical cancer in mere milliseconds. The research focuses on building a neuromorphic system which can be used for healthcare access in resource-constrained areas with limited access to human specialists. “While many software AI models exist for healthcare and diagnostic related applications, the 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,” said Professor Manan Suri, Department of Electrical Engineering, IIT Delhi. [caption id=“attachment_6223461” align=“alignnone” width=“1280”]Representational image. Representational image.[/caption] Suri, who is leading the team of researchers, said microscopy is particularly well adapted to low-resource, high disease burden areas, being both simple and versatile; even for diagnostic tasks. While newer technologies are available for diagnosis, the cost of specialised equipment may render it impractical in such places, he said. “In contrast to alternatives such as rapid diagnostic tests, however, a 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,” the professor said. “There is, therefore, need for alternatives which can help in providing the access to quality diagnosis that is currently routinely unavailable,” he added.

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Health Healthcare artificial intelligence malaria Tuberculosis cervical cancer AI TB Drug resistance Mobile phone based microscopy remote diagnosis SciTech Malaria Diagnosis TB Diagnosis Medical Diagnosis neuromorphic system tuberculosis diagnosis microscopy based diagnosis
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