AI joins the hunt in India as dogs sniff cancer with 3D-printed gear
A Bengaluru-based startup is training dogs like Chloe with AI-assisted gear to detect cancer. The project involves 15 dogs and has drawn interest from global researchers.
Kulgod, a Bengaluru-based startup, is using AI to train dogs like Chloe to detect cancer through their sense of smell. The dogs are fitted with 3D-printed helmets and harnesses equipped with sensors to collect data during training sessions. This initiative aims to develop a non-invasive method for early cancer detection, leveraging the dogs' natural ability to identify scent markers associated with the disease.
The project is part of a broader global effort to explore the potential of canine olfactory capabilities in medical diagnostics. Research suggests that dogs can be trained to detect various illnesses, including cancer, Parkinson's, and even Covid-19. Kulgod's approach combines this biological talent with AI to enhance accuracy and scalability in detection efforts.
According to a key figure in the project, 'In an hour, they can do thousands of sniffs,' highlighting the efficiency of the dogs in collecting scent data. Kulgod's team has trained 15 dogs, including Chloe, a Labrador mix, who wears a customised data-gathering helmet. This technology captures detailed information that could be used to identify cancer-related compounds in human breath.
India's regulatory environment and growing interest in AI-driven healthcare solutions have positioned the country as a key player in this emerging field. The startup has attracted attention from local and international researchers, with potential applications in early cancer screening across the nation. Regulatory bodies like TRAI are closely monitoring developments in AI-assisted medical technologies, ensuring compliance and safety standards are met.
While the project is still in its early stages, the potential impact on cancer detection methods is significant. If successful, this approach could offer a cost-effective and non-invasive alternative to traditional diagnostic tools. The startup plans to expand its efforts in the coming years, with ongoing research and development aimed at refining the technology and exploring new applications in medical diagnostics.