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Pratik Shah's Talk on AI Looks to Its Beneficial Uses in Diagnosis
Kalin Ned — August 1, 2018 — Keynote Trends
References: media.mit.edu & ted
Medical technologist Pratik Shah delivers a concise and direct talk on AI that informs the audience of how technology revolutionizes healthcare. The keynote communicates an optimistic forecast for the future of AI-based diagnosis.
The main challenge for the industry is identifying life-threatening illnesses — a category which includes cancer, autoimmune and infectious diseases. Since artificial intelligence exhibits high accuracy on a massive scale, it is sufficient to believe that computer-enhanced diagnostic methods can help the early detection of these often deadly health anomalies. Pratih Shah, who works with a team at the MIT Media Lab, is currently developing a high-tech method that will ultimately simplify the traditional diagnostic process — one that is expensive, extensive and resource-intensive. The main objective of the project is to evolve AI to a point where it is more scalable and effective.
The talk on AI reveals MIT's successful pursuits in prototyping a variety of unorthodox AI architectures that address the issues of diagnosis. For one, the technicians were able to convert a singular image into billions of data points that train the artificial intelligence algorithm. Secondly, the professionals created a composite image by layering a standard white light photograph on top with the hopes of reducing the expenses of medical imaging technologies. Pratih Shah and his team determined that they needed about 50 of these composite images to create a highly efficient AI algorithm.
The main challenge for the industry is identifying life-threatening illnesses — a category which includes cancer, autoimmune and infectious diseases. Since artificial intelligence exhibits high accuracy on a massive scale, it is sufficient to believe that computer-enhanced diagnostic methods can help the early detection of these often deadly health anomalies. Pratih Shah, who works with a team at the MIT Media Lab, is currently developing a high-tech method that will ultimately simplify the traditional diagnostic process — one that is expensive, extensive and resource-intensive. The main objective of the project is to evolve AI to a point where it is more scalable and effective.
The talk on AI reveals MIT's successful pursuits in prototyping a variety of unorthodox AI architectures that address the issues of diagnosis. For one, the technicians were able to convert a singular image into billions of data points that train the artificial intelligence algorithm. Secondly, the professionals created a composite image by layering a standard white light photograph on top with the hopes of reducing the expenses of medical imaging technologies. Pratih Shah and his team determined that they needed about 50 of these composite images to create a highly efficient AI algorithm.
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