Gaming Chips To Save Lives: Hospitals To Be Rebooted Soon

Research activities in utilizing deep learning to automate the process of disease identification in medical images are gaining momentum. Nvidia announced Project Clara, which consists of powerful chips containing software for performing various medical tasks.

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Gaming Chips To Save Lives Hospitals To Be Rebooted Soon
Life-Saving Gaming Chips: Hospitals Would Increase Mortality Rate With AI Chips

Artificial intelligence (AI) has brought revolution in almost every sector. Lawyers have been afraid that AI may eat up their jobs in the future. Workers in the automobile sector are also worried that emergence of AI may put them out of the job. However, the tech sector is reaping as many benefits as it can by developing new technologies and bringing up new solutions. The autonomous driving cars will be on roads in next few years despite recent shocking incidents resulting in deaths of people. There is no doubt that AI is the future. It is ready to become an essential part of the medical and healthcare sector. The leading gaming hardware manufacturer Nvidia has recognized this and progressed toward the development of chips for AI algorithms. It has been developing a hardware that can be used for training and run the deep learning algorithms.

Jensen Huang, CEO of Nvidia, outlined that the company is providing graphics processors which offer right kind of parallel processing to enable AI algorithms to run smoothly. The chief of the gaming hardware manufacturer also recognized that AI algorithms would revolutionize medical and healthcare sector. Doctors, hospitals, and medical researchers would be new customers of Nvidia. Huang told MIT Technology Review, “The amount of data that health care has is enormous, and it’s the perfect example of unstructured data. And yet the computational use of that data is fairly limited. One area that is a perfect first entry is medical imaging.”

Research activities in utilizing deep learning to automate the process of disease identification in medical images are gaining momentum. Researchers from Stanford University have shown that this technique can be used for detection of skin cancer from images. On the other hand, researchers at Google have used this technique for identification of anomalies in chest x-rays.

Nvidia has been working with medical companies that produce imaging instruments. These companies have been asking systems with computational analysis. The existing systems can be connected to these systems and images are analyzed. In the future, the existing systems will become supercomputers in the same way cloud computing has done for cell phones. The gaming chip manufacturer announced Project Clara, which consists of powerful chips containing software for performing tasks such as sharpening MRI images and create a visualization of ultrasound data. This system would help in identifying signs of disease in a medical image.

John Guttag, a professor of computer science at MIT, outlined that the medical imaging sector will be transformed with machine learning and deep learning. There will be a dramatic change of scenario. With the help of AI algorithms, doctors and medical professionals will be able to learn things that are not possible with the naked eye.

Atul Butte, a professor at the UCSF School of Medicine and an expert on utilization of technology in the healthcare sector, outlined that hospitals will begin to invest enormously in the hardware required to run AI algorithms. He said, “There are faculty at UCSF and elsewhere that are already using Nvidia boards and equipment to train deep-learning models on medical images, including mammography, ultrasounds, and more.”

According to the current scenario, things are moving slowly for the adoption of AI diagnosis in the hospitals and medical laboratories. Many companies are moving toward making advancements in the field of medical research through AI technology. AI algorithms would help doctors in analyzing more data that it was possible before. It will be interesting to see how the medical field will accept AI in the future.

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