The first step and next step of medical AI, NVIDIA's cross-border products
NVIDIA, which has been doing its own mainstream products, is currently playing the abacus of medical AI. In the face of the medical AI vent that seems to be chasing everyone, NVIDIA still has to try the cross-border that it is not good at. The purpose of the field is to catch up with the last bus of the feng shui, or to use its own technical strength to truly incite the medical field?
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Start with the field of medicine and health care
The dedicated hardware developed by chip maker NVIDIA for specific advanced learning algorithms is currently driving the advancement of artificial intelligence.
It is now locked into the next big market – medicine and health care .
Medical imaging research is developing at an alarming rate. NVIDIA has seen many suppliers in hospitals, and they are envisioning new applications in artificial intelligence.
A machine learning technique called "deep learning" is being applied to the screening of medical images and medical data.
Inspired by the workings of neurons in the brain, deep learning is also of particular use in image recognition and processing of audio files.
The graphics processor developed by NVIDIA is ideal for deep learning that requires parallel computing. It has also provided a variety of specialized hardware for deep learning for academia and industry.
This includes a powerful supercomputer DGX-1 and a system Drive PX for driverless cars.
NVIDIA's hardware is increasingly used in hospitals and medical research centers. Deep learning helps improve the reliability of diagnosis and may help developing countries with lower professional standards to significantly improve their care standards. Discovering new drugs may also be another important application area for deep learning.
Deep learning may also help doctors dig out potential application patterns from the data. For example, Nvidia collaborated with Bradley Erickson, a neuroradiologist at the Mayo Clinic, to use deep learning to study brain images.
For the advancement of artificial intelligence in the field of cancer, top-of-the-line artificial intelligence applications may be the most significant breakthrough in NVIDIA's medical field.
However, there are many challenges to applying techniques similar to deep learning to the medical field. The deep learning method is too complicated. Most of the time, the prediction results are difficult for experts to explain, and this is the focus of current research.
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Vigorously promote the field of artificial intelligence assisted radiology
Recently, the international data company IDC and Nvidia are working together to promote the development of artificial intelligence-assisted radiology.
In hospitals where AI has been deployed, the role of AI is to improve work efficiency, to screen, to support primary care, to support the diagnosis and treatment of incurable diseases, and to prevent disease. In general, two aspects, one is to improve efficiency, and the other is to improve the level of diagnosis and treatment.
Nvidia believes that the addition of artificial intelligence will help NVIDIA improve the quality of image analysis and medical health. At the same time, Nvidia believes that the help of artificial intelligence will improve the accessibility of medical services, and reduce the cost of medical care, benefiting the health of the wider people.
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