135262600-the-concept-of-the-use-of-artificial-intelligence-in-medicine-the-doctor-clicks-

A.I DOCTOR

Convergence Research Consortium: University-Enterprise-Hospital Joint Study to Obtain Medical Clinical Experiments and Data for Machine Learning of Virtual Company Platforms, and Proceed with Commercialization Research. Development of medical diagnosis platform using artificial intelligence technology.

 
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LAB-ON-A-DISK

Amongst numerous microfluidic technologies available, this study proposes the design of a centrifugal microfluidic chip, also known as Lab-on-a-Disc (LOD), which is regarded as one of the most outstanding platforms in microfluidics. Typical centrifugal micro-devices perform a set of microfluidic operations, such as liquid transport, metering, aliquoting, mixing, and valving through rotational-speed control. Accordingly, such devices have the advantage of being able to control the fluid through use of a single motor to generate the force required for fluid propulsion thereby eliminating the need for an external pump and multiple laboratory instruments. Since fluid control is exclusively regulated by the centrifugal force, the overall process becomes simpler and faster. Implementation of the analytical protocol is based on the use of both capillary and vinyl valves. Through use of the proposed design, the authors expect to prevent leakage and exercise control over liquid flow with regard to centrifugal microfluidics.

 
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DEEP LEARNING APPLICATIONS

GAN(Generative Adversarial Network)

A generative adversarial network, or GAN, is a deep neural network framework which is able to learn from a set of training data and generate new data with the same characteristics as the training data. Generative adversarial networks consist of two neural networks, the generator and the discriminator, which compete against each other.

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DEEP LEARNING APPLICATION

Semantic segmenation

Semantic image segmentation is the task of classifying each pixel in an image from a predefined set of classes. In the following example, different entities are classified. In order to perform semantic segmentation, a higher level understanding of the image is required. The algorithm should figure out the objects present and also the pixels which correspond to the object. Semantic segmentation is one of the essential tasks for complete scene understanding.