Artificial intelligence capsule endoscopy with an integrated camera.
WHY THE NEED FOR ROBOTICS?
With current capsule technology, evaluation of the stomach is challenging. The capsule cannot be guided and can remain in the stomach for 15 minutes to hours, relying on gravity and peristalsis to move through the body. To evaluate the entirety of the stomach, an active capsule is necessary…one that can be manipulated. The best way to accomplish this utilizes magnetic control along with sophisticated software and algorithms.
ROBOTICS – A HELPING HAND FOR CLINICIANS
The NaviCam® Stomach System utilizes advanced robotic technologies combined with innovative and intelligent software to provide physicians with external robotic control of a capsule inside the human body.
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ARTIFICIAL INTELLIGENCE – HOW DOES IT WORK?
Artificial intelligence is the primary capability behind the development of precision medicine. Artificial Intelligence (AI) is not one, but rather a collection of technologies. The great majority of precision medicine applications require a training dataset for which the outcome variable is known.
Artificial Intelligence (AI) is one of the primary capabilities behind the development of precision medicine that is broadly used today. AI is not one, but rather a collection of technologies. With AI, a machine or software needs to be trained using a technique called Machine Learning (ML). ML is a method of supervised learning using training algorithms that enables machines or software to learn how to make decisions using provided data to make accurate predictions.
The more complex forms of ML involve Deep Learning (DL), which are models with many levels of variables that predict outcomes. Just like our brain identifies patterns and classifies various types of information, machines can be taught to accomplish the same tasks using deep learning algorithms. Convolutional Neural Networks (CNN) is a type of DL algorithm that takes in an input image, assigns importance to various aspects in the image and is then able to differentiate one from the other.
AnX Robotica used these same types of Dynamic Models to differentiate lesions, tumors, and bleeding from normal. The algorithm was trained with massive amounts of clinical image data classified and marked by Gastroenterologists. After it is optimized to meet stringent sensitivity and accuracy targets, the algorithm became a Static Model, which means it does not continually evolve. This static algorithm was incorporated as part of the intelligent reading support capability in the AnX software platform.
The AnX Robotica NaviCam ® Platform provides physicians with external robotic control to manipulate the capsule in all directions and incorporates software, which if they choose, can enable the physician to recognize abnormalities, assisting them to provide optimal care for their patients.