One of the primary applications of artificial intelligence in medical imaging is assisted diagnosis and screening. It refers to the process of using a large number of high-quality medical imaging data to train deep learning algorithms, and applying the validated software to identify legions during screening and to provide assisted disease detection or diagnosis.

 

It has the potential in dramatically improving screening efficiency with performance on a par with clinicians and radiologists. Quality of healthcare delivery will increase while the cost drops. AI’s application to medical imaging also alleviates the uneven distribution of healthcare resources.

 

 

With the wide adoption of EMR by healthcare providers and a spike in the volume of personal health information collected by wearable devices, massive amount of medical data become available. Machine learning can be utilized to effectively analyze such data and explore its value in precision medicine, health management, drug development and epidemiology, etc.

 

In 2016, State Council announced a landmark policy directive on promoting and regulating healthcare big data’s application and development, officially identified and elevated medical big data to the level of national strategic resources.

 

 

Medical robots refer to medical or assisted care robots used in specific medical settings.

 

As medical robotic systems become established in clinics around the world, one of the next paradigm shifts in the field will come from more precise, less invasive, targeted systems, an emerging area often referred to as micro- and nanorobotics.

 

These tiny bots are being studied to perform screening functions and to treat a variety of diseases. They are designed to enter the body and deliver drugs at a specific location or to perform precise operations. SiBionics is Primarily focused on screening and therapeutic robots.