The combination of medical image and artificial intelligence is a relatively new branch in the field of digital medical care (Savadjiev,2019), and it is also a hot spot in the digital medical industry. Medical images contain so much data that even experienced doctors can sometimes seem overwhelming. The interpretation of medical images requires the accumulation of professional experience over a long period of time, and the training period for radiologists is relatively long. However, artificial intelligence can detect images faster than professional doctors in efficiency and accuracy, reducing the human error rate.
Several well-known start-ups have emerged in many countries. Enlitic (Journal of Engineering, 2022) in the table is a relatively well-known artificial intelligence medical imaging company. Although it was founded in 2014, it was named one of the 50 smartest companies in the world in 2015 by MIT Technology Review in the following year and received a total of 15 million US dollars in financing. The Butterfly is developing a small ultrasound device that runs largely on software, including using techniques developed by artificial intelligence experts to comb through a series of images to extract features that can automatically diagnose disease. The world’s first and third most active venture capital institutions focusing on artificial intelligence have also become investors in smart medical imaging start-ups.
Judging from the number of misdiagnoses in imaging, the number of misdiagnoses in the United States has reached 12 million per year, while the number of misdiagnoses in China has reached an astonishing 57 million per year due to its huge population base. (Atencio, 2021) These misdiagnoses mainly occur in primary medical institutions. At present, medical imaging in China is transitioning from traditional film to electronic film, while traditional American film has become a thing of the past. The widespread use of electronic film has led to a substantial increase in medical imaging data, with an annual growth rate of 63.1% in the United States and 30% in China. The annual growth rate of radiologists in the United States and China is only 2.2% and 4.1%, which is far lower than the growth of imaging data, forming a huge gap. This means that the workload of doctors is greatly increased, and the accuracy of a judgment is reduced. The use of artificial intelligence to judge images can effectively fill the gap.
Reference:
“Hub Security Partners with Enlitic to Secure Health Data, Enhance Patient Care through Artificial Intelligence” (2022) Journal of Engineering, 829, pp. 829–829.
Atencio, Y. P. et al. (2021) “2021 International Conference on Electrical, Computer, Communications and Mechatronics Engineering (iceccme),” in Image Processing Techniques for Medical Applications. IEEE, pp. 1–6. doi: 10.1109/ICECCME52200.2021.9591045.
Savadjiev, P. et al. (2019) “Demystification of Ai-Driven Medical Image Interpretation: Past, Present and Future,” European radiology, 29(3), pp. 1616–1624. doi: 10.1007/s00330-018-5674-x.
