Imaging AI Field is Exploding in U.S Amidst Challenges

In the AWS panel arranged this week, the experts said, gathering the data, labeling it, and monitoring the efficacy of the tools used in is critical, but the AI tools can be the major bottlenecks in the healthcare space. The U.S Food and Drug Administration has approved 60 new products in the year 2020 to analyze medical imaging data. Thus, it can be seen that the use of machine learning and AI is increasing in the U.S healthcare field.

However, according to Elad Benjamin, the respected general manager, the scaling of AI in the medical field can pose unique challenges. Mr. Elad Benjamin works as a general manager of Radiology and AI Informatics at the Multinational conglomerate company Philips. He said it during the presentation of Amazon Web Services this week.

He said there are various applications and tools being introduced in the AI field. Mr. Benjamin explained how companies could use machine learning and artificial neural networks for the analysis of imaging data and to analyze relevant clinical findings. During the explanation, he outlined three important business models that one should pursue, namely, Triage, Population health, and Decision Support.

Mr. Banjamin, during the presentation, described the common challenges and bottlenecks encountered during the development and marketing of the AI tools. He notified that some challenges in AI tools that are hard to tackle in healthcare. He also stated that gathering the data is a challenge while gathering diverse information is critical and difficult to achieve.

Additionally, he noted that the process of labeling the data incurs more cost and is time-consuming. He added that receiving feedback and monitoring is also sometimes difficult. He emphasized the monitoring of AI tools in the real world. Mr. Benjamin pointed out some AWS tools that are tackling the challenges including, Comprehend, SageMaker, and HealthLake.