MedTech: Transforming Healthcare with Medical Imaging AI

Healthcare providers and their patients stand to benefit dramatically from AI technologies, thanks to their ability to leverage data, but for AI developers to perform the research that will feed the next wave of breakthroughs, they first need the right data and the tools to use it. Challenges in Finding Useful Data   The outputs of each of these systems can vary, and researchers need to design workflows to perform initial data ingestion, and possibly ongoing ingestion for new data. As part of this interfacing with various archives, AI developers often source data across imaging modalities, including MR and CT scans, x-rays, and potentially other types of imaging. Once AI researchers have ingested data into their platform, challenges still remain in finding the right subsets. Ensuring a consistent level of quality is crucial for machine learning in order to normalize training data and avoid bias. Just as algorithms can be used to preprocess data at the ingestion step, they can also be applied for quality checks.

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