First Full-Stack AI Radiology Clinic - Towards Automation in Health-Care

Abstract

Building a AI full-stack Radiology Clinic requires accounting for many variables: building an infrastructure that can be safely deployed in hospital environment with the respect to all data protection and patent privacy guidelines, creating accurate algorithms for classifying radiology data (MRI, X-ray, CT etc.), incorporating tools with generative abilities that can, given the imaging input, make a radiologist-level report that correctly interprets images and performs that by utilizing specific medical vocabulary. Likewise, this system also relies on various methods that allow for patient interaction, simulating what would usually be a patient-doctor interaction. Also, this setup also requires finding software solution that increases imaging resolution and aids in more precisely identifying medical conditions. To the best of my knowledge, this paper is the first available literature to propose a comprehensive solution to radiology clinic where the most important tasks can be handled by AI. In my opinion, the potential implications of this paper can be far-reaching. Most countries in the world suffer from the critical lack of radiologists and have less then 1 radiologist per 100 thousand people. Likewise, US projects a shortage of more than 20 thousand physicians with radiology being one of the most affected fields. Furthermore, even developed countries have somewhat constrained access to radiologists and radiology clinics (US has only 30 thousand radiologists for more then 340 million people) while developing countries have even lower radiologists-to-population ratio. Additionally, it is estimated that applying comprehensive AI solutions for radiology clinics that require very little human input can drastically reduce costs for building a radiology clinic: experts estimate that formation of the conventional radiology clinic can cost up to 8 million dollars while applying AI solutions such as those outlined in our paper can bring expenditures down to 500 thousand to 1 million dollars. In conclusion, we believe that this necessitates emergence of the solution that makes radiology clinics more feasible and less dependent on radiologist presence particularly in areas with less radiologist frequency.