AI helps clinicians to review scans and images and consequently, it helps radiologists to assess important insights to prioritize critical issues. This way, you can reduce potential errors while reading the EHRs (Electronic Health Records) and also form a more accurate diagnosis.
A medical study results in massive amounts of images and data that needs to be read and analysed. AI algorithms help to do an analysis on these data at a higher speed and do a comparison with other studies to detect patterns and interconnections which may be out of sight. The process largely helps medical imaging clinicians to detect crucial details quickly.
For instance, HMH (Hardin Memorial Health) was looking for a way out to extract crucial data from EHRs for imaging experts. The ER had over 70,000 patients every year and decided to collaborate with IBM for implementing “The Patient Synopsis”. It is a system that can assess the information of the patient related to the imaging process performed on that patient.
Patient Synopsis helps to extract the medical procedures, diagnostics, current allergies, lab results and medical history thereby delivering a summary to cardiologists and radiologists. The summary emphasizes the context for these procedures. The product can be combined with any medical unit system that can be accessed through any communication device and upgraded with no impact on the routine activity of the medical device.
AI contributes to a great extent as it detects relevant problems and presents them to radiologists in the form of a summary that makes the design highly customised, accurate and targeted report utilized in the medical decision process.