Using Machine Learning to diagnose conditions from Medical Images

According to the Medscape National Physician Burnout and Depression Report, 44% of the surveyed radiologists reported burnout. To make matters worse, utilization of Radiology services has increased by 30% over the last five years. This combined with an acute shortage of trained imaging professionals has resulted in a highly stressed workforce.

Accion Labs has built Machine Learning based radiology assistant platforms that can process medical images e.g. X-rays, CT Scans, etc., and provide a #diagnosis in real time e.g. level of Arthritis degeneration in the knee and hips from an X-ray. This helps #radiologists process their backlog of X-rays faster including nightly batches of thousands of images that are pre-processed by the platform. This has helped dramatically reduce errors and increase the Radiology Department’s throughput.

Accion Labs offers an acceleration platform called Medical Imaging and Diagnosis Assistance System (MIDAS) that uses advanced image pre-processing and a variety of Machine Learning algorithms to process medical images and triage them by diagnosis and severity within seconds. The platform provides pre-packaged modules that can be configured and re-trained using human-labeled images.

MIDAS supports Digital Imaging and Communications in Medicine (DICOM), JPG, and other industry-standard image formats. It can be integrated with your RIS/PACS and outbound patient communication systems as well using APIs.

If you’d like to know more, please reach out to us at healthcare@accionlabs.com or share your details here.

#innovation #healthcare #medicalimaging #digitalhealth #healthtech