Robot
BLEEP, BLIP, BLOOP
Jason Warrelmann is global director of healthcare industry at UiPath.
The coronavirus COVID-19 has now infected .0008% of the global population, and the World Health Organization (WHO) estimates this number could double to over 20 million people by the end of the month. China is scrambling to screen patients in the Hubei province, with hospitals overwhelmed and resources strained. News agencies are reporting massive backlogs of clinical documentation and x-rays that are waiting to be reviewed by radiologists to identify and diagnose patients of this deadly respiratory virus. Patients are sitting in makeshift hospitals, citizens are quarantined in their homes, and some travelers have been forced to stay on cruise liners until the port clears them.
The issue of ‘hospital backlogs’ is not new, and hospital administration, government officials, and recently even data scientists have been accelerating their efforts to solve this widespread challenge through technology. We believe our industry can help provide a meaningful improvement here. By combining machine learning (ML) and Robotic Process Automation (RPA) into a single deployable model, we have the ability to compress diagnosis timelines by 50% or more, while also improving accuracy and patient care.
Continue reading...
The coronavirus COVID-19 has now infected .0008% of the global population, and the World Health Organization (WHO) estimates this number could double to over 20 million people by the end of the month. China is scrambling to screen patients in the Hubei province, with hospitals overwhelmed and resources strained. News agencies are reporting massive backlogs of clinical documentation and x-rays that are waiting to be reviewed by radiologists to identify and diagnose patients of this deadly respiratory virus. Patients are sitting in makeshift hospitals, citizens are quarantined in their homes, and some travelers have been forced to stay on cruise liners until the port clears them.
The issue of ‘hospital backlogs’ is not new, and hospital administration, government officials, and recently even data scientists have been accelerating their efforts to solve this widespread challenge through technology. We believe our industry can help provide a meaningful improvement here. By combining machine learning (ML) and Robotic Process Automation (RPA) into a single deployable model, we have the ability to compress diagnosis timelines by 50% or more, while also improving accuracy and patient care.
Continue reading...