The 5 Levels Of Automation In Medicine

“Good morning! How may I help you today?” asks the virtual assistant as you boot your telemedicine app. After experiencing a sore throat and runny nose for a few days, you’ve decided to seek medical attention. You share your symptoms with the assistant who subsequently suggests a cause after scanning its database. “There’s an 83% chance that you are experiencing allergic symptoms,” replies the chatbot. “I will send you your prescription shortly, but if you are not satisfied or still feel unwell, please request for a human physician.” Considering the likelihood of the diagnosis and the deductive prowess of the artificial intelligence, you decide to heed to its advice and take the prescribed medicines. However, after two weeks, the symptoms persist and you decide to turn to an ENT specialist. After checking your CT scan, the latter determines that you have chronic sinusitis, which will require a surgical procedure. Had it been diagnosed earlier, you might not even have needed surgery. So who is liable in this hypothetical scenario of the future? The algorithm that suggested allergies rather than an ENT examination, the doctor for not supervising the chatbot or the patient? Going further, what if an algorithm misses a cancerous lesion on an X-ray; or if a surgical robot accidentally damages a nerve bundle and partially paralyses the patient? With A.I. and its potential to automate processes in medicine, such questions will become commonplace. While it’...
Source: The Medical Futurist - Category: Information Technology Authors: Tags: Artificial Intelligence in Medicine Digital Health Research Future of Medicine Healthcare Design Healthcare Policy Medical Education ibm watson automation A.I. Andrew Ng A.I. assistant Journal Of Clinical Oncology Behold.ai Source Type: blogs