HIPAA and Machine Learning at Loyal

Deep learning traditionally involves funneling huge data sets into layers of software to produce actionable insights. But when strict privacy requirements control what can appear in the output, machine learning methods have to change. I talked to Abhi Sharma, chief product officer at Loyal, about how they do machine learning. Loyal, I’m told by Sharma, created one of first HIPAA-compliant chatbots. They are continuing to refine their chatbots and extend AI into other areas of the patient experience, using a combination of common machine learning and some new technologies inspired by Google’s BERT algorithm, with large language models. Figure 1 shows a typical screen from one of Loyal’s chatbots, offering several options plus a box for free-form text. Figure 1: Initiating a conversation in a chatbot.   Figure 1: Initiating a conversation in a chatbot. Loyal’s partners include more than 400 hospitals with different sizes and locations. Loyal’s core business, chat, has carried more than 30 million messages, and the company also offers services such as physician search. Loyal creates customized chatbots for each client, asking them what their needs are. For instance, one clinical facility might want to concentrate on patients asking for information on particular conditions, whereas another is concerned with directing a patient to the proper person to handle their reported symptoms. For the desired services, Loyal creates a standard tree structur...
Source: EMR and HIPAA - Category: Information Technology Authors: Tags: Administration Communication and Patient Experience Health IT Company Healthcare IT Hospital - Health System Security and Privacy Abhi Sharma Chatbots Deep Learning Healthcare Chatbots Loyal Machine Learning Patient Chatbot Provi Source Type: blogs