Reduce healthcare professionals’ workload and save patients time by leveraging AI-enabled conversational chatbots that can help answer patients questions, schedule appointments, provide reminders for health tasks, and more
Understand the Use-case under 5 minutes
Video (5 minutes)
How Health Chatbots save time and make life easier through automated customer support. It can book doctors appointments, remind users about medications, help them make prescription refills, and more
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Video (2.5 minutes)
How Virtual Healthcare Chatbots leverage Machine Learning and Natural Language Processing to ensure quality healthcare, showing different scenarios enabled by smart chatbots
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Video (1.5 minutes)
Chat to your very own virtual doctor to get personalized and medically accurate health advice in an instant. Free, trustworthy & actionable health information has never been so easy
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Get to know more Business and Technical details about the use-case (15-30 minutes)
More detailed introduction covering business and technical aspects
Article (36 minutes)
Great introduction to Health Chatbots, the role of AI and Machine Learning , real life examples, and what skills and technologies are needed to build great Health Chatbots
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Video (27 minutes)
This talk highlights best practices and considerations when implementing intelligent virtual health assistants, challenges and pitfalls, as well as see real-world use cases that help realize the promise of AI in healthcare
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Article (8 minutes)
In this article, we’ll take a closer look at what chatbots are and the advantages they offer to those in the healthcare industry.
VisitCase studies, Organizational Aspects, Return on Investment examples
Case Study
Geisinger experienced an enormous surge in demand for COVID-19 screening requests, appointments, information and determination of vaccine eligibility. Using Gyant (Health Chatbot), they were able to engage with 66,465 in 2 weeks
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Case Study
Intermountain Healthcare wanted to rapidly respond to the COVID-19 crisis with automated screening. Using a Health Chatbot with symptom evaluation triage capabilities, they were able to handle 7,500 daily covid screanings
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Case Study
Learn how using Quincy the healthcare chatbot helped Coryell Health safely share hundreds of test results with patients during the pandemic resulting in a $78,000 annual ROI.
ReadMore details on the technical aspects of the use-case
Video (10 minutes)
Join Maddy Butzbach from Microsoft Azure AI to learn about common types of chatbots and see how to use Azure AI to build them.
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Video (30 minutes)
Hear how Dropbox used the Amazon Lex interface to build a chatbot as a support offering. The session covers how the Amazon Lex console allows you to easily create flows and manage them
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Video (25 minutes)
In this video you will learn how you can easily build your own healthcare assistant using Azure Health Bot. In the end ,you will be able to build your own assistant either by using the templates or by creating your own customized scenario!
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Technical resources that will help you implement the use-case (notebooks, tutorials..)
Dialogflow is a natural language understanding platform that makes it easy to design and integrate a conversational user interface into your apps. Explore the Documentation and Tutorials
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Lex is an AI amazon service for building conversational interfaces into any application using voice and text. Explore the Documentation and a sample Github Repo that shows an example workflow
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ChatterBot is a machine-learning based conversational dialog engine built in Python which makes it possible to generate responses based on collections of known conversations.
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Video (32 minutes)
In this tutorial you will learn how to build a healthcare chatbot for chronic kidney disease step by step using colab.
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Data Sets you can use to build Demos, POCs, or test Algorithms
An English medical dialogue dataset about COVID-19 and other types of pneumonia. Patients who are concerned that they may be infected by COVID-19 or other pneumonia consult doctors and doctors provide advice. There are 603 consultations.
Two large datasets; 1. English medical dialogue contains 257,454 English consultations between patients and doctors, and 2. Chinese medical dialogue: contains 1,145,231 Chinese consultations between patients and doctors.
A large multi-center database of over 200,000 critical care admissions for 140,000 unique patients admitted to hospitals in the United States. All data were collected during routine patient care
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