Medical Chatbots Use Cases, Examples and Case Studies of Generative Conversational AI in Medicine and Health

Chatbots in Healthcare: Top 6 Use Cases & Examples in 2023

healthcare chatbot use case diagram

Livi, a conversational AI-powered chatbot implemented by UCHealth, has been helping patients pay better attention to their health. The use case for Livi started with something as simple as answering simple questions. Livi can provide patients with information specific to them, help them find their test results. She is an integral part of the patient journey at UCHealth, with a sharp focus on enabling a smooth and seamless patient experience. AI chatbots with natural language processing (NLP) and machine learning enabled help boost your support agents’ productivity and efficiency using human language analysis. You can train your bots to understand the language specific to your industry and the different ways people can ask questions.

Open up the NLU training file and modify the default data appropriately for your chatbot. These platforms have different elements that developers can use for creating the best chatbot UIs. Almost all of these platforms have vibrant visuals that provide information in the form of texts, buttons, and imagery to make navigation and interaction effortless. If you look healthcare chatbot use case diagram up articles about flu symptoms on WebMD, for instance, a chatbot may pop up with information about flu treatment and current outbreaks in your area. The chatbot offers website visitors several options with clear guidelines on preparing for tests such as non-fasting and fasting health checkups, how to prepare for them, what to expect with results, and more.

Share Crucial Health Announcements

Not only can customers book through the chatbot, but they can also ask questions about the tests that will be conducted and get answers in real time. Here are five ways the healthcare industry is already using chatbots to maximize their efficiency and boost standards of patient care. That happens with chatbots that strive to help on all fronts and lack access to consolidated, specialized databases. Plus, a chatbot in the medical field should fully comply with the HIPAA regulation. Recently, Google Cloud launched an AI chatbot called Rapid Response Virtual Agent Program to provide information to users and answer their questions about coronavirus symptoms. Google has also expanded this opportunity for tech companies to allow them to use its open-source framework to develop AI chatbots.

Real time chat is now the primary way businesses and customers want to connect. At REVE Chat, we have extended the simplicity of a conversation to feedback. Healthcare bots help in automating all the repetitive, and lower-level tasks of the medical representatives. While bots handle simple tasks seamlessly, healthcare professionals can focus more on complex tasks effectively. These healthcare chatbot use cases show that artificial intelligence can smoothly integrate with existing procedures and ease common stressors experienced by the healthcare industry. By using NLP technology, medical chatbots can identify healthcare-related keywords in sentences and return useful advice for the patient.

Internal help desk support

Implementing a chatbot for appointment scheduling removes the monotony of filling out dozens of forms and eases the entire process of bookings. They can provide information on aspects like doctor availability and booking slots and match patients with the right physicians and specialists. One of the most prevalent uses of chatbots in healthcare is to book and schedule appointments. Soon enough, organizations like WHO and CDC started adopting conversational AI-powered chatbots to provide curated information to a wide audience with ease.

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There are many more reasons for a medical business to develop a healthcare chatbot app, and you’ll find most of them in this article. Furthermore, social distancing and loss of loved ones have taken a toll on people’s mental health. With psychiatry-oriented chatbots, people can interact with a virtual mental health ‘professional’ to get some relief.

Artificial Intelligence BSc Hons Undergraduate courses University of Kent

Technology and AI Oxford University Department for Continuing Education

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In the event of any change we’ll consult and inform students in good time and take reasonable steps to minimise disruption. This module provides a comprehensive introduction to ai engineer degree computer vision

and practical skills for solving real-world applications. You are given the opportunity to combine your developing CCT knowledge with your programming abilities.

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We will cover the process needed to take the main principles of digital communications such as digital modulation and detection. This course is intended to give students an outline of how wireless communication and computer networks work „above the physical layer”. This includes the interoperability of wireless networks such as WiMax/GPRS and WiFi to provide WiFi on trains etc.

Embedded Computer Systems

You will work closely with your lecturers and supervisors to carry out a major project on the AI topic that you want to specialise in. Chat with current students and King’s staff to find out about the courses we offer, life at King’s and ask any questions you may have. „AI is quite unique in having very deep theoretical foundations as well as tremendous industrial applications…the MSc in AI does a very good job at letting you experience both.” „The group project was an incredible opportunity to work as a team with an external start-up, and learn how to design and build efficient, production level code.” „The MSc in AI undoubtedly gives its graduates a solid foundation on which to build a career in industry or academia.”

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Where a course has additional expenses, we make every effort to highlight them. These may include optional field trips, materials (e.g. art, design, engineering), security checks such as DBS, uniforms, specialist clothing or professional memberships. You will find more information on country specific entry requirements in the International section of our website. Methods of assessment will vary according to subject specialism and individual modules. Most stage three modules are assessed by a combination of coursework and end-of-year examination. Projects are assessed by your contribution to the final project, the final report, and oral presentation and viva examination.


Our MSc Artificial Intelligence covers specialist modules in programming, AI, applied machine learning, data mining robotics and intelligent systems, and computer vision, as well as modules that prepare you for your individual AI project. Throughout the module, students will learn to embed data analysis and statistics concepts into a programming language which offers good support for AI (e.g., Python). Students will learn to use important AI-purposed libraries and tools, and apply these techniques to data loading, processing, manipulation and visualisation. Cyber Security Team Project is a module that equips students with the knowledge needed to keep an organisation secure from today’s cyber security threats and presents the necessary steps to take when a breach occurs. Using a combination of learning methods and teaching techniques such as project based learning, active learning and case studies, this module teaches cyber security management principles that are needed to secure the digital assets of an organisation.

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Can I study AI without coding?

However, the traditional perception of AI being complex and heavily reliant on coding has deterred many from exploring this exciting field. In recent years, advancements in technology have given rise to no-code and low-code AI solutions, enabling individuals to learn and implement AI without extensive coding knowledge.