Artificial Intelligence AI Chatbots in Medicine: A Supplement, Not a Substitute PMC

chatbot in healthcare

This percentage could be even higher now, given the increasing reliance on AI chatbots in healthcare. Questions like these are very important, but they may be answered without a specialist. A chatbot is able to walk the patient through post-op procedures, inform him about what to expect, and apprise him when to make contact for medical help.

chatbot in healthcare

Healthcare chatbots significantly cut unnecessary spending by allowing patients to perform minor treatments or procedures without visiting the doctor. Most insurance agents are stuck working the Quote-to-Cash (QTC) process – an end-to-end process where firms create, price, and prepare initial policy quotes and collect “cash” from customers. These tedious, long processes reduce an insurer’s ability to issue new policies and generate additional revenue. Using AI, insurance quotes can be assessed and delivered to policyholders more efficiently. In fact, they are sure to take over as a key tool in helping healthcare centers and pharmacies streamline processes and alleviate the workload on staff. ScienceSoft’s software engineers and data scientists prioritize the reliability and safety of medical chatbots and use the following technologies.

Conclusion - The future perspective

Another challenge for chatbots in the healthcare industry is security. Chatbots have access to sensitive information, such as patient’s medical records. This information must be protected from unauthorized access and misuse. Chatbots must therefore be designed with security in mind, incorporating features such as encryption and authentication. The future is now, and artificial intelligence (AI) technologies are on the rise. Chatbots have been introduced in many industries to automate and speed processes up by using chat technology that uses natural language processing and machine learning.

chatbot in healthcare

Many medical companies implement rule-based tools as more reliable and cost-efficient solutions. This helps them avoid unnecessary expenses on AI chatbot development services, which can bring some unpredictable results. However, everything depends on business needs and specific customer demands. Businesses will need to look beyond technology when creating futuristic healthcare chatbots.

What’s the most common flaw causing a chatbot to fail?

There are three primary use cases for the use of chatbot technology in healthcare – informative, conversational, and prescriptive. These chatbots vary in their conversational style, the communication, and the type of solutions they provide. One of the most tasking operations of the healthcare industry is scheduling appointments.

Where are chatbots used in healthcare?

A well-designed healthcare chatbot can plan appointments based on the doctor's availability. Additionally, chatbots can be programmed to communicate with CRM systems to assist medical staff in keeping track of patient visits and follow-up appointments while keeping the data readily available for future use.

A chatbot can ask patients a series of questions to help assess their symptoms. Those responses can also help the bot direct patients to the right services based on the severity of their condition. Your patients can access the chatbot through a ton of different channels, giving them access to help anytime and anywhere. That’ll help your patients get a seamless and convenient experience when they need it. You can implement several AI capabilities like machine learning (ML), natural language processing (NLP), speech recognition, etc. Now that we’ve gone over all the details that go into designing and developing a successful chatbot, you’re fully equipped to handle this challenging task.


This transformation enables the healthcare industry to access comprehensive insights and meaningful information from diverse data sources. For example, Generative AI chatbot can extract relevant information from medical notes and categorize it into specific sections, such as patient history, symptoms, diagnosis, and treatment plans. Similarly, it can analyze medical images to identify abnormalities or assist in diagnosis by comparing them with a vast database of reference images. Glass.Health is an exemplar of this capability, as they have created an AI tool that can generate diagnoses and clinical plans by utilizing symptom inputs. Glass AI 2.0 combines an LLM with an extensive clinical knowledge database. OTC (Over the counter) assistance is a valuable feature provided by Generative AI chatbots.

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What tools are required for chatbot?

  • Google Dialogflow.
  • Microsoft Bot Framework.
  • Amazon Lex.
  • BotMan.
  • GupShup.
  • Botsify.
  • Rasa.
Published On: August 21st, 2023 / Categories: AI News /