Implementation of Chatbot Technology in Health Care: Protocol for a Bibliometric Analysis PMC

Conversational AI may simplify and streamline the onboarding process, help patients through the prescription request process, enable them to update crucial information such as their address or a change in circumstances, and much more. When AI chatbots are trained by psychology scientists by overseeing their replies, they learn to be empathic. Conversational AI is able to understand your symptoms and provide consolation and comfort to help you feel heard whenever you disclose any medical conditions you are struggling with. Although the internet is an amazing source of medical information, it does not provide personalized advice.

This allows for a more relaxed and conversational approach to providing critical information for their file with your healthcare center or pharmacy. Set up messaging flows via your healthcare chatbot to help patients better manage their illnesses. For example, healthcare providers can create message flows for patients who are preparing for gastric bypass surgery to help them stay accountable on the diet and exercise prescribed by their doctor.

Powerful AI chatbot marketing software helps you improve customer experiences and boost lead generation with fast, personalized customer support. Bradesco automated their customer service answers with 95% accuracy using watsonx Assistant—answering 283,000 questions monthly and continuing to learn from feedback of over 10 million interactions. However, if the patient misunderstands a post-care plan instruction or fails to complete particular activities, their recovery outcomes may suffer. A conversational AI system can help overcome that communication gap and assist patients in their healing process. For example, the patient could submit information regarding what post-care steps they have taken and where they are in their treatment plan. In turn, the system might give reminders for crucial acts and, if necessary, alert a physician.

The process of filing insurance inquiries and claims is standardized and takes a lot of time to complete. The solution provides information about insurance coverage, benefits, and claims information, allowing users to track and handle their health insurance-related needs conveniently. A medical facility’s desktop or mobile app can contain a simple bot to help collect personal data and/or symptoms from patients. By automating the transfer of data into EMRs (electronic medical records), a hospital will save resources otherwise spent on manual entry. An important thing to remember here is to follow HIPAA compliance protocols for protected health information (PHI).

Insurance claims

The chatbot helps guide patients through their entire healthcare journey – all over WhatsApp. An AI chatbot can quickly help patients find the nearest clinic, pharmacy, or healthcare center based on their particular needs. The chatbot can also be trained to offer useful details such as operating hours, contact information, and user reviews to help patients make an informed decision. Speed up time to resolution and automate patient interactions with 14 AI use case examples for the healthcare industry. Conversational AI allows patients to stay on top of their physical health by identifying symptoms early and consulting healthcare professionals online whenever necessary. At Haptik, we’ve already witnessed the success of this tech-driven conversational approach to raising public health awareness.

In this blog we’ll walk you through healthcare use cases you can start implementing with an AI chatbot without risking your reputation. In most industries it’s quite simple to create and deploy a chatbot, but for healthcare and pharmacies, things can get a little tricky. You’re dealing with sensitive patient information, diagnosis, prescriptions, and medical advice, which can all be detrimental if the chatbot gets something wrong. Care providers can use conversational AI to gather patient records, health history and lab results in a matter of seconds. Fundamentally, scheduled appointments help reduce patient wait times and improve satisfaction.

While an AI-powered chatbot can help with medical triage, it still requires additional human attention and supervision. The outcomes will be determined by the datasets and model training for conversational AI. Nonetheless, this technology has enormous promise and might produce superior outcomes with sufficient funding. The cost of building a medical chatbot varies based on complexity and features, with factors like development time and functionalities influencing the overall expense. Chatbots collect minimal user data, often limited to necessary medical information, and it is used solely to enhance the user experience and provide personalized assistance. This section provides a step-by-step guide to building your medical chatbot, outlining the crucial steps and considerations at each stage.

Only by adopting this approach, quality chatbots with high usability can be used to promote health care. Chatbots are software applications that use computerized algorithms to simulate conversations with human users through text or voice interactions [1,2]. Compared to human agents, chatbots can efficiently respond to a large number of users simultaneously, conserving human effort and time while still providing users with a sense of human interaction [4]. Against this social-technological backdrop, artificial intelligence (AI) chatbots, also known as conversational AI, hold substantial promise as innovative tools for advancing our health care systems [5]. To fully realize the potential of chatbot technology in improving health outcomes for everyone, sustained collaborative efforts from an interdisciplinary research team comprising chatbot engineers and health scientists are essential.

They are easy to understand and can be tuned to fit basic needs like informing patients on schedules, immunizations, etc. According to the analysis made by ScienceSoft’s healthcare IT experts, it’s a perfect fit for more complex tasks (like diagnostic support, therapy delivery, etc.). In the table below, we compare a custom AI chatbot with two leading codeless healthcare chatbots. Challenges like hiring more medical professionals and holding training sessions will be the outcome. You may address the issues and provide the scalability to handle real-time discussions by integrating a healthcare chatbot into your customer support. This type of chatbot app provides users with advice and information support, taking the form of pop-ups.

These queries often require deep medical knowledge, critical thinking, and years of clinical experience that chatbots do not possess at this point in time [7]. Thus, the intricate medical questions and the nuanced patient interactions underscore the indispensable role of medical professionals in healthcare. AI chatbots are playing an increasingly transformative role in the delivery of healthcare services. By handling these responsibilities, chatbots alleviate the load on healthcare systems, allowing medical professionals to focus more on complex care tasks. AI chatbots are undoubtedly valuable tools in the medical field, enhancing efficiency and augmenting healthcare professionals’ capabilities.

In order to contact a doctor for serious difficulties, patients might use chatbots in the healthcare industry. A healthcare chatbot can respond instantly to every general query a patient has by acting as a one-stop shop. Therefore, a healthcare chatbot can offer patients an easy way to obtain pertinent information, whether they wish to verify their current coverage, file for claims, or track the status of a claim.

The chatbots can use the information and assist the patients in identifying the illness responsible for their symptoms based on the pre-fetched inputs. The patient can decide what level of therapies and medications are required using an interactive bot and the data it provides. Now that you understand the advantages of chatbots for healthcare, it’s time to look at the various healthcare chatbot use cases. This paper presents a protocol of a bibliometric analysis aimed at offering the public insights into the current state and emerging trends in research related to the use of chatbot technology for promoting health. While many patients appreciate receiving help from a human assistant, many others prefer to keep their information private. Chatbots are seen as non-human and non-judgmental, allowing patients to feel more comfortable sharing certain medical information such as checking for STDs, mental health, sexual abuse, and more.

With a team of meticulous healthcare consultants on board, ScienceSoft will design a medical chatbot to drive maximum value and minimize risks. The platform doesn’t offer any in-built user authentication tools or technical safeguards required by HIPAA (data encryption, identity management, etc.), so it is not suited for PHI transfer. A chatbot can send reminders like taking medication or measuring vitals to patients.

In healthcare, AI-powered chatbots evaluate your patients’ lifestyle behaviors, preferences, and medical history to produce tailored daily reminders and guidance. Managing appointments is one of a healthcare facility’s most demanding yet vital tasks. While appointment scheduling systems are now very popular, they are sometimes inflexible and unintuitive, prompting many patients to disregard them in favor of dialing the healthcare institution. Chatbots can quickly and efficiently handle a high volume of patient queries, addressing routine questions and concerns and freeing up healthcare professionals to focus on complex cases and direct patient interaction. This improves response times and reduces wait times, leading to a more positive patient experience.

For example, the conversational AI system records numerous instances of patients attempting to schedule appointments with podiatrists but failing to do so within a reasonable timeline. A study of the data would reveal this reoccurring pattern, and the healthcare organization may then determine that they may need to hire more podiatrists to meet patient demand. Relying on 34 years of experience in data science and AI and 18 years in healthcare, ScienceSoft develops reliable AI chatbots for patients and medical staff. Using the integrated databases and applications, a chatbot can answer patients’ questions on a healthcare organization’s schedule, health coverage, insurance claims statuses, etc.

If navigating the intricacies of chatbot development for healthcare seems daunting, consider collaborating with experienced software engineering teams. Chatbots provide 24/7 availability, allowing patients to access information and support whenever needed, increasing their engagement with the healthcare system. They can answer basic questions, schedule appointments, and manage tasks, all within the comfortable environment of a digital interface, attracting patients who prefer a self-service approach. Automating medication refills is one of the best applications for chatbots in the healthcare industry. Due to the overwhelming amount of paperwork in most doctors’ offices, many patients have to wait for weeks before filling their prescriptions, squandering valuable time. Instead, the chatbot can check with each pharmacy to see if the prescription has been filled and then send a notification when it is ready for pickup or delivery.

Using AI to imitate an actual conversation, medical chatbots will send personalized messages to users. Backed by sophisticated data analytics, AI chatbots can become a SaMD tool for treatment planning and disease management. A chatbot can help physicians ensure the medications’ compatibility, plan the dosage, consider medication alternatives, suggest care adjustments, etc. The rise in demand is supported by increased adoption of innovations, lack of patient engagement, and need to automate initial patient assessment.

How Much Does It Cost to Build a Prescription Discount App like GoodRx?

These health chatbots are better capable of addressing the patient’s concerns since they can answer specific questions. Infobip can help you jump start your conversational patient journeys using AI technology tools. Get an inside look at how to digitalize and streamline your processes while creating ethical and safe conversational journeys on any channel for your patients. However, Conversational AI will get better at simulating empathy over time, encouraging individuals to speak freely about their health-related issues (sometimes more freely than they would with a human being).

These human traits are invaluable in effective patient care, especially when nuanced language interpretation and non-verbal cues come into play. AI chatbots are limited to operating on pre-set data and algorithms; the quality of their recommendations is only as good as the data fed into them, and any substandard or biased data could result in harmful outputs. Because it reduces many of the common issues of FAQ sections on healthcare providers’ websites, conversational AI is the best solution for self-service in healthcare. Users may struggle to identify the most appropriate response to their query using the website search tool, for example, since they aren’t using the same vocabulary as the FAQ. Alternatively, they may have a number of queries that need them to navigate to various sites. Harness the full potential of healthcare chatbots and create a more engaging and efficient experience for your patients and healthcare professionals.

ChatBot guarantees the highest standards of privacy and security to help you build and maintain patients’ trust. Patients who look for answers with unreliable online resources may draw the wrong conclusions. Data sharing is not applicable to this article as no data sets were generated or analyzed during this study. Once again, go back to the roots and think of your target audience in the context of their needs. AI chatbots cannot perform surgeries or invasive procedures, which require the expertise, skill, and precision of human surgeons.

Second, misinformation originates from the immature or flaws of the chatbot algorithms. Training a chatbot is an iterative process that demands a large data set and vetting of the outputs by researchers. During a chatbot creation, the earlier versions of the chatbot often provide redundant and impersonalized information that may prevent users from using the chatbot. To increase chatbot usability, a chatbot must be precise enough in its communications with users or can connect users to a human agent if necessary [11,12]. You can foun additiona information about ai customer service and artificial intelligence and NLP. Third, even well-trained chatbots can provide biased responses or solutions to users [13]. To minimize these risks of using chatbots in health care, it is necessary for researchers to validate chatbot outputs and reduce biases in the data sets used to train a chatbot.

While the phrases chatbot, virtual assistant, and conversational AI are sometimes used interchangeably, they are not all made equal. Healthcare chatbots prioritize safety and Chat PG security, employing encryption and strict data protection measures. Depending on the interview outcome, provide patients with relevant advice prepared by a medical team.

Emergencies can happen at any time and need instant assistance in the medical field. Patients may need assistance with anything from recognizing symptoms to organizing operations at any time. Our goal is to complete the screening of papers and perform the analysis by February 15, 2024. We anticipate a significant increase in chatbot research following the emergence of ChatGPT.

Ideal channels are ones that patients easily access and integrate seamlessly with existing systems. Voice assistants, bots, and messaging platforms are some of the most often used choices for meeting the demands of various patients. Conversational AI systems do not face the same limitations in this area as traditional chatbots, such as misspellings and confusing descriptions. Even if a person is not fluent in the language spoken by the chatbot, conversational AI can give medical assistance. In these cases, conversational AI is far more flexible, using a massive bank of data and knowledge resources to prevent diagnostic mistakes. Patients frequently have pressing inquiries that require immediate answers but may not necessitate the attention of a staff member.

They can also be programmed to answer specific questions about a certain condition, such as what to do during a medical crisis or what to expect during a medical procedure. As patients continuously receive quick and convenient access to medical services, their trust in the chatbot technology will naturally grow. Although AI chatbots can provide support and resources for mental health issues, they cannot replicate the empathy and nuanced understanding that human therapists offer during counseling sessions [6,8]. Healthcare insurance claims are complicated, stressful, and not something patients want to deal with, especially if they are in the middle of a health crisis. Using an AI chatbot for health insurance claims can help alleviate the stress of submitting a claim and improve the overall satisfaction of patients with your clinic.

• AI and chatbot integration in healthcare refers to the application of Artificial Intelligence and automated response systems (chatbots) within the healthcare sector.
• This type of chatbot app provides users with advice and information support, taking the form of pop-ups.
• While many patients appreciate receiving help from a human assistant, many others prefer to keep their information private.
• Augment your customer service agents and scale your team’s best techniques, insights, and important data across every interaction in real time.
• ScienceSoft’s healthcare IT experts narrowed the list down to 6 prevalent use cases.

Healthcare chatbots can remind patients when it’s time to refill their prescriptions. These smart tools can also ask patients if they are having any challenges getting the prescription filled, allowing their healthcare provider to address any concerns as soon as possible. Future assistants may support more sophisticated multimodal interactions, incorporating voice, video, and image recognition for a more comprehensive understanding of user needs. At the same time, we can expect the development of advanced chatbots that understand context and emotions, leading to better interactions.

Undoubtedly, medical chatbots will become more accurate, but that alone won’t be enough to ensure their successful acceptance in the healthcare industry. As the healthcare industry is a mix of empathy and treatments, a similar balance will have to be created for chatbots to become more successful and accepted in the future. As a result of this training, differently intelligent conversational AI chatbots in healthcare may comprehend user questions and respond depending on predefined labels in the training data.

When it is your time to look for a chatbot solution for healthcare, find a qualified healthcare software development company like Appinventiv and have the best solution served to you. A healthcare chatbot example for this use case can be seen in Woebot, which is one of the most effective chatbots in the mental health industry, offering CBT, mindfulness, and dialectical behavior therapy (DBT). Several healthcare service companies are converting FAQs by adding an interactive healthcare chatbot to answer consumers’ general questions.

It’s inevitable that questions will arise, and you can help them submit their claims in a step-by-step process with a chatbot or even remind them to complete their claim with personalized reminders. For hospitals and healthcare centers, conversational AI helps track and subsequently optimize resource allocation. Another significant aspect of conversational AI is that it has made healthcare widely accessible. People can set and meet their health goals, and receive routine tips to lead a healthy lifestyle. In addition, patients have the tools and information available on their fingertips to manage their own health.

In addition to answering the patient’s questions, prescriptive chatbots offer actual medical advice based on the information provided by the user. To do that, the application must employ NLP algorithms and have the latest knowledge base to draw insights. Informative, conversational, and prescriptive healthcare chatbots can be built into messaging services like Facebook Messenger, Whatsapp, or Telegram or come as standalone apps. In conclusion, it is paramount that we remain steadfast in our ultimate goal of improving patient outcomes and quality of care in this digital frontier.

To the best of our knowledge, this is the first study aimed at summarizing the current status and future trends of chatbots in the health care field. This study includes papers published since the inception of the chatbot and is not confined by the language of publication. Consequently, it offers a global perspective on the evolution of chatbots within the health care domain.

A study conducted six months ago on the use of AI chatbots among healthcare workers found that nearly 20 percent of them utilized ChatGPT [5]. This percentage could be even higher now, given the increasing reliance on AI chatbots in healthcare. With that being said, we could end up seeing AI chatbots helping with diagnosing illnesses or prescribing medication. We would first have to master how to ethically train chatbots to interact with patients about sensitive information and provide the best possible medical services without human intervention.

Healthcare chatbots are intelligent assistants used by medical centers and medical professionals to help patients get assistance faster. They can help with FAQs, appointment booking, reminders, and other repetitive questions or queries that often overload medical offices. When we talk about the healthcare sector, we aren’t referring solely to medical professionals such as doctors, nurses, medics etc. but also to administrative staff at hospitals, clinic and other healthcare facilities. They might be overtaxed at the best of times with the sheer volume of inquiries and questions they need to field on a daily basis.

use cases for healthcare chatbots

However, the future of these AI chatbots in relation to medical professionals is a topic that elicits diverse opinions and predictions [2-3]. The paper, “Will AI Chatbots Replace Medical Professionals in the Future?” delves into this discourse, challenging us to consider the balance between the advancements in AI and the irreplaceable human aspects of medical care [2]. Train your chatbot to be conversational and collect feedback in a casual and stress-free way. The efficiency of appointment scheduling via chatbots significantly reduces waiting times, enhancing the overall patient experience. In fact, 78% of surveyed physicians consider this application one of the most innovative and practical features of chatbots in healthcare (Source ). Launching a chatbot may not require any specific IT skills if you use a codeless chatbot product.

The current body of research papers lacks the breadth of a comprehensive scientific performance mapping analysis. This overview will facilitate the identification of areas for improvement and promote the integration of chatbot technology into health care systems. When using a healthcare chatbot, a patient is providing critical information and feedback to the healthcare business. This allows for fewer errors and better care for patients that may have a more complicated medical history.

Before a diagnostic appointment or testing, patients often need to prepare in advance. Use an AI chatbot to send automated messages, videos, images, and advice to patients in preparation for their appointment. The chatbot can easily converse with patients and answer any important questions they have at any time of day. The chatbot can also help remind patients of certain criteria to follow such as when to start fasting or how much water to drink before their appointment. In general, people have grown accustomed to using chatbots for a variety of reasons, including chatting with businesses. In fact, 52% of patients in the USA acquire their healthcare data through chatbots.

• In order to contact a doctor for serious difficulties, patients might use chatbots in the healthcare industry.
• Therefore, a healthcare chatbot can offer patients an easy way to obtain pertinent information, whether they wish to verify their current coverage, file for claims, or track the status of a claim.
• Healthcare chatbots can offer this information to patients in a quick and easy format, including information about nearby medical facilities, hours of operation, and nearby pharmacies and drugstores for prescription refills.
• Of course, no algorithm can compare to the experience of a doctor that’s earned in the field or the level of care a trained nurse can provide.
• Launching a chatbot may not require any specific IT skills if you use a codeless chatbot product.

Informative chatbots offer the least intrusive approach, gently easing the patient into the system of medical knowledge. That’s why they’re often the chatbot of choice for mental health support or addiction rehabilitation services. Now that you have a solid understanding of healthcare chatbots and their crucial aspects, it’s time to explore their potential!

NLP enables the model to comprehend the text rather than simply scanning for a few words to get a response. A healthcare chatbot is a computer program designed to interact with users, providing information and assistance in the healthcare domain. You can build a secure, effective, and user-friendly healthcare chatbot by carefully considering these key points. Remember, the journey doesn’t end at launch; continuous monitoring and improvement based on user feedback are crucial for sustained success. Healthcare chatbots find valuable application in customer feedback surveys, allowing bots to collect patient feedback post-conversations.

These campaigns can be sent to relevant audiences that will find them useful and can help patients become more aware and proactive about their health. Conversational AI solutions help track body weight, what and which medications to take, health goals that people are on course to meet, and so on. All client examples cited or described are presented as illustrations https://chat.openai.com/ of the manner in which some clients have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics will vary depending on individual client configurations and conditions. Generally expected results cannot be provided as each client’s results will depend entirely on the client’s systems and services ordered.

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Data security is a top priority in healthcare, and AI and chatbot platforms should adhere to HIPAA guidelines and other relevant data protection regulations. However, it’s important to ensure that any AI or chatbot tool used is from a trusted source and complies with all necessary security regulations. Conversational AI in healthcare communication channels must be carefully selected for successful execution.

Liliya’s expert knowledge in the intricacies of EMR/EHR systems, HIPAA compliance, EDI, and HL7 standards makes a great contribution to Binariks through commitment to our working principles. Namely, to always add an industry-specific lens and prioritize security and compliance to deliver unmatched value to our customers. Liliya is a highly skilled developer and a true techie whose hands-on experience reaches across multiple healthcare IT modules, providing a deep understanding of the nuances and complexities of healthtech regulations. Contact us today to discuss your vision and explore how custom chatbots can transform your business. This approach proves instrumental in continuously enhancing services and fostering positive changes within the healthcare environment (Source ).

Chatbot engineers then upgrade the chatbot, followed by health scientists testing the updated version, training it, and conducting further assessments. This iterative cycle can impose significant demands in terms of time and funding before a chatbot is equipped with the necessary knowledge and language skills to deliver precise responses to its users. Despite the obvious benefits of chatbot technology in health care, several potential risks of using chatbots exist, including breaching privacy, providing misinformation, and generating systematically biased responses [2,7-9]. These risks are relevant to the nature of chatbot technology, in which chatbot developers need to maximize a personalized experience and enable chatbots to provide users with precision answers through training chatbots [12]. However, training chatbots requires chatbot technology to have access to a wealth of users’ personal data. To address privacy issues, chatbot developers and researchers must ensure that users’ data are protected using encryption during human-chatbot interactions or when a chatbot needs to retrieve backend data [2].

The latter was particularly important from a customer experience standpoint, given that there is understandably a lot of anxiety that surrounds an impending test report, which makes a swift response all the more appreciated. The healthcare sector can certainly benefit tremendously from such AI-driven customer care automation. In fact, Haptik has worked with several healthcare brands to implement such solutions – one of the most successful examples being our work with a leading diagnostics chain, Dr. LalPathLabs. It assists patients by providing timely appointment reminders, informing them about documents they should (or needn’t) bring, and whether they might need someone’s assistance after the appointment. Augment your customer service agents and scale your team’s best techniques, insights, and important data across every interaction in real time.

They could be particularly beneficial in areas with limited healthcare access, offering patient education and disease management support. However, considering chatbots as a complete replacement for medical professionals is a myopic view. The more plausible and beneficial future lies in a symbiotic relationship where AI chatbots and medical professionals complement each other.

People with chronic health issues, such as diabetes, asthma, etc., can benefit most from it. With the use of sentiment analysis, a well-designed healthcare chatbot with natural language processing (NLP) can comprehend user intent. The bot can suggest suitable healthcare plans based on how it interprets human input. When every second counts, chatbots in the healthcare industry rapidly deliver useful information. For instance, chatbot technology in healthcare can promptly give the doctor information on the patient’s history, illnesses, allergies, check-ups, and other conditions if the patient runs with an attack.

In the long term, Conversational AI can serve as a virtual ‘healthcare consultant’ at any point in time – answering questions that millions of people across the globe have about major and minor health-related issues on a daily basis. In this regard, a conversation with an AI Assistant would efficiently substitute the initial phone call you might make to your doctor to discuss your concerns, before making an in-person appointment. In certain situations, conversational AI in healthcare has made better triaging judgments than certified professionals with a deeper examination of patients’ symptoms and medical history. The introduction of chatbots has significantly improved healthcare, especially in providing patients with the information they seek. This was particularly evident during the COVID-19 pandemic when the World Health Organization (WHO) deployed a COVID-19 virtual assistant through WhatsApp.

Conversational AI has the potential to enable governments and institutions to establish a reliable source of information about the virus’s transmission. For example, in the case of a public health crisis such as COVID-19, a conversational AI system may distribute recommended advice such as washing your hands for 20 seconds, maintaining social distance, and wearing a face covering. Conversational AI, on the other chatbot technology in healthcare hand, uses natural language processing (NLP) to comprehend the context and “parse” human language in order to deliver adaptable responses. An exemplary case is Saba Clinics, the largest multispecialty skincare and wellness center in Saudi Arabia, which utilized a WhatsApp chatbot to streamline the feedback collection process. Share information about your working hours, clinicians, treatments, and procedures.

It can raise awareness about a specific health-related concern or crisis by offering swift access to accurate, reliable and timely information. All this in an engaging, conversational manner, across a range of digital platforms including websites, social media, messaging apps etc. There can be no substitute for the inspiring efforts of doctors, medics and other healthcare providers, but technology can play a key role in enabling them to focus their energies more effectively and amplifying the impact of their work.

These virtual assistants, powered by artificial intelligence (AI) , are poised to revolutionize patient experience and streamline workflows across various healthcare settings. Perfectly imitating human interaction, AI-powered medical chatbots can improve the quality and availability of care and patient engagement, drive healthcare and administrative staff productivity, facilitate disease self-management. AI chatbots often complement patient-centered medical software (e.g., telemedicine apps, patient portals) or solutions for physicians and nurses (e.g., EHR, hospital apps).

The number of interactions patients have with healthcare experts varies significantly depending on their stage of treatment. For example, post-treatment patients may have frequent check-ups with a doctor, but they are otherwise responsible for following their post-treatment plan. AI chatbots that have been upgraded with NLP can interpret your input and provide replies that are appropriate to your conversational style. Intelligent conversational interfaces address this issue by utilizing NLP to offer helpful replies to all questions without requiring the patient to look elsewhere. Furthermore, conversational AI may match the proper answer to a question even if its pose differs significantly across users and does not correspond with the precise terminology on-site.