Chatbot for Health Care and Oncology Applications Using Artificial Intelligence and Machine Learning: Systematic Review

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. There were 47 (31%) apps that were developed for a primary care domain area and 22 (14%) for a mental health domain. Involvement in the primary care domain was defined as healthbots containing symptom assessment, primary prevention, and other health-promoting measures.

Unlike artificial systems, experienced doctors recognise the fact that diagnoses and prognoses are always marked by varying degrees of uncertainty. They are aware that some diagnoses may turn out to be wrong or that some of their treatments may not lead to the cures expected. Thus, medical diagnosis and decision-making require ‘prudence’, that is, ‘a mode of reasoning about contingent matters in order to select the best course of action’ (Hariman 2003, p. 5). Further refinements and large-scale implementations are still required to determine the benefits across different populations and sectors in health care [26]. Although overall satisfaction is found to be relatively high, there is still room for improvement by taking into account user feedback tailored to the patient’s changing needs during recovery.

Assess your needs, considering desired chatbot healthcare use cases

Many healthcare chatbots using artificial intelligence already exist in the healthcare industry. These include OneRemission, which helps cancer patients manage symptoms and side effects, and Ada Health, which assesses symptoms and creates personalized health information, among others. ChatGPT and similar chatbot-style artificial intelligence software may soon serve a critical frontline role in the healthcare industry. ChatGPT is a large language model using vast amounts of data to generate predictive text responses to user queries. Released on November 30, 2022, ChatGPT, or Chat Generative Pre-trained Transformer, has become one of the fastest-growing consumer software applications, with hundreds of millions of global users.

Following Pasquale (2020), we can divide the use of algorithmic systems, such as chatbots, into two strands. First, there are those that use ML ‘to derive new knowledge from large datasets, such as improving diagnostic accuracy from scans and other images’. Second, ‘there are user-facing applications […] which interact with people in real-time’, providing advice and ‘instructions based on probabilities which the tool can derive and improve over time’ (p. 55). The latter, that is, systems such as chatbots, seem to complement and sometimes even substitute HCP patient consultations (p. 55). The systematic literature review and chatbot database search includes a few limitations.

Top Health Chatbots

Their results suggest that the primary factor driving patient response to COVID-19 screening hotlines (human or chatbot) were users’ perceptions of the agent’s ability (Dennis et al. 2020, p. 1730). A secondary factor in persuasiveness, satisfaction, likelihood of following the agent’s advice and likelihood of use was the type of agent, with participants reporting that they viewed chatbots more positively in comparison with human agents. One of the positive aspects is that healthcare organisations struggling to meet user demand for screening services can provide new patient services. However, one of the downsides is patients’ overconfidence in the ability of chatbots, which can undermine confidence in physician evaluations.

For each app, data on the number of downloads were abstracted for five countries with the highest numbers of downloads over the previous 30 days. Chatbot apps were downloaded globally, including in several African and Asian countries with more limited smartphone penetration. The United States had the highest number of total downloads (~1.9 million downloads, 12 apps), followed by India (~1.4 million downloads, 13 apps) and the Philippines (~1.25 million downloads, 4 apps). Details on the number of downloads and app across the 33 countries are available in Appendix 2. Only ten apps (12%) stated that they were HIPAA compliant, and three (4%) were Child Online Privacy and Protection Act (COPPA)-compliant. For example, the system entity @sys.date corresponds to standard date references like 10 August 2019 or the 10th of August [28].

What are the top chatbot use cases in healthcare?

Implementing chatbots in healthcare requires a cultural shift, as many healthcare professionals may resist using new technologies. Providers can overcome this challenge by providing staff education and training and demonstrating the benefits of chatbots in improving patient outcomes and reducing workload. Telemedicine uses technology to provide healthcare services remotely, while chatbots are AI-powered virtual assistants that provide personalized patient support.

With the rapidly increasing applications of chatbots in health care, this section will explore several areas of development and innovation in cancer care. Various examples of current chatbots provided below will illustrate their ability to tackle the triple aim of health care. The specific use case of chatbots in oncology with examples of actual products and proposed designs are outlined in Table 1. 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. However, chatbot solutions for the healthcare industry can effectively complement the work of medical professionals, saving time and adding value where it really counts. A chatbot can monitor available slots and manage patient meetings with doctors and nurses with a click.

This can be addressed by integrating with electronic medical records and other healthcare systems and adopting tools like dbt. Based on a large language model (LLM) developed by Google, the chatbot demonstrated superior accuracy in diagnosing respiratory issues, cardiovascular conditions, and various chatbot technology in healthcare ailments than a general practitioner. Furthermore, compared with human doctors, the algorithm extracted a similar amount of information from dialogues, displaying a higher level of empathy, as reported in a preprint study by Tao Tu and colleagues from Google Research and Google DeepMind.

A chatbot is a typical example of an AI system and one of the most elementary and widespread examples of intelligent Human-Computer Interaction (HCI) [1]. It is a computer program, which responds like a smart entity when conversed with through text or voice and understands one or more human languages by Natural Language Processing (NLP) [2]. In the lexicon, a chatbot is defined as “A computer program designed to simulate conversation with human users, especially over the Internet” [3]. Chatbots are also known as smart bots, interactive agents, digital assistants, or artificial conversation entities. The app helps people with addictions  by sending daily challenges designed around a particular stage of recovery and teaching them how to get rid of drugs and alcohol.

An Overview of the Use of Chatbots in Medical and Healthcare Education

Using a combination of data-driven natural language processing with knowledge-driven diagnostics, this chatbot interviews the patient, understands their chief complaints, and submits reports to physicians for further analysis [43]. Similarly, Sense.ly (Sense.ly, Inc) acts as a web-based nurse to assist in monitoring appointments, managing patients’ conditions, and suggesting therapies. Another chatbot that reduces the burden on clinicians and decreases wait time is Careskore (CareShore, Inc), which tracks vitals and anticipates the need for hospital admissions [42]. Chatbots have also been proposed to autonomize patient encounters through several advanced eHealth services. In addition to collecting data and providing bookings, Health OnLine Medical Suggestions or HOLMES (Wipro, Inc) interacts with patients to support diagnosis, choose the proper treatment pathway, and provide prevention check-ups [44]. Although the use of chatbots in health care and cancer therapy has the potential to enhance clinician efficiency, reimbursement codes for practitioners are still lacking before universal implementation.

• Electronic health records have improved data availability but also increased the complexity of the clinical workflow, contributing to ineffective treatment plans and uninformed management [86].
• Contact to the chatbot is spread through a user’s social graph without leaving the messaging app the chatbot lives in, which provides and guarantees the user’s identity.
• If you want your company to benefit financially from AI solutions, knowing the main chatbot use cases in healthcare is the key.
• Chatbot is a timely topic applied in various fields, including medicine and health care, for human-like knowledge transfer and communication.