Chatbots in Healthcare: Six Use Cases

Although not able to directly converse with users, DeepTarget [64] and deepMirGene [65] are capable of performing miRNA and target predictions using expression data with higher accuracy compared with non–deep learning models. With the advent of chatbot use cases in healthcare phenotype–genotype predictions, chatbots for genetic screening would greatly benefit from image recognition. New screening biomarkers are also being discovered at a rapid speed, so continual integration and algorithm training are required.

The integration of this application would improve patients’ quality of life and relieve the burden on health care providers through better disease management, reducing the cost of visits and allowing timely follow-ups. In terms of cancer therapy, remote monitoring can support patients by enabling higher dose chemotherapy drug delivery, reducing secondary hospitalizations, and providing health benefits after surgery [73-75]. We systematically searched the literature to identify chatbots deployed in the Covid-19 public health response.

Mental Health Support

This is especially important for cases where the facilities that care for patients with multiple insurance providers, as it is easier to track which ones cover particular health services and which don’t. Collecting patient health data is crucial to provide proper medical care in the healthcare industry. Chatbots can collect this data from patients and provide it to medical professionals for further analysis. Many customers prefer making appointments online over calling a clinic or hospital directly.

The healthcare industry incorporates chatbots in its ecosystem to streamline communication between patients and healthcare professionals, prevent unnecessary expenses and offer a smooth, around-the-clock helping station. There is no doubt that the accuracy and relevancy of these chatbots will increase as well. But successful adoption of healthcare chatbots will require a lot more than that.

AI Powered Chatbots In Healthcare: Use Cases, Pros And Cons

Healthbots are computer programs that mimic conversation with users using text or spoken language9. The advent of such technology has created a novel way to improve person-centered healthcare. The underlying technology that supports such healthbots may include a set of rule-based algorithms, or employ machine learning techniques such as natural language processing (NLP) to automate some portions of the conversation. UK health authorities have recommended apps, such as Woebot, for those suffering from depression and anxiety (Jesus 2019). Pasquale (2020, p. 46) pondered, ironically, that cheap mental health apps are a godsend for health systems pressed by austerity cuts, such as Britain’s National Health Service.