AI in Medicine: 3 Applications for Healthcare Chatbots

Article by Hengtee Lim | October 23, 2019

There is a lot of research being done on the implementation of AI in medicine. In fact, healthcare chatbots are becoming more and more common. As chatbot technology improves our experiences with self-driving cars and virtual help desks, it’s also improving health services through improved data entry, more detailed analytics, and better self-diagnosis.

But exactly how can a chatbot improve your workplace? And what role does machine learning play in the process?

It’s important to consider these two questions when deciding to introduce AI-driven systems to your workplace. And though they aren’t the only questions, they do provide a good starting point for further research. So let’s take a look at three examples of chatbot applications for improving healthcare.

 

Medical AI Chatbots for Administrative Improvement

Administrative tasks require a significant amount of time and energy in modern healthcare. Though electronic health records help consolidate information between services, physicians often spend more time on data entry than with patients. In addition, many healthcare providers also have a variety of complicated insurance claims to process.

Unsurprisingly, this fragile balance of workload, time, and stress plays a key role in burnout rates. It also keeps physicians and staff at their computers longer, meaning less time spent with patients.

To alleviate some of this administrative burden, medical AI can automate rote tasks and allow for quicker analysis. Through text classification and data collection, physicians can access specific information in health records easily and quickly. AI can also be trained to notice particular symptoms related to specific conditions, so physicians can spot them earlier.

 

Healthcare Chatbots for Physicians

Faster and smoother workflows are not the only areas that benefit from AI in medicine. Healthcare chatbots can also give physicians access to a wider range of information and analytics, helping them make better decisions. One example is SafedrugBot. This healthcare chatbot was designed for women who are breastfeeding, and provides physicians with information related to drugs, their appropriate dosages, and available alternatives.

With the help of natural language processing, medical AI also provides quicker access to patient information at the point of care. This means physicians can ask for specific information without spending too much time at a computer. Instead, the physician simply asks the chatbot for the relevant information, such as past vaccine shots or when a particular medication was first administered.

In addition, the impact of AI in medicine through these chatbots is far-reaching, providing small or rural hospitals access to specific information and a more comprehensive body of research.

 

Healthcare Chatbots for Patients

With the advent of wearable AI and chatbot applications, integrated healthcare chatbots now help patients more accurately self-diagnose their conditions, locate nearby facilities, book appointments, and remember to take medication. Some chatbots, such as Gyant, even allow for physicians to provide diagnoses in real-time, as patients communicate with the chatbot.

The training data for these chatbots ranges from past clinical reports and diagnoses to frequently asked questions and their common responses. Chatbots trained this way can react to patient input by asking smart questions and providing pertinent answers. These conversations could range from illness symptoms, medications, hospital schedules, and more.

The benefits of custom healthcare chatbots is that they create not just better monitoring, but also a real chance for patients to be more aware of their own health.

 

How to Start

The examples listed above are just a handful of ideas for improving your workplace with medical AI chatbots. However, keep in mind that AI in medicine should be tailored to specific needs and goals. You also need to be mindful of common AI issues including privacy and bias. The implementation of AI requires careful consideration and planning, as well as accurate, annotated training data to ensure the best results for your unique application.

This is where Lionbridge can help. With a crowdsourced workforce of 500,000 professionals, Lionbridge is well-equipped to handle the collection of chatbot training data in multiple languages, as well as classifying and annotating the data for specific purposes. We also provide audio data collection and audio classification for the training of voice assistants.

For more on how to start training your own healthcare chatbot, visit our medical services page.

Want help getting started? Get in touch!
The Author
Hengtee Lim

Hengtee is a writer with the Lionbridge marketing team. An Australian who now calls Tokyo home, you will often find him crafting short stories in cafes and coffee shops around the city.

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