The health sector is increasingly embracing Artificial Intelligence (AI) to boost patient care and improve healthcare. AI tools help caregivers make informed decisions, medical centers attain better outcomes, and patients receive personalized and timelier care. AI applications are evident in various core areas ranging from smart devices to diagnostics as well as health and wellness. Here is how AI plays a role in medical diagnostics and how machine translation can help reach patients in their own language.
Babylon Health, a United Kingdom-based health subscription service, developed a chatbot for the diagnosis and prevention of diseases. Such chatbots use speech recognition technologies to compare the user's symptoms with a disease database. It responds by recommending the right course of action depending on the analysis of reported symptoms, patient circumstances, and patient history.
For instance, if a patient reports flu-like symptoms, the app will advise the patient to get over-the-counter drugs from a pharmacy. On the contrary, if the user describes severe symptoms, the app may advise a quick visit to the hospital or dial an emergency hotline. Besides diagnostic features, the app integrates user information from wearable devices to monitor cholesterol levels and heart rate, among other vitals.
AI’s ability to access and analyze data from different sources and give correct diagnoses will benefit medical professionals and patients.
Artificial Intelligence technology can combine patient information from different sources, such as patients’ Electronic Health Records (EHR) and genetics, to give caregivers more timely suggestions and alerts. In 2017, for instance, the FDA permitted 23andMe to sell direct-to-consumer test that gives genetic risk data for Celiac disease.
AI tools can combine symptoms listed in the EHR, such as vomiting or chronic bloating, with the knowledge of the DNA variation to alert the medical practitioner of an increased chance of Celiac Disease. AI algorithms input information from various sources, such as labs, health records, and genetic tests, among others, to allow personalized and timely outputs.
This is all great if you speak English, but what happens if you don't?
Well, this is where the publishers of such software and chatbots need to ensure that for instance, the database of diseases is pre-translated in order for a patient to be able to get a report or advice in their language.
Translating medical terms used to take time and cost a lot of money. But with the deployment of neural machine translation into the translation workflow, it is now possible to accomplish this faster and cheaper.
If you would like to know if the type of content you have is suitable for machine translation, SimulTrans can offer a totally free report.
Want to learn how you can successfully deploy neural machine translation into your own current translation process and support your patients in their own language?