Open AccessCOGNITIVE NATURAL LANGUAGE PROCESSING ASSISTANT FOR POST-OPERATIVE CARE
Author(s) -
Konduru Viswanath Akhil,
Mythri Shivakumar,
Ajay Vardhan Reddy
Publication year - 2021
Publication title -
international research journal of computer science
Language(s) - English
Resource type - Journals
ISSN - 2393-9842
DOI - 10.26562/irjcs.2021.v0806.001
Subject(s) - unavailability , schedule , conversation , cognition , computer science , health care , quality (philosophy) , grammar , psychology , medical emergency , medicine , engineering , linguistics , psychiatry , communication , philosophy , epistemology , economics , reliability engineering , economic growth , operating system
The vast intricacies that hover over post-operative care often lead to higher risk and inherent damage, when ignored. Postoperative care has several complications, ranging from decreased quality of care due to enormous patient to doctor gap ratio to unavailability of remote healthcare. To ensure that these issues are eradicated, the Cognitive NLP assistant using Dialogflow is proposed. This assistant will hold a regular conversation similar to what a medical professional would, but at the feasibility of the user’s home. It will monitor and track symptoms. The assistant will suggest prompts, based on prior charts and care suggested for the respective surgery. The proposed methodology is achieved by using the Rule-Based Grammar algorithm and the ML matching algorithm. The assistant’s services will extend to connecting with the medical professional if any abnormalities arise and cover communication gaps, by providing the details it has gathered. This assistant has reduced the burden of the physician while providing care to the user and eliminating the need to travel distances to seek treatment for non-emergent issues along with reducing the stress to schedule an appointment. It will function as a whole care provider by being available around the clock to tend to the user.