International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
HealthCare Chatbot Manaswi Vichare1, Divya Kadole2, Sheetal Kumari3, Shresth Jain4 Student, Dept of CSE, MIT School of Engineering, MIT ADT University, Pune, Maharashtra, India ---------------------------------------------------------------------***--------------------------------------------------------------------1,2,3,4
Abstract - With changing times due to the Covid-19 pandemic, it is advisable to leave our houses only during emergencies. Despite the fact that hospitals maintain adequate precautions, people still remain fearful of visiting them due to the risk of getting infected. In the safe confines of one's own home, this work can be used to analyze and understand diseases and symptoms. It contains a Medical Test webpage that makes predictions about various illnesses using the concept of machine learning. If the user wants to know the cause for the particular symptom, they can use the chat-bot facility. The chat-bot will ask to state the symptoms which the user is experiencing. The user can state their symptoms one by one and receive the predicted output. It will also provide the probability of the illness occurring based on the symptoms. A set of possible future symptoms are also displayed concerning the probable disease. When an emergency occurs, it helps pinpoint what is wrong and recommends expert doctors based on their Practo profile to schedule an appointment. Key Words: Chatbot, Healthcare, Machine learning, Decision Tree, Natural Language Processing, Neural Network
1. INTRODUCTION Even though we are getting accustomed to the latest changes due to the Covid-19 pandemic, the fear of getting infected is increasing due to new emerging variants. Despite the strict lockdown restrictions, the cases are yet to be recovered, causing a disturbance in our daily life. One of the issues includes applying for a doctor's appointment. The hospitals follow the Covid-19 protocols up to the mark, yet people have a misconception of hospitals being a hotspot for Corona patients. To minimize this fear and to avoid people leaving their houses frequently, we came up with an idea of selfdiagnosis at home. The user can check their health reports for crucial concerns regarding Cancer, Diabetes, Heart, Liver, Kidney, Malaria, Pneumonia, which are prime health issues faced in India. This process is carried out through a Medical Web page using Flask, where the users can input their health report details and get a diagnosis for the same. This web page is developed using machine learning and web development methods. Other queries related to health are answered through the chatbot service. The chatbot will ask the user to state the symptoms, for example, the user types "I’m feeling cold", "There are skin rashes", "Vomiting", "Fatigue" etcetera, and the model will then predict that the user has "Dengue." Further, it will list out more symptoms that may occur and calculate the probability of the illness supposedly happening, © 2022, IRJET
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Impact Factor value: 7.529
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based on the symptoms selected. It helps to figure out what is wrong and how urgent the situation is and recommends expert doctors with their Practo profile to book an appointment in the case of an emergency. The main benefit of this research is that the users will be able to evaluate the severity of their illnesses and take the appropriate action as a result. In that way, they can determine if a hospital visit or clinic consultation is necessary or if self-diagnosis and telephonic consultation would suffice. Rather than spending hours waiting and making multiple trips to the hospital, you can save time through this work.
2. LITERATURE REVIEW In [1], the authors developed an intelligent virtual assistant able to talk with patients to understand their symptomatology, counsel doctors, and monitor treatments and health parameters. By utilizing a natural language-based interaction, the system permits the user to form their health profile, describe their symptoms, search for doctors, or remember a treatment to attend. As a future scope, they want to boost the performance of the Symptom Checker module by adding information on the rarity of the diseases; automatic suggestions of food and physical activity to perform based on the user’s health conditions. An exploratory study on using conversational interfaces (CIs) was done in [2] to support physicians conducting occupational health consultations. The CI was developed with the help of a web-based information dashboard along with a chatbot assistant, which provides real-time recommendations. Two system designs were implemented in this paper. The first design was by using a proactive chatbot, and the other was by using an on-demand interaction. The limitation was that it was conducted using simulated medical cases, with limited participants, based on only one round of experiments. Hence, the results might not have been sufficient to demonstrate the effects of CIs in longterm routine in real occupational health consults. Analysis of two characteristics; language, and persona; and their effect on outcomes such as effectiveness, usability, and trust in a chatbot was carried out in [3]. Its disadvantage was the use of informal language for online counseling, a lack of trust in the information, or the chatbot being perceived as not having the correct information. The chatbot in [4] stores the information in the database to identify the keywords from the sentences and make a decision for the query and answer the question. A score is calculated for each sentence, and more similar sentences are obtained for the given query, from ISO 9001:2008 Certified Journal
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