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@article{180791,
        author = {Tamboli Owaiz and Junaid Shaikh and Zakriya Mulla and Sawant Anil},
        title = {Healthcare prediction system Using IOT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {2446-2452},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180791},
        abstract = {Disease prediction of a human means 
predicting the probability of a patient’s disease after 
examining the combinations of the patient’s symptoms. 
Monitoring a patient's condition and health 
information at the initial examination can help doctors 
to treat a patient's condition effectively. This analysis 
in the medical industry would lead to a streamlined 
and expedited treatment of patients. The previous 
researchers have primarily emphasized machine 
learning models mainly Support Vector Machine 
(SVM), K-nearest neighbors (KNN), for the detection 
of 
diseases with the symptoms as parameters. 
However, the data used by the prior researchers for 
training the model is not transformed and the model is 
completely dependent on the symptoms, while their 
accuracy is poor. Nevertheless, there is a need to 
design a modified model for better accuracy and early 
prediction of human disease. The proposed model has 
improved the efficacy and accuracy model, by 
resolving the issue of the earlier researcher’s models. 
The proposed model is using the medical dataset from 
Kaggle and transforms the data by assigning the 
weights based on their rarity. This dataset is then 
trained using a combination of machine learning 
algorithms: Random Forest, Long Short-Term 
Memory (LSTM), and SVM. Parallel to this, the 
history of the patient can be analyzed using LSTM 
Algorithm. SVM is then used to conclude, the possible 
disease. The proposed model has achieved better 
accuracy and reliability as compared to state-of-the
art methods. The proposed model is useful to 
contribute towards development in the automation of 
the healthcare industries.},
        keywords = {AI chatbot, healthcare, natural language  processing, rural healthcare, appointment booking,  IOT enabled.},
        month = {June},
        }