SDLDpred is a web-based tool to predict drugs of lifestyle-related diseases using symptoms as features. It uses an unsupervised machine learning model trained using Bisecting K-Means algorithm to perform the prediction. The model was trained with disease-symptom and drug-disease association data of 143 lifestyle-related diseases, 1271 drugs and 305 symptoms. To know more about SDLDpred, go to About page. For help, please refer to Help page.

Cite as: Bhattacharjee, S., Saha, B., & Saha, S. (2024). Symptom-based drug prediction of lifestyle-related chronic diseases using unsupervised machine learning techniques. Computers in Biology and Medicine, 174, 108413. https://doi.org/10.1016/j.compbiomed.2024.108413

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	Symptom	Symptom intensity (0-10)

More symptoms can be added by clicking on the "Add symptom" button below. To delete symptoms, first select the checkbox for the symptoms to be deleted and, then, click on "Delete symptom" button below. Symptom intensity can be in the range 0-10, where 10 indicates severest symptom.
Add symptom	Delete symptom
	Reset

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Please contact Dr. Sudipto Saha (ssaha4@jcbose.ac.in, ssaha4@gmail.com) regarding any further queries.