This is an innovative machine learning project that utilizes patient reviews with many other attributes to analyze and evaluate the effectiveness of drugs.
A molecular docking pipeline for the drug database against SARS-CoV2
Visualized medication plan on a Raspberry Pi 3
This Python script scrapes drug-related information from the "Talk to Frank" website and saves the extracted data in both JSON and YAML formats. It utilizes the `requests` library to fetch the webpage, `BeautifulSoup` for HTML parsing, and `json` and `yaml` libraries for data storage.
Implementation of Drug database with LinearSVC, BernoulliNB, MultinomialNB, LogisticRegression, Perceptron and MLPClassifier models
A molecular docking pipeline for the drug database against SARS-CoV2
AI-powered medicine database and drug interaction checker with Indian medicines and mental health focus
Automated pipeline for extracting drug safety information from FDA Structured Product Labels (SPL) using NLP and MedDRA mapping for pharmacovigilance research.
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