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
Egyptian drug database (May 2026) — 24,868 medicines with Arabic + English trade names, scientific composition, manufacturer, drug class, route, and EGP price. CSV + JSON. CC0. قاعدة بيانات الأدوية المصرية
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.
串接藥品檔+外觀檔+健保規範+仿單
Implementation of Drug database with LinearSVC, BernoulliNB, MultinomialNB, LogisticRegression, Perceptron and MLPClassifier models
26K+ Egyptian drugs dataset with active ingredients, FDA mapping, Arabic drug information, prices, barcodes, and medical warning flags.
Open data packs for Vitatheca — offline reference for foods and medications. Aggregated SQLite databases from USDA, EFSA, EMA, openFDA, WHO, DrugBank, RxNorm.
Automated pipeline for extracting drug safety information from FDA Structured Product Labels (SPL) using NLP and MedDRA mapping for pharmacovigilance research.
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
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