Popular GitHub Repositories for Drugs

Analyzing the Drugs Descriptions, conditions, reviews and then recommending it using Deep Learning Models, for each Health Condition of a Patient.

PlaNet: Predicting population response to drugs via clinical knowledge graph

Pytorch implementation of Pocket2Drug: a generative deep learning model to predict binding drugs for ligand-binding sites.

Drug Repurposing using TigerGraph and Graph Machine Learning.

A collection of deep reinforcement learning-based & GFlowNet drug molecule generators focused on generation of molecules using Graphs/SELFIES guided by modern retrosynthesis tools to increase synthetic accessibility of de-novo designed drugs.

Named Entity Recognition for Disorder, Species, Chemical or Drug, Gene and Protein, Enzyme, Anatomy, Biological Process, Molecular Function, Cellular Component, Pathway and microRNAs.

MediVirtuoso ChatBot: An intelligent conversational agent powered by Google's Gemini LLM, featuring image recognition for drugs and medicines. Engage in natural language conversations, make queries, and explore the world of pharmaceuticals seamlessly with its user-friendly interface built on Streamlit

OpioidRL is a cutting-edge reinforcement learning (RL) library that simulates drug addiction behaviors within RL agents. Inspired by the addictive properties of drugs like methamphetamine and crack cocaine, OpioidRL offers a unique environment where agents experience reward dependency, high-risk decision-making, and compulsive behaviors — pushing

Analyzing the Drugs Descriptions, conditions, reviews and then recommending the medicines for each Health Condition of a Patient.

Analyzing psychedelic trip reports for predictive modeling and harm reduction and creating a trip report generator

This Python script is designed to provide detailed information on interactions between drugs and genes using the Sydney module for natural language processing and the Drug Gene Interaction Database (DGIdb) API. Users can input the names of three drugs separated by commas and receive information on the interactions with the corresponding genes.

the aim of this project is to extract precise information such as drugs, treatments,... from typed or handwritten prescriptions and medical records

Electrophysiology Chemical Drug Signal Identification, Fentanyl data...

using a pretrained ML model to identify and extract named entities (drugs and dosage) from a medical corpus of clinical text

search and download papers on specific drugs(SMILES format). Then building Pinecone vector database which can be used a rag pipeline. Where you can build a command line interface for clients wanting to talk to the vector database

Using biological and lifestyle data on Machine learning models to predict the type and severity of drug use in individuals.