https://github.com/killervardhan8/adr-net

ADR-Net implements a simple case study on detecting Adverse Drug Reactions (ADRs) using Artificial Neural Networks (ANN) and Latent Semantic Analysis (LSA). This simple project includes tools for analyzing ADR data with LSA to uncover patterns and evaluates model accuracy with F-Scores.
https://github.com/killervardhan8/adr-net

lsa neural-networks python statistics

Last synced: 29 days ago
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ADR-Net implements a simple case study on detecting Adverse Drug Reactions (ADRs) using Artificial Neural Networks (ANN) and Latent Semantic Analysis (LSA). This simple project includes tools for analyzing ADR data with LSA to uncover patterns and evaluates model accuracy with F-Scores.

• Host: GitHub
• URL: https://github.com/killervardhan8/adr-net
• Owner: KillerVardhan8
• Created: 2024-05-10T18:15:44.000Z (8 months ago)
• Default Branch: main
• Last Pushed: 2024-08-21T09:47:36.000Z (5 months ago)
• Last Synced: 2024-08-21T11:04:26.333Z (5 months ago)
• Topics: lsa, neural-networks, python, statistics
• Language: Python
• Homepage:
• Size: 2.88 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Adverse Drug Reaction-Neural Networks(ADR-Net)

Case Study Implementation of the Research Paper [here](https://github.com/KillerVardhan8/ADR-Net/blob/75a018eaa65d0eeae52f7dbd95624af6dfd67b41/Research%20Paper%20(ANN%20and%20LSA%20for%20Adverse%20Drug%20Reaction%20Detection)%20.pdf) which deals about **Artificial Neural Networks** and **Latent Semantic Analysis** for **Adverse Drug Reaction Detection** related to **Neuro Fuzzy and Genetic Programming** subject.

## ADR Test

The "ADR Test" file uses Latent Semantic Analysis (LSA) to analyze user-reported Adverse Drug Reactions (ADRs). This file identifies hidden patterns and associations in the text, helping to better understand user experiences with various drugs.

## Accuracy

The "Accuracy" file compares the performance of the LSA model with other machine learning models using F-Scores. It evaluates which model is most accurate in predicting ADRs, ensuring the best approach for analyzing user-reported data.

## Research Paper Analysis 

[click here](https://github.com/KillerVardhan8/ADR-Net/blob/bdcdcf257c12d31c8ce57ead71e42d1a53fd457e/Research%20Paper%20Analysis.docx)

## The Implementation Video link 

[click here](https://drive.google.com/file/d/1hWk4WMLnd92T8bFem4kTt2VRh0OuWEb4/view?usp=sharing)