AltayBioAI-BloodCell-ResNet18-V2
A ResNet18-Based Deep Learning Model For Human Blood Cell Classification Using PyTorch.
Model Overview
AltayBioAI-BloodCell-ResNet18-V2 Is A Biomedical Computer Vision Model Designed To Classify Human Blood Cell Images Into Four Categories.
The Model Is Built Using ResNet18 And Implemented With PyTorch As Part Of The AltayBioAI Collection, An Open-Source Initiative Focused On Biomedical Artificial Intelligence, Medical Imaging, And Deep Learning.
Model Details
| Property | Value |
|---|---|
| Model Name | AltayBioAI-BloodCell-ResNet18-V2 |
| Architecture | ResNet18 |
| Framework | PyTorch |
| Task | Image Classification |
| Domain | Medical Imaging |
| Number Of Classes | 4 |
| License | MIT |
Classes
The Model Classifies The Following Types Of Human Blood Cells:
- Eosinophil
- Lymphocyte
- Monocyte
- Neutrophil
Dataset
Blood Cells Dataset
Source: Kaggle
Dataset Link:
https://www.kaggle.com/datasets/paultimothymooney/blood-cells
Training Configuration
| Parameter | Value |
|---|---|
| Epochs | 5 |
| Training Time | Approximately 20 Minutes |
| Training Platform | Google Colab |
Performance
| Metric | Value |
|---|---|
| Accuracy | 68.68% |
Increasing The Number Of Training Epochs May Improve Model Performance.
Technologies
- PyTorch
- Torchvision
- ResNet18
- KaggleHub
- Google Colab
- Jupyter Notebook
Model File
File Name
blood_cell_resnet18.pth
Repository Contents
- Google Colab Notebook
- Jupyter Notebook
- Python Script
- Requirements File
- Project Information File
- Dataset Sample Images
- Prediction Result Images
Intended Use
This Model Is Intended For:
- Biomedical Artificial Intelligence Research
- Medical Image Classification
- Deep Learning Education
- Computer Vision Research
- Academic And Experimental Projects
Limitations
- Trained For Five Epochs.
- Performance May Improve With Additional Training.
- Evaluated Using A Public Dataset.
- Not Evaluated In Clinical Environments.
Notes
The Trained Model Is Distributed Through Release Assets To Keep The Repository Lightweight.
The Google Colab Version Was Used For Training And Evaluation.
The Jupyter Notebook And Python Script Versions Provide Equivalent Implementations For Local Execution.
This Project Is Designed To Remain Accessible For CPU And Google Colab Users.
Disclaimer
This Model Is Intended For Educational And Research Purposes Only.
It Is Not Intended For Clinical Diagnosis, Medical Decision-Making, Or Any Real-World Healthcare Application.
Medical Decisions Should Always Be Made By Qualified Healthcare Professionals.
License
This Project Is Released Under The MIT License.
You Are Free To Use, Modify, And Distribute This Model Under The Terms Of The MIT License.
About AltayBioAI
AltayBioAI Is An Open-Source Collection Of Biomedical Artificial Intelligence Projects Focused On:
- Medical Imaging
- Deep Learning
- Computer Vision
- Computational Biology
- Artificial Intelligence For Healthcare
The Goal Of AltayBioAI Is To Develop Accessible, Educational, And Research-Oriented AI Models For The Biomedical Community.
Developed By AliSolaxay35