Cancer Detection using Machine Learning (YOLOV8)

Cancer Detection Yolov8

1. Skin Cancer Detection 1

2. Project Overview 2 Objective: Develop a tool for detecting and classifying potential skin cancer lesions from images using YOLOv8. Tools Used: YOLOv8, Gradio , OpenAI API

3. Dataset 3 Dataset Link: https://www.isic-archive.com/ Malignant Benign Dataset: Skin lesion images Annotation: Annotations for training YOLOv8 model

4. Model Training 4 Base Model: YOLOv8 small model (yolov8s.pt) Training Command: yolo task=detect mode=train model=yolov8s.pt data= data.yaml epochs=50 imgsz =320 plots=True

5. Training Results 5

6. Validation Results 6

7. Confusion Matrix 7

8. Prediction Results 8

9. Gradio Interface 9

10. Gradio Interface 10

11. Gradio Interface 11

12. Use References 12 https://www.isic-archive.com/ https://my.clevelandclinic.org/health/diseases/22121-benign-tumor https://ieeexplore.ieee.org/abstract/document/9445249/ You can use these websites:

13. Thank you & Welcome 13