About WBC Smart Lab
Everything white blood cell-related. Key features:
AI-Powered White Blood Cell Classifier:
Snap a photo directly through your microscope and the AI model will classify the white blood cell type. Save time, improve consistency, and get another opinion. 98% accuracy with our test set, may vary depending on lighting & microscope. Keep in mind that this should be used to aid, not make, your decision.
WBC Counter:
A user-friendly cell type counter for educational, lab and clinical use. Increment&decrement, haptics/vibration, save data, custom classes, and automatically calculate ratios.
Interactive Training Mode:
Practice identifying white blood cell type with high quality labeled sample images. Get immediate feedback and performance report, perfect for exam prep or training.
For instructors: contact me at knotgavin[at]gmail[dot]com to get an institutional account in order to assign and track student's performance.
Contact me at knotgavin[at]gmail[dot]com to provide feedback/suggestions! I'll try to constantly improve the model as more real world data is available.
Thanks to the Faculty of Allied Health Sciences, Chulalongkorn University for the dataset and support!
AI-Powered White Blood Cell Classifier:
Snap a photo directly through your microscope and the AI model will classify the white blood cell type. Save time, improve consistency, and get another opinion. 98% accuracy with our test set, may vary depending on lighting & microscope. Keep in mind that this should be used to aid, not make, your decision.
WBC Counter:
A user-friendly cell type counter for educational, lab and clinical use. Increment&decrement, haptics/vibration, save data, custom classes, and automatically calculate ratios.
Interactive Training Mode:
Practice identifying white blood cell type with high quality labeled sample images. Get immediate feedback and performance report, perfect for exam prep or training.
For instructors: contact me at knotgavin[at]gmail[dot]com to get an institutional account in order to assign and track student's performance.
Contact me at knotgavin[at]gmail[dot]com to provide feedback/suggestions! I'll try to constantly improve the model as more real world data is available.
Thanks to the Faculty of Allied Health Sciences, Chulalongkorn University for the dataset and support!
