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Full-Text Articles in Education
Enhanced Breast Cancer Tumor Classification Using Mobilenetv2: A Detailed Exploration On Image Intensity, Error Mitigation, And Streamlit-Driven Real-Time Deployment, Aaditya Surya, Aditya Keshary Shah, Subash Tarun Sasikumar, Jarnell Kabore
Enhanced Breast Cancer Tumor Classification Using Mobilenetv2: A Detailed Exploration On Image Intensity, Error Mitigation, And Streamlit-Driven Real-Time Deployment, Aaditya Surya, Aditya Keshary Shah, Subash Tarun Sasikumar, Jarnell Kabore
Butler Journal of Undergraduate Research
This research introduces a sophisticated transfer learning model based on Google’s MobileNetV2 for breast cancer tumor classification into normal, benign, and malignant categories, utilizing a dataset of 1576 ultrasound images (265 normal, 891 benign, 420 malignant). The model achieves an accuracy of 0.82, precision of 0.83, recall of 0.81, ROC-AUC of 0.94, PR-AUC of 0.88, and MCC of 0.74. It examines image intensity distributions and misclassification errors, offering improvements for future applications. Addressing dataset imbalances, the study ensures a generalizable model. This work, using a dataset from Baheya Hospital, Cairo, Egypt, compiled by Walid Al- Dhabyani and colleagues (2020), emphasizes …
Are You A Quantitative Or Qualitative Runner?: 5.13 Miles And Rosemary-Lilac Shampoo, Shelly Sheats Harkness
Are You A Quantitative Or Qualitative Runner?: 5.13 Miles And Rosemary-Lilac Shampoo, Shelly Sheats Harkness
Humanistic Mathematics Network Journal
No abstract provided.