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Full-Text Articles in Medicine and Health Sciences
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 …
Our Histories, Our Horizons: A Letter To Our Readers
Our Histories, Our Horizons: A Letter To Our Readers
Akesis
Volume 5, Issue 1 marks a new chapter in the history of our narrative medicine journal as we realize an important goal of Akesis—establishing a foothold on the Portland campus of UNE. Our hope is that Akesis becomes a familiar name among students, faculty, and staff, and that our call for submissions and issue publications are events everyone anticipates and enjoys. This issue also welcomes six new editors to Akesis, students representing a diverse sampling of UNE’s graduate and professional programs from both campuses. The success of this issue’s call for submissions is due to the efforts of …