Breast cancer has the second highest frequency of death rate among women worldwide. Early-stage prevention becomes complex due to reasons unknown. However, some typical signatures like masses and micro-calcifications upon investigating mammograms can help diagnose women better. Manual diagnosis is a hard task the radiologists carry out frequently. For their assistance, many computer-aided diagnosis (CADx) approaches have been developed. To improve upon the state of the art, we proposed a deep ensemble transfer learning and neural network classifier for automatic feature extraction and classification. In computer-assisted mammography, deep learning-based architectures are generally not trained on mammogram images directly. Instead, the images are pre-processed beforehand, and then they are adopted to be given as input to the ensemble model proposed. The robust features extracted from the ensemble model are optimized into a feature vector which are further classified using the neural network (nntraintool). The network was trained and tested to separate out benign and malignant tumors, thus achieving an accuracy of 0.88 with an area under curve (AUC) of 0.88. The attained results show that the proposed methodology is a promising and robust CADx system for breast cancer classification. Graphical Abstract Flow diagram of the proposed approach. Figure depicts the deep ensemble extracting the robust features with the final classification using neural networks.
Evaluation of the Safety and Efficacy of Immunotherapy Rechallenge in Patients With Renal Cell Carcinoma
November 6, 2020
Anti-tau scFvs Targeted to the Cytoplasm or Secretory Pathway Variably Modify Pathology and Neurodegenerative Phenotypes.
November 2, 2020
March 9, 2020
- ASCO – Lung CancerASCO.20 Virtual Scientific Program, held May 29 - 31, brought professionals from all over the world together to hear the brightest minds in oncology present state-of-the-art treatment modalities and new therapies.
- AACR-2020The American Association for Cancer Research is the world's oldest and largest professional association related to cancer research.
- ACC 2020The American College of Cardiology decided to cancel ACC.20/WCC due to COVID-19, which was scheduled to take place March 28-30 in Chicago. However, ACC.20/WCC Virtual Meeting continues to release cutting edge science and practice changing updates for cardiovascular professionals on demand and free through June 2020.
- ASCO 2019The 2019 ASCO Annual Meeting, taking place May 31-June 4 in Chicago, will bring together more than 32,000 oncology professionals from across the globe. The theme of this year’s conference is Caring for Every Patient, Learning From Every Patient.