In this paper, we have presented a novel deep neural network architecture involving transfer learning approach, formed by freezing and concatenating all the layers till block4 pool layer of VGG16 pre-trained model (at the lower level) with the layers of a randomly initialized nave Inception block module (at the higher level). Further, we have added the batch normalization, flatten, dropout and dense layers in the proposed architecture. Our transfer network, called VGGIN-Net, facilitates the transfer of domain knowledge from the larger ImageNet object dataset to the smaller imbalanced breast cancer dataset. To improve the performance of the proposed model, regularization was used in the form of dropout and data augmentation. A detailed block-wise fine tuning has been conducted on the proposed deep transfer network for images of different magnification factors. The results of extensive experiments indicate a significant improvement of classification performance after the application of fine-tuning. The proposed deep learning architecture with transfer learning and fine-tuning yields the highest accuracies in comparison to other state-of-the-art approaches for the classification of BreakHis breast cancer dataset. The articulated architecture is designed in a way that it can be effectively transfer learned on other breast cancer datasets.

Background: In the last few decades, it has been largely perceived that the factors affecting the immune system and its varying pathways lead to the pathological progression of inflammation and inflammatory conditions. Chronic inflammation also contributes to common diseases, such as diabetes mellitus, ischemic heart disease, cancer, chronic renal inflammatory disease, non-alcoholic fatty hepat-ic disease, autoimmune diseases and neurodegenerative diseases. Objective: Interestingly, plant sources and secondary metabolites from plants have been increasingly employed in managing acute and chronic inflammatory diseases for centuries. Boswellic acids are pentacyclic triterpenoidal moieties obtained from the oleo gum resin of different Boswellia species. Methods: Detailed data was collected revealing the anti-inflammatory potential of Boswellic acids through various databases. Results: These are pharmacologically active agents that possess promising anti-inflammatory, anti-arthritic, antirheumatic, anti-diarrheal, anti-hyperlipidemic, anti-asthmatic, anti-cancer, and anti-microbial effects. Conclusion: Boswellic acids have been in use since ancient times primarily to treat acute and chronic inflammatory diseases. This review discusses the various mechanisms underlying the inflammatory process and the necessity of such natural products as a medication to treat inflammatory diseases. In addition, a discussion has also been extended to understand the primary targets involved in inflamma-tion. The review further explores the therapeutic potential of boswellic acids in