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Class imbalanced datasets are common in real-world applications that range from credit card fraud detection to rare disease diagnostics. Several popular classification algorithms assume that classes are approximately balanced, and hence build the accompanying objective function to maximize an overall accuracy rate. In these situations, optimizing the overall accuracy will lead to highly skewed predictions towards the majority class. Moreover, the negative business impact resulting from false positives (positive samples incorrectly classified as negative) can be detrimental. Many methods have been proposed to address the class imbalance problem, including methods such as oversampling, under-sampling and cost-sensitive methods. In this paper, we consider the over-sampling method, where the aim is to augment the original dataset with synthetically created observations of the minority classes. In particular, inspired by the recent advances in generative modelling techniques (e.g., Variational Inference and Generative Adversarial Networks), we introduce a new oversampling technique based on variational autoencoders. Our experiments show that the new method is superior in augmenting datasets for downstream classification tasks when compared to traditional oversampling methods.

Cancer refers to a collective group of diseases involving abnormal, uncontrolled cell proliferation with the potential to spread to the other tissues from the location of origin. Various modes of treatments such as radiotherapy, chemotherapy, surgical methods, etc. are commonly available. However, these approaches are not very cost-effective and are accompanied by side effects. An emerging approach of targeted drug delivery or smart drug delivery with the assistance of nanoparticles (NPs) and also in combination with immunological therapies has proven to show great potential in cancer treatment with an additional advantage of having the least side effects. Stimulus-sensitive smart nanomaterials have been designed to specifically target the cancer cells, causing no damage to the healthy cells. This is attained using Poly (lactic-co-glycolic acid) (PLGA), PEGylated NPs, αvβ3-integrin-specific lipid NPs, NP-based radiosensitizers (NBRs), and NP drones. Moreover, not only the specific targeting but the advances allow the detection of these drug-loaded NPs with the help of plasmonic Biosensor and fluorescence nanoprobes that emits fluorescence as it comes in contact with the target. This article describes the application of NPs in targeting the tumor cells as well as the recent researches going on to facilitate easier & cheaper modes of treatment using nanotechnology.

Tissue engineering (TE) for skin grafting, also known as skin tissue engineering (STE) is a strategy involving the generation of artificial skin by using widely available natural or synthetic materials as substitutes that resemble the native skin i.e., it involves in-vitro fabrication of the biocompatible scaffolds. Earlier the skin grafting needed a healthy donor making the therapy limited due to the chances of immune rejection. Besides this, skin grafting may often result in poor healing in diabetic patients and bleeding problems in the individuals suffering from hemophilia. It may often result in infection of either the donor or the recipient at transplantation site. The emergence of novel methods of TE has overcome the limitations associated with the conventional methods. Various tissues and organs like the heart, skin, lung, liver, cartilage, etc, can be regenerated using TE. TE can be facilitated with the aid of nanotechnology for the generation of scaffolds due to various properties it possess, of which, the major advantageous property involves a large surface area to volume ratio to serve wider range function as well as antimicrobial properties to prevent infections near the damaged area. Often, the different types of stem cells can be used for tissue repairing, due to their self-renewable properties. The skin mimics are often prepared using 3-dimensional bioprinting. This review deals with the applications of TE in skin grafting, typically by manipulation of naturally available materials.

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