Lung Cancer may be a variety of Cancer that begins in the Lungs because of those that smokes often. However, there Area unit rare probabilities those area unit non-smokers get Affected because of unhealthy pollution and Harmful gasses. The detection of tumor is incredibly vital that helps to detect affected neoplasm areas in the lungs. Computed tomography help us to understand the cancer positions in patients. The detection of cancer tumours are performed by scanning the images of computed tomography. Lung cancer identification system goes with a method of Morphological opening and Gray level co-occurrence matrix (GLCM) feature extraction and Normalized cross-correlation with patches Analysis. Lung cancer classification using Linear Discriminant Analysis (LDA) gives good results of Accuracy of 81.81%. Patch Analysis is a new method to find lung cancer.

This paper presents the Nano cavity Implementation of the biosensors in the detection of melanoma cancer tissue. The key challenge in the work is to provide the accuracy for the biosensors and the results are obtained. The developed design shows a path advancing field of medical aspects with the development of Nano plasmon technologies. The Surface Plasmon Resonance (SPR) technology is used, the concept depends on the refractive index of the selected slab layer. The refractive index material of the normal cancer by comparing it with the refractive index of the melanoma cancer tissue in order to know the tissue is cancerous are non-cancerous. Sensitivity for different sensor design is investigated. The overall highest sensitivity obtained is 300 nm/RIU for 1550 nm of wavelength.

Unstructured data is outcome of various major business applications. Summarizing unstructured data is considered as a significant task in this era of smart digital evolution. Text summarization is basically done using the common approaches on the basis of certain predefined rules. Text summarization is a branch of text mining which helps in bringing together the main content of the text from the original text or document. This work was an attempt to understand the existing literature and make a critical review on the pros and cons of the methods used. A gap analysis is also included after inspecting various methods. A comparative study of intrinsic and extrinsic evaluation techniques is included. A methodology is proposed for text summarization using machine learning.