Bioinformatics Solutions for Image Data Processing

In recent years, the increasing use of medical devices has led to the generation of large amounts of data, including image data. Bioinformatics solutions provide an effective approach for image data processing in order to retrieve information of interest and to integrate several data sources for knowledge extraction; furthermore, images processing techniques support scientists and physicians in diagnosis and therapies. In addition, bioinformatics image analysis may be extended to support several scenarios, for instance, in cyber-security the biometric recognition systems are applied to unlock devices and restricted areas, as well as to access sensitive data. In medicine, computational platforms generate high amount of data from medical devices such as Computed Tomography (CT), and Magnetic Resonance Imaging (MRI); this chapter will survey on bioinformatics solutions and toolkits for medical imaging in order to suggest an overview of techniques and methods that can be applied for the imaging analysis in medicine

Useful Datasets and Very Recent Approach for Melanoma Image Classification.

The growing incidence of skin cancers, coupled with low awareness among the population fuels interest in developing computer-assisted diagnostics solutions for skin cancer classification. A large number of data sets on skin lesions are publicly available and researchers have developed machine learning solutions to distinguish Malignant from benign skin lesions aimed both to support the doctors and as mobile applications useful in self-diagnosis. The Computer Aided Diagnosis (CAD) systems are still in the very early stages of clinical application: in this review, we focus on the latest approaches used for image-based solutions for skin cancer diagnosis, highlighting the necessary future directions to improve these artificial intelligence systems

Declarative Semantics for Consistency Maintenance

Dipartimento di Elettronica, Informatica e Sistemistica, Dottorato di Ricerca in Ingegneria dei Sistemi e Informatica, Ciclo XX, a.a. 2007Università della Calabri

IOS Press Collaborative Filtering Supporting Web Site Navigation

Abstract. The proliferation of information available on the world wide web and the new emerging technologies that have reduced the barriers in organizing and publishing documents, have made the support for navigation and personalization of web sites an appealing and promising task for the AI community. Making the process of retrieving relevant documents easier is one of the most challenging activities in the design of modern sites and goes beyond any particular domain. This paper proposes a new technique for Web navigation based on current algorithms used in Recommendation Systems. Our approach identifies really relevant documents adopting methodologies similar to those successfully used in current search engines. The effectiveness and the validity of our technique have been shown by several experiments