Machine Learning in Cancer
Informatics
Prof Dr. Abdel-Badeeh M. Salem
Head of BioMedical Informatics and Knowledge
Engineering Research Lab, Faculty of Computer and Information sciences,
Ain Shams University, Abbasia, Cairo-Egypt.
Abstract
<![if !vml]>
<![endif]>pathology,
radiology, computational biology, physical chemistry, computer science,
information systems biostatistics, machine learning, artificial
intelligence, data mining and many others. Machine learning (ML) offers
potentially powerful tools, intelligent methods, and algorithms that can help
in solving many medical and biological problems. The variety of ML algorithms
enable the design of a robust techniques and new methodologies for managing,
representing, accumulating, changing ,discovering ,and updating knowledge in
cancer-based systems. Moreover it supports learning and understanding the
mechanisms that will help oncologists, radiologists and pathologists to induce
knowledge from cancer information database.
This paper presents the application of
machine learning techniques in cancer informatics. The paper describes the
following applications; (a) Case-Based Reasoning for diagnosis
of cancer diseases ,(b) Ontological engineering for lung and breast
cancer knowledge management, (c) data mining for assessing diagnosis of
breast cancer, and(d) genetic algorithms based classifier for breast cancer
disease. In addition the talk discusses several directions for future.