Lung cancer prognosis system using data mining techniques

This paper describes a Lung Cancer Prognosis System (LCPS) that aims at providing oncologists with an accurate estimate of the health status of their patients. The proposed system is born from two observations: First, lots of efforts are still required in healthcare to improve productivity, accuracy, etc. by providing ad hoc computer-based solutions; second, while increasing popular, AI and data mining tools cannot be used without significant training and expertise. LCPS thus aims at providing the former by integrating the latter into a user-friendly tool, supplementing the knowledge of the expert oncologist with information about their patients, and leading to improved patient care and treatments. LCPS can accept a variety of lung cancer datasets and employs several data mining algorithms to uncover relationships between observed health signs and probable outcomes, and provides oncologists with various statistical results including predictions about their patients’ medical future. Furthermore, LCPS makes it easy to manage patients’ records, allows them view their profiles and any information as deemed suitable by their doctor, including prognosis and other comments. Lastly, while the current application is currently limited to lung cancer treatment, it can be considered a prototype that can be adapted to other diseases.