A Prototype Software Framework for
Predicting Lung Cancer Treatment Outcomes

Lung Cancer Study at Mayo Clinic and
Computer Science at Winona State University

Zhang Mingrui, Liu Yingxu, Jiang Yichen, Sun Zhifu, Yang Ping, "Model based user interface design for predicting lung cancer treatment outcomes", Proceedings IEEE Eng Med Biol Soc. 2011:75-8. PMID: 22254254

We have developed a model based user interface design for integrating multiple statistical models into one software tool, and successfully implemented four prediction models of lung cancer treatments.

An illustration of a hypothetical scenario: a male patient diagnosed limited-stage small cell carcinoma at age 43.

To make the comparison of cancer treatments more convenient, checkboxes are used with the graph view of prediction results. Based on feedback from physicians, annotation is added to the graph view to help users interpret the survival probability accurately. As the user moves the cursor (or his/her finger tip on an iPhone) over the prediction graph, the survival probability is displayed as an annotation over the curve.

Gegg-Harrison Timothy, Zhang Mingrui, Meng Nan, Sun Zhifu, Yang Ping, "Porting a cancer treatment prediction to a mobile device", Proceedings IEEE Eng Med Biol Soc. 2009:6218-21. PMID: 19965083

A new interface is designed for mobile devices. We have addressed the issues display size along with wireless data transfer speeds by redefining the interface and limiting the amount of data that is required. The resultant tool provides doctors with the flexibility of mobility while maintaining the effectiveness of the desktop version. The prototype supports both desktop and mobile devices.