Project Team
Students
Tianjie Chen
Computer Science
Penn State Harrisburg
Faculty Mentors
Md Faisal Kabir
Penn State Harrisburg
School Of Science, Engineering, And Technology
Soundar Kumara
Penn State University Park
College of Engineering
Project
Project Video
Project Abstract
Early diagnosis and prognostication of cancer have significant impact on patients’ survival chances. This requirement led to the search for efficient solutions, including machine learning (ML). Many studies have proved ML methods are a reliable choice in the medical field. However, current ML studies mainly focus on either diagnosis or prognostication, with few on combining both. Hence, we propose a ML model that integrates both cancer diagnosis and prognostication. First, we constructed a classification model and a regression model based on hyperparameter searches using k-fold cross validation. Next, we evaluated the performance of both models on RNA-seq data of prostate cancer. Last, we built a link that connects the classifier and the regressor. The result model shows strong performance in diagnosing and prognosticating while eliminating manual data transfer processes. The proposed model shows a promising start in making cancer diagnosis and prognostication more efficient.
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