Publications (12)
Persistent homology machine learning for fingerprint classification
Noah Giansiracusa, Robert Giansiracusa, Chul Moon
The fingerprint classification problem is to sort fingerprints into pre-determined groups, such as arch, loop, and whorl. It was asserted in the literature that minutiae points, wh…
Hypothesis Testing for Shapes using Vectorized Persistence Diagrams
Chul Moon, Nicole A. Lazar
Topological data analysis involves the statistical characterization of the shape of data. Persistent homology is a primary tool of topological data analysis, which can be used to a…
Using Persistent Homology Topological Features to Characterize Medical Images: Case Studies on Lung and Brain Cancers
Chul Moon, Qiwei Li, Guanghua Xiao
Tumor shape is a key factor that affects tumor growth and metastasis. This paper proposes a topological feature computed by persistent homology to characterize tumor progression fr…
A survival analysis of glioma patients using topological features and locations of tumors
Yuhyeong Jang, Tu Dan, Eric Vu +1
Tumor shape plays a critical role in influencing both growth and metastasis. We introduce a novel topological radiomic feature derived from persistent homology to characterize tumo…
Discovering Clinically Meaningful Shape Features for the Analysis of Tumor Pathology Images
Esteban Fernández Morales, Cong Zhang, Guanghua Xiao +2
With the advanced imaging technology, digital pathology imaging of tumor tissue slides is becoming a routine clinical procedure for cancer diagnosis. This process produces massive…
Spatial Analysis for AI-segmented Histopathology Images: Methods and Implementation
Yoolkyu Park, Fangjiang Wu, Xin Feng +6
Quantitative characterization of cellular spatial organization is critical for understanding tumor progression and immune response. Recent advances in artificial intelligence (AI)…
Enhancing Empathic Accuracy: Penalized Functional Alignment Method to Correct Temporal Misalignment in Real-time Emotional Perception
Linh H Nghiem, Jing Cao, Chrystyna Kouros +1
Empathic accuracy (EA) is the ability to accurately understand another person\textquotesingle s thoughts and feelings, which is crucial for social and psychological interactions. T…
Bayesian Elastic Net based on Empirical Likelihood
Chul Moon, Adel Bedoui
We propose a Bayesian elastic net that uses empirical likelihood and develop an efficient tuning of Hamiltonian Monte Carlo for posterior sampling. The proposed model relaxes the a…
Persistence Terrace for Topological Inference of Point Cloud Data
Chul Moon, Noah Giansiracusa, Nicole A. Lazar
Topological data analysis (TDA) is a rapidly developing collection of methods for studying the shape of point cloud and other data types. One popular approach, designed to be robus…
Bayesian Landmark-based Shape Analysis of Tumor Pathology Images
Cong Zhang, Guanghua Xiao, Chul Moon +2
Medical imaging is a form of technology that has revolutionized the medical field in the past century. In addition to radiology imaging of tumor tissues, digital pathology imaging,…
generalRSS: Sampling and Inference for Balanced and Unbalanced Ranked Set Sampling in R
Chul Moon, Soohyun Ahn
Ranked set sampling (RSS) is a stratified sampling method that improves efficiency over simple random sampling (SRS) by utilizing auxiliary information for ranking and stratificati…
Empirical Likelihood Inference for Area under the ROC Curve using Ranked Set Samples
Chul Moon, Xinlei Wang, Johan Lim
The area under a receiver operating characteristic curve (AUC) is a useful tool to assess the performance of continuous-scale diagnostic tests on binary classification. In this art…