Selected Conference Presentations:
Kun-Hsing Yu, Ce Zhang, Gerald J. Berry, Russ B. Altman, Christopher Ré, Daniel L. Rubin, Michael Snyder, Isaac S. Kohane. Unraveling the Molecular Basis of Lung Adenocarcinoma Dedifferentiation and Prognosis by Integrating Omics and Histopathology. American Medical Informatics Association 2018 Annual Symposium; November 3-7, 2018; San Francisco, CA.
Kun-Hsing Yu, Tsung-Lu Michael Lee, Chi-Shiang Wang, Yu-Ju Chen, Christopher Ré, Samuel C. Kou, Jung-Hsien Chiang, Isaac S. Kohane, Michael Snyder. Systematic Protein Prioritization through Literature Mining. Human Proteome Organization (HUPO) World Congress; September 30-October 3, 2018; Orlando, FL.
Kun-Hsing Yu, Oren Miron, Nathan Palmer, Dario Lemos, Mustafa Sahin, Isaac Kohane. Data-Driven Analyses on a Nationwide Insurance Claims Dataset Revealed the Comorbidity Landscape of Tuberous Sclerosis Complex. American Medical Informatics Association 2018 Informatics Summit; March 12-15, 2018; San Francisco, CA.
William Yuan, Isaac S. Kohane, Kun-Hsing Yu. Integrative Transcriptome-Histopathology Analysis Revealed Insights into the Hormone Receptor Status of Breast Cancer Patients. American Medical Informatics Association 2018 Informatics Summit; March 12-15, 2018; San Francisco, CA.
Kun-Hsing Yu, Nathan Palmer, Isaac S. Kohane. Subtype Discovery for Autism Spectrum Disorder by Comorbidity Analysis. American Medical Informatics Association 2017 Annual Symposium; November 4-8, 2017; Washington, DC.
Kun-Hsing Yu, Gerald J. Berry, Russ B. Altman, Christopher Ré, Daniel L. Rubin, Michael Snyder. Deciphering Lung Adenocarcinoma Morphology and Prognosis by Integrating Omics and Histopathology. Pacific Symposium on Biocomputing; January 3-7, 2017; Big Island, HI.
Discovered the correlations between genomic aberrations and tumor cell morphology
Kun-Hsing Yu, Michael Fitzpatrick, Luke Pappas, Jessica Kung, Michael Snyder. Omics AnalySIs System for PRecision Oncology (OASISPRO): A Web-based Tool for Tumor Omics Analysis. American Medical Informatics Association 2016 Summit on Translational Bioinformatics; March 21-24, 2016; San Francisco, CA.
Built a general purpose data-mining tool for precision oncology
Kun-Hsing Yu, Douglas A. Levine, Hui Zhang, Daniel W. Chan, Zhen Zhang, and Michael Snyder. Predicting Ovarian Cancer Patients' Clinical Response to Platinum-based Chemotherapy by their Tumor Proteomic Signatures. United States Human Proteome Organization (HUPO). March 13-16, 2016; Boston, MA.
Predicted ovarian cancer patients' chemotherapy response by proteomic profiles
Kun-Hsing Yu, Ce Zhang, Gerald J. Berry, Russ B. Altman, Christopher Ré, Daniel L. Rubin, Michael Snyder. Understanding Non-Small Cell Lung Cancer Morphology and Prognosis by Integrating Omics and Histopathology. Pacific Symposium on Biocomputing; January 4-8, 2016; Big Island, HI.
Identified image features associated with different types of non-small cell lung carcinoma
Kun-Hsing Yu, Daniel L. Rubin, Michael Snyder. Understanding Lung Adenocarcinoma Morphology and Prognosis by Integrating Omics and Histopathology. American Society of Human Genetics Annual Meeting. October 6-10, 2015; Baltimore, MD.
Correlated quantitative image features associated with lung adenocarcinoma survival
Kun-Hsing Yu, Daniel L. Rubin, Michael Snyder. Integrating Omics and Histopathology Profiles to Identify Novel Subtypes of Lung Adenocarcinoma. 2015 Big Data in Biomedicine Conference. May 20-22, 2015; Stanford, CA.
Integrated omics and histopathology data to predict survival outcomes of lung adenocarcinoma patients
Kun-Hsing Yu, Wei Wang, Chung-Yu Wang, Michael Snyder. Predicting Papillary Thyroid Carcinoma Patient Outcomes through Gene Expression Data. American Medical Informatics Association 2015 Summit on Translational Bioinformatics; March 23-27, 2015; San Francisco, CA.
Established a prediction model for the prognosis of papillary thyroid carcinoma patients
Kun-Hsing Yu, Daniel L. Rubin, Mark F. Berry, Michael Snyder. Integrating Omics and Histopathology Profiles to Identify Novel Subtypes of Lung Adenocarcinoma. Pacific Symposium on Biocomputing; January 4-8, 2015; Big Island, HI.
Spearheaded an integrative study on the transcriptomics, proteomics and histopathology image features of lung adenocarcinoma
Kun-Hsing Yu, Wei Wang, Chung-Yu Wang, Michael Snyder. Identifying Thyroid Carcinoma Subtypes and Outcomes through Gene Expression Data. Paper presented at: Biomedical Computation at Stanford (BCATS) 14th Annual Symposium; January 30, 2014; Stanford, CA.
Discovered biomarkers for tumor stages and prognoses of thyroid cancer patients
Kun-Hsing Yu, Shanshan Tuo, Daniel Rubin. Classifying Benign and Malignant Lung Diseases by Applying Machine Learning Methods to Microscopic Pathology Images. Paper presented at: American Medical Informatics Association 2013 Annual Symposium; November 16-20, 2013; Washington DC.
Designed and developed an automated system for histopathology diagnosis and prognosis
Chia-Li Han, Jinn-Shiun Chen, Err-Cheng Chan, Chien-Peng Wu, Kun-Hsing Yu, Chia-Feng Tsai, Guei-Tien Chen, Chih-Wei Chien, Yung-Bin Kuo, Pei-Yi Lin, Jao-Song Yu, Yu-Ju Chen. Proteomics: Case Study on Colorectal Cancer. Paper presented at: 58th ASMS Conference on Mass Spectrometry and Allied Topics; May 23-27, 2010; Salt Lake City, Utah.
Identified colorectal cancer markers through bioinformatics methods
Ming-Jung Ho, Kun-Hsing Yu, Hui Pan, Jessie L. Norris, You-Sin Liang, Jia-Ning Li, David Hirsh. A Tale of Two Cities: Understanding Constructs of Medical Professionalism in Two Chinese Cultural Contexts. The First Annual Social Science Fair; May 23, 2014; Stanford, CA.
Built a data mining pipeline for quantitative information and won the Second Prize of the Best Poster Award
Kun-Hsing Yu, Ming-Jung Ho, David Hirsh, Tien-Shiang Huang, Pan-Chyr Yang. Does One Size Fit All? – Building a Framework for Medical Professionalism. Paper presented at: Flexner Report Centennial International Conference; October 24-25, 2010; Taipei, Taiwan.
Conceptualized the professionalism framework and won the Best Poster Award