Journal Publications:

  • Jin, Y. Luo, S. Eksioglu, “Integration of Production Sequencing and Outbound Logistics in the Automotive Industry", International Journal of Production Economics, 2008, 113(2):766-774. DOI: 10.1016/j.ijpe.2007.11.003.
  • Luo, F. Szidarovszky, Y. Al-Nashif, S. Hariri, “Game Theory Based Network Security", Journal of Information Security, 2010, 1:41-44. DOI: 10.4236/jis.2010.11005.
  • Luo, F. Szidarovszky, Y. Al-Nashif, S. Hariri, “A Fictitious-Play Based Response Strategy for Multi-Stage Intrusion Defense Systems", Security and Communication Networks, 2014, 7(3):473-491. DOI: 10.1002/sec.730.
  • Luo, S. Miller, “A Game Theory Analysis of Market Incentive for US Switchgrass Ethanol", Ecological Economics, 2013, 93:42-56. DOI: 10.1016/j.ecolecon.2013.04.015.
  • Szidarovszky, Y. Luo, “Incorporating Risk Seeking Attitude into Defense Strategy", Reliability Engineering and System Safety, 2014, 123:104-109. DOI: 10.1016/j.ress.2013.11.002.
  • Zhang, X. Heng, Y. Luo, Q. Fu, Z. Li, F. Che, B. Li, “Influence of Negative Lymph Node in No 7 on Survival of Patients with Middle Thoracic Esophageal Squamous Cell Carcinoma", OncoTargets and Therapy, 2016, 9:1831-1837. DOI: 10.2147/OTT.S94236.
  • Luo, S. Miller, “Using Game Theory to Resolve the `Chicken and Egg' Situation in Promoting Cellulosic Bioenergy Development", Ecological Economics, 2017, 135:29-41. DOI: 10.1016/j.ecolecon.2016.12.013.
  • Luo, I. El Naqa, D. McShan, D. Ray, I. Lohse, M. Matuszak, D. Owen, S. Jolly, T. Lawrence, F-M. Kong, R. Ten Haken, “Unraveling Biophysical Interactions of Radiation Pneumonitis in Non-Small-Cell Lung Cancer via Bayesian Network Analysis", Radiotherapy and Oncology, 2017, 123(1):85-92. DOI: 10.1016/j.radonc.2017.02.004.
  • El Naqa, S. Kerns, J. Coates, Y. Luo, C. Speers, C. West, B. Rosenstein, R. Ten Haken, “Radiogenomics and Radiotherapy Response Modeling", Physics in Medicine and Biology, 2017, 62(16):179-206. DOI: 10.1088/1361-6560/aa7c55.
  • Tseng, Y. Luo, S. Cui, J. Chien, R. Ten Haken, I. El Naqa, “Deep Reinforcement Learning for Automated Dose Adaptation in Lung Cancer", Medical Physics, 2017, 44(12):6690-6705. DOI: 10.1002/mp.12625.
  • Zhang, Y. Liu, F. Che, Y. Luo, W. Huang, X. Heng, B. Li, “Pattern of Lymph Node Metastasis in Thoracic Esophageal Squamous Cell Carcinoma with Poor Differentiation", Molecular and Clinical Oncology, 2018, 8(6):760-766. DOI: 10.3892/mco.2018.1606.
  • Luo, D. McShan, D. Ray, M. Matuszak, S. Jolly, T. Lawrence, F-M. Kong, R. Ten Haken, I. El Naqa, “A Multi-Objective Bayesian Networks Approach for Joint Prediction of Tumor Local Control and Radiation Pneumonitis in Non-Small-Cell Lung Cancer (NSCLC) for Response-Adapted Radiotherapy", Medical Physics, June 2018, 45(8):3980-3995. DOI: 10.1002/mp.13029.
  • Tseng, Y. Luo, R. Ten Haken, I. El Naqa, “The Role of Machine Learning in Knowledge-based Response-adapted Radiotherapy", Frontiers in Oncology, section Radiation Oncology, July 2018, 8, Article 266. DOI: 10.3389/fonc.2018.00266.
  • Tseng, L. Wei, S. Cui, Y. Luo, R. Ten Haken, I. El Naqa, “Machine Learning and Imaging Informatics in Oncology", Oncology, November 2018, 23:1-19. DOI: 10.1159/000493575.
  • Zhang, X. Heng, Y. Luo, L. Li, H. Zhang, F. Che, B. Li, “Negative Lymph Node at Station 108 Is a Strong Predictor of Overall Survival in Esophageal Cancer", Oncology Letters, September 2018, 16:6705-6712. DOI: 10.3892/ol.2018.9456.
  • Luo, D. McShan, D. Ray, M. Matuszak, S. Jolly, T. Lawrence, F-M. Kong, R. Ten Haken, I. El Naqa, “Development of a Fully Cross-Validated Bayesian Network Approach for Local Control Prediction in Lung Cancer", IEEE Transactions on Radiation and Plasma Medical Sciences, March 2019, 3(2):232-241. DOI: 10.1109/TRPMS.2018.2832609.
  • Cui, Y. Luo, H. Tseng, R. Ten Haken, I. El Naqa, “Artificial Neural Network with Composite Architectures for Prediction of Local Control in Radiotherapy", IEEE Transactions on Radiation and Plasma Medical Sciences, March 2019, 3(2):242-249. DOI: 10.1109/TRPMS.2018.2884134.
  • Cui, Y. Luo, H. Tseng, R. Ten Haken, I. El Naqa, “Combining Handcrafted Features with Latent Variables in Machine Learning for Prediction of Radiation-Induced Lung Damage", Medical Physics, May 2019, 46(5):2497-2511. DOI: 10.1002/mp.13497.
  • Luo, H. Tseng, R. Ten Haken, I. El Naqa, “Balancing Accuracy and Interpretability of Machine Learning Approaches for Radiation Treatment Outcomes Modeling", BJR Open, 2019, 1:20190021. DOI: 10.1259/bjro.20190021.
  • Luo, S. Chen, G. Valdes, “Machine Learning for Radiation Outcome Modeling and Prediction", Medical Physics, 2020, 47(5), e178-184. DOI: 10.1002/mp.13570.
  • Luo, S. Jolly, D.A. Palma, T.S. Lawrence, H. Tseng, G. Valdes, D. McShan, R. Ten Haken, I. El Naqa, “A Situational Awareness Bayesian Network Approach for Accurate and Credible Personalized Adaptive Radiotherapy Outcomes Prediction in Lung Cancer Patients", Physica Medica, July 2021, 87:11-23. DOI: 10.1016/j.ejmp.2021.05.032.
  • Luo, H. Carretta, I. Lee, G. LeBlanc, D. Sinha, G. Rust, “Naive Bayesian Network-based Contribution Analysis of Tumor Biology and Healthcare Factors to Racial Disparity in Breast Cancer Stage-at-diagnosis", Health Information Science and Systems, September 2021, 9(1):35. DOI: 10.1007/s13755-021-00165-5.

 

Book Chapters:

  • Luo, F. Szidarovszky, “A Proactive Defense Strategy to Enhance Situational Awareness in Computer Network Security", In book: Situational Awareness in Computer Network Defense: Principles, Methods and Applications, Cyril Onwubiko, Thomas Owens Editors, IGI Global, 2012. DOI: 10.4018/978-1-4666-4707-7.ch080.
  • Luo, “Exploring Efficient Reward Strategies to Encourage Large-Scale Cooperation among Boundedly Rational Players with the Risk and Impact of the Public Good", In book: Optimization Dynamics with Their Applications: Essays in Honor of Ferenc Szidarovszky, Akio Matsumoto Editor, Springer, 2017. DOI: 10.1007/978-981-10-4214-0 4.
  • El Naqa, S. Kerns, J. Coates, Y. Luo, C. Speers, R. Ten Haken, C. West, B. Rosenstein, “Biological Data: The Use of -Omics in Outcome Models", In book: A Guide to Outcome Modeling in Radiotherapy and Oncology: Listening to the Data, I. El Naqa Editor, Taylor & Francis, 2018. ISBN-13: 9781498768054.
  • Luo, I. El Naqa, “Machine Learning for Radiation Oncology", In book: Big Data in Radiation Oncology, Jun Deng, Lei Xing Editors, CRC Press, 2019. ISBN: 9780367780159.

 

Conference Publications:

  • Al-Nashif, A. Kumar, S. Hariri, Y. Luo, F. Szidarovszky, G. Qu, “Multi-Level Intrusion Detection System (ML-IDS)", International Conference on Autonomic Computing (ICAC), pp.131-140. June 2-6, 2008, Chicago, IL, USA. DOI: 10.1109/ICAC.2008.25.
  • Luo, F. Szidarovszky, Y. Al-Nashif, S. Hariri, “A Game Theory Based Risk and Impact Analysis Method for Intrusion Defense Systems", the 7th IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), pp.975-982. May 10-13, 2009, Rabat, Morocco. DOI: 10.1109/AICCSA.2009.5069450.
  • Luo, F. Szidarovszky, Y. Al-Nashif, S. Hariri, “Game Tree Based Partially Observable Stochastic Multi-Stage Game Model", IIE Annual Conference and Expo (IERC), May 30-June 3, 2009, Miami, FL, USA. ProQuest Document ID: 192457567.
  • Szidarovszky, Y. Luo, “On Optimal Strategies in Protecting Computer Networks", the 9th IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), pp.140-143. December 27-30, 2011, Sharm El-Sheikh, Egypt. DOI: 10.1109/AICCSA.2011.6126582.
  • Luo, D. McShan, F. Kong, M. Matuszak, M. Schipper, R. Ten Haken, “SU-D-137-03: Bayesian Belief Network Based Personalized Adaptive Decision Support to Individualize Response-Based Adaptive Therapy", Medical Physics 2013, 40(6):102-102. DOI: 10.1118/1.4814006.
  • McShan, Y. Luo, M. Schipper, R. Ten Haken, “Bayesian Decision Support for Adaptive Lung Treatments", XVII International Conference on the Use of Computers in Radiation Therapy (ICCR), May 6-9, 2013, Melbourne, Australia. DOI: 10.1088/1742-6596/489/1/012053.
  • Luo, D. McShan, F. Kong, M. Matuszak, M. Schipper, R. Ten Haken, “SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning", Medical Physics 2014, 41(6):155-155. DOI: 10.1118/1.4888055.
  • Luo, D. McShan, F. Kong, M. Matuszak, M. Schipper, R. Ten Haken, “TH-AB-304-07: A Two-Stage Signature-Based Data Fusion Mechanism to Predict Radiation Pneumonitis in Patients with Non-Small-Cell Lung Cancer (NSCLC)", Medical Physics 2015, 42:3702. DOI: 10.1118/1.4926122.
  • Luo, I. El Naqa, D. McShan, I. Lohse, M. Schipper, R. Ten Haken, “Response-Based Bayesian Network Approaches for Adaptive Radiotherapy of Non-Small-Cell Lung Cancer", Radiotherapy and Oncology 2016, 118:S100-S101. DOI: 10.1016/S0167-8140(16)30207-9.
  • Luo, D. McShan, M. Matuszak, S. Hobson, S. Jolly, R. Ten Haken, I. El Naqa, “WE-AB-207B-02: A Bayesian Network Approach for Joint Prediction of Tumor Control and Radiation Pneumonitis (RP) in Non-Small-Cell Lung Cancer (NSCLC)", Medical Physics 2016, 43(6):3804. DOI: 10.1118/1.4957783.
  • Luo, D. McShan, R. Ten Haken, I. El Naqa, “TU-FG-605-1: A Multi-Objective Dynamic Bayesian Network Approach for Adaptive Personalized Radiotherapy in Non-Small-Cell Lung Cancer (NSCLC)", Medical Physics 2017, 44(6):3158. DOI: 10.1002/mp.12304.
  • Luo, I. El Naqa, D. McShan, M. Matuszak, S. Jolly, R. Ten Haken, “Simultaneous Prediction of Specific Radiotherapy Outcomes Using a Multi-Objective Bayesian Network (moBN) Approach", International Journal of Radiation Oncology*Biology*Physics 2017, 99(2):S35. DOI: 10.1016/j.ijrobp.2017.06.094.
  • Cui, Y. Luo, S. Jolly, R. Ten Haken, I. El Naqa, “Prediction of Local Control in Non-small Cell Lung Cancer Patients after Radiotherapy by Composite Deep Learning Neural Networks", International Journal of Radiation Oncology*Biology*Physics 2018, 102(3S):S4. DOI: 10.1016/j.ijrobp.2018.06.107.
  • Luo, S. Jolly, D.A. Palma, T.S. Lawrence, D. McShan, R.K. Ten Haken, I. El Naqa, “A Subjective Bayesian Network Approach to Develop a Human-in-the-Loop Decision Support System for Personalized Adaptive Radiotherapy in Non-Small-Cell Lung Cancer (NSCLC)", International Journal of Radiation Oncology*Biology*Physics 2019, 105(1S):S94-S95. DOI: 10.1016/j.ijrobp.2019.06.573.