2025
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1.   Lu, Q., Y. Luo, H. Li, J. Luo, and Z. Wang, Deep Differentiable Symbolic Regression Neural Network. Neurocomputing, 2025. 629: p. 129671. [DOI]https://doi.org/10.1016/j.neucom.2025.129671.
2. Lu, C., Q. Lu, and J. Luo. An Explainable Vision Question Answer Model via Diffusion Chain-of-Thought. in European Conference on Computer Vision (ECCV 2024). 2025. Allianz MiCo, Milano Convention Centre: Springer. p. 146-162. [DOI]https://doi.org/10.1007/978-3-031-72855-6_9.
      
    2024
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3. Zagloul, M.M., J.M. Bock, J.H. Blumin, D.R. Friedland, J.A. Adams, L. Tong, K.I. Osinksi, M. Khani, and J. Luo, Evaluation of Social Determinants of Health on Dysphagia Care Pathways at a Tertiary Care Facility. The Laryngoscope, 2024. 134(3): p. 1139-1146. [DOI]https://doi.org/10.1002/lary.31040.
4. Yuan, M., Q. Lu, X. Zeng, J. Luo, and D. Li. Alleviating Semantic Drift in Multi-Hop Question Answering on Knowledge Graphs with Bidirectional Semantics. in IEEE 2024 International Joint Conference on Neural Networks (IJCNN). 2024. Pacifico Yokohama, Yokohama, Japan. [DOI]https://doi.org/10.1109/IJCNN60899.2024.10651324.
5. Taleban, A. and J. Luo. Unveiling health disparities: A big data approach to socioeconomic status and disease prevalence across income quantile. in American Public Health Association (APHA) 2024 Annual Conference. 2024. Minneapolis, MN. [DOI]https://apha.confex.com/apha/2024/meetingapp.cgi/Paper/548918.
6. Song, J., Q. Lu, B. Tian, J. Zhang, J. Luo, and Z. Wang. Symbol Graph Genetic Programming for Symbolic Regression. in Parallel Problem Solving from Nature – PPSN XVIII. 2024. Cham: Springer Nature Switzerland. p. 221-237. [DOI]https://doi.org/10.1007/978-3-031-70055-2_14.
7. Patel, P., O. Iqbal, D. Mohananey, S. Bajwa, M. Khani, J. Luo, D. Stein, J. Hashash, E. Mansoor, and R. Cross. ANTI TNF MEDICATIONS BUT NOT JAK INHIBITORS ARE ASSOCIATED WITH INCREASED RISK OF VENOUS THROMBOEMBOLISM. DATA FROM A LARGE NATIONAL COHORT. IS IT THE MECHANISM OF THE DRUG OR THE DISEASE? in Gastroenterology. 2024. p. S-1120. [DOI]https://ddw.digitellinc.com/p/s/6645.
8. Patel, P., O. Iqbal, D. Mohananey, S. Bajwa, M. Khani, J. Luo, D. Stein, J. Hashash, E. Mansoor, and R. Cross. BIOLOGICS AND JAK INHIBITORS DECREASE MAJOR CARDIOVASCULAR EVENTS (MACE) IN IBD PATIENTS. DATA FROM A LARGE NATIONAL COHORT. IS IT THE MECHANISM OF THE DRUG OR CONTROL OF DISEASE? in Gastroenterology. 2024. p. S-172. [DOI]https://ddw.digitellinc.com/p/s/6645.
9. Osafo, N.K., J.M. Bock, J.H. Blumin, J.A. Adams, D. Friedland, and J. Luo, Socioeconomic Determinants of Health and Reflux Management: Insights from a Tertiary Medical Center. The Laryngoscope, 2024. 10.1002(lary.31872). [DOI]https://doi.org/10.1002/lary.31872.
10. J. Luo, Assadi. M. Analyzing the impact of socioeconomic factors on disease recurrence, severity and patient mortality. in American Public Health Association (APHA) 2024 Annual Conference. 2024. Minneapolis, MN. [DOI]https://apha.confex.com/apha/2024/meetingapp.cgi/Paper/549634.
11. J. Luo, M.A. Shalmani, C. Berg, M. Carvan, R. Hesselbach, and D. Petering
    Data Science Empowerment for SEPA Students: Engaging Students through a Collaborative Portal of Big Data Applications Using Student Generated Experimental Results. in NIH SciEd 2024: Annual Conference for NIH Science Education Projects. 2024. Salt Lake City, USA. [DOI]https://nihsepa.org/annual-meeting/nih-scied-2024-annual-conference-for-nih-science-education-projects/.
12. Liu, Z., Q. Lu, Y. Zhao, Y. Zhao, and J. Luo, Differentiable Neural Network for Assembling Blocks. Frontiers in Artificial Intelligence and Applications, 2024. Volume 392(2024): p. 2250-2257. [DOI]https://doi.org/10.3233/FAIA240747.
13. Koss, K.R., D. Kumar, D.R. Friedland, J.A. Adams, K.K. Lauer, L. Tong, J. Luo, and B.T. Woodson, Disparities in polysomnography referral in a high-risk cardiac population. Sleep and Breathing, 2024. [DOI]https://doi.org/10.1007/s11325-024-03051-y.
14. Khani, M., J. Luo, M. Assadi Shalmani, A. Taleban, J. Adams, and D.R. Friedland, Advancing personalized healthcare: leveraging explainable AI for BPPV risk assessment. Health Information Science and Systems, 2024. 13(1): p. 1. [DOI]https://doi.org/10.1007/s13755-024-00317-3.
15. Khani, M. and J. Luo. Enhancing Early Intervention: Predicting Pancreatic Cancer Mortality Rates. in AMIA Clinical Infoirmatics Summit 2024. 2024. Boston, USA. p. P20. [DOI]https://s4.goeshow.com/amia/cic/2024/schedule_at_a_glance.cfm.
16. Bakeman, A., L. Tong, J. Rhee, D. Friedland, J. Adams, J. Luo, J. Kasprzak, and S. Pawar, Wound Healing Complications Associated with Staged Reconstruction after Facial Lentigo Maligna Resection. Facial Plastic Surgery & Aesthetic Medicine, 2024. [DOI]10.1089/fpsam.2023.0296.
17. Bajwa, S., P. Patel, O. Iqbal, D. Mohananey, M. Khani, J. Luo, D. Stein, J. Hashash, E. Mansoor, R. Cross, and P. Sinh. Inflammatory Bowel Disease is Associated With Increased Risk of Cardiovascular Events but Not Mortality. Data From a Large U.S. National Database. in Am J Gastroenterol. 2024. p. P. [DOI]10.14309/01.ajg.0001033660.60985.8a.
18. Assadi, M. and J. Luo. Analyzing the impact of socioeconomic factors on disease recurrence, severity and patient mortality. in American Public Health Association (APHA) 2024 Annual Conference. 2024. Minneapolis, MN. [DOI]https://apha.confex.com/apha/2024/meetingapp.cgi/Paper/549634.
19. Anik, A.A., P.B. Upama, M. Rabbani, S. Tian, M.S. Park, S.I. Ahamed, J. Luo, and H. Oh. Identifying Medical Concepts and Semantic Types in Lay Vocabularies of Health Consumers Who are Concerned with Diabetes on Social Media Using the UMLS and NLP. in 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC). 2024. IEEE. p. 862-869. [DOI]https://doi.org/10.1109/compsac61105.2024.00119.
20. Adams, J., V. Flanary, A. Thomas, L. Tong, K. Osinski, J. Luo, and D. Friedland, The Impact of Sociodemographic Factors on Rates of Tympanostomy Tube Placement for Pediatric Otitis Media. OTO open, 2024. 8(3): p. e159. [DOI]https://doi.org/10.1002/oto2.159.
    
    2023
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21. Weber, C., S. Ravi, S.M. Dongur​, J.F. b, and J. Luo. Obesity Diagnosis, and effect of SDOH on Obesity Rate and Food Insecurity Analysis​. in WCHQ Annual Diabetes Summit 2023. 2023. Madison, WI.
22. Thompson-Harvey, A., D.R. Friedland, J.A. Adams, L. Tong, K. Osinski, and J. Luo, The Demographics of Menière’s Disease: Selection Bias or Differential Susceptibility? Otology & Neurotology, 2023. 44(2). p. e95-e102 [DOI]https://doi.org/10.1097/mao.0000000000003780.
23. Park, M.S., P.B. Upama, A.A. Anik, S.I. Ahamed, J. Luo, S. Tian, M. Rabbani, and H. Oh. A Survey of Conversational Agents and Their Applications for Self-Management of Chronic Conditions. in 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC). 2023. IEEE. p. 1064-1075. [DOI]https://doi.org/10.1109/COMPSAC57700.2023.00162.
24. Park, M.S., H. Oh, J. Luo, S.I. Ahamed, P.B. Upama, A.A. Anik, S. Tian, and M. Rabbani. UMLS-Based Approach for Developing VoiS:  Voice-Activated Conversational Agent for Self-Management of Multiple Chronic Conditions in 2023 Association for Library and Information Science Education (ALISE) Annual Conference. 2023. [DOI]https://doi.org/10.21900/j.alise.2023.1251.
25. Alzughaibi, S.I. and J. Luo. HPV Vaccine Information Promotion Chatbot System: Development and Implementation Study. in Taxes Doswell Health Informatics Conference. 2023. Dallas, TX.
26. Tong, L. and J. Luo Association between Socioeconomic Disparity, Diagnostic Factors and Senior Adult Falls. in AcademyHealth 2023 Annual Research Meeting. 2023. Seattle, WA.
27. Tong, L., J. Luo, J. Adams, K. Osinski, X. Liu, and D. Friedland,, Interpretable machine learning text classification for clinical computed tomography reports – a case study of temporal bone fracture. Computer Methods and Programs in Biomedicine Update, 2023. 3: p. 100104. [DOI]https://doi.org/10.1016/j.cmpbup.2023.100104.
28. Harvey, E.A., D.R. Friedland, J.A. Adams, K. Osinski, and J. Luo. Association Between Low Frequency Sensorineural Hearing Loss and Cardiovascular Disease. in AAO-HNSF 2023 Annual Meeting & OTO Experience. . 2023. Music City Center, Nashville, Tennessee. [DOI]https://aao-hnsfjournals.onlinelibrary.wiley.com/doi/full/10.1002/ohn.447.
29. Feller, C.N., J.A. Adams, D.R. Friedland, M. Khani, J. Luo, and D.M. Poetker, Impacts of Socioeconomic Status on Dentoalveolar Trauma Wisconsin Medical Journal—WMJ, 2023. 122(1): p. 32-37. [DOI]https://wmjonline.org/122no1/feller/.
30. Drake, M., D.R. Friedland, B. Hamad, G. Marfowaa, J.A. Adams, J. Luo, and V. Flanary, Factors associated with delayed referral and hearing rehabilitation for congenital sensorineural hearing loss. International Journal of Pediatric Otorhinolaryngology, 2023. 175: p. 111770. [DOI]https://doi.org/10.1016/j.ijporl.2023.111770.
31. Baca, A.R., S. Saysanasongkham, C. Wallace, S.S. Seballos, S. Konphanthavong, S. Khamvongsa, J. Luo, and K.A. Cohn, Creation and Analysis of a Lao American Collaborative Medical Education Facebook Page. Education for Health, 2023. 36(1). [DOI]https://doi.org/10.4103/efh.efh_241_21.

    
    2022
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32. Tong, L., J. Luo, J. Adams, K. Osinski, X. Liu, and D. Friedland. A Clustering-Aided Approach for Diagnosis Prediction: A Case Study of Elderly Fall. in 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). 2022. p. 337-342. [DOI]https://doi.org/10.1109/COMPSAC54236.2022.00054.
33. Tong, L., M. Khani, Q. Lu, B. Taylor, K. Osinski, and J. Luo, Association between Body-Mass Index, Patient Characteristics, and Obesity-related Comorbidities among COVID-19 Patients: A Prospective Cohort Study. Obesity Research & Clinical Practice, 2022. [DOI]https://doi.org/10.1016/j.orcp.2022.12.003.
34. Tong, L., B. George, B.H. Crotty, M. Somai, B.W. Taylor, K. Osinski, and J. Luo, Telemedicine and health disparities: Association between patient characteristics and telemedicine, in-person, telephone and message-based care during the COVID-19 pandemic. IPEM-Translation, 2022. 3-4: p. 100010. [DOI]https://doi.org/10.1016/j.ipemt.2022.100010.
35. Thomas, A., V. Flanary, D.R. Friedland, J.A. Adams, L. Tong, K. Osinski, and J. Luo. The Impact of Social Determinants of Health on Tympanostomy Tube Placement for Otitis Media. in American Society of Pediatric Otolaryngolog 46th Annual Meeting, Dallas, TX. 2022. Dallas, TX, USA. [DOI]https://www.researchposters.com/Posters/COSM/COSM2022/i025.pdf.
36. Rabbani, M., S. Tian, A.A. Anik, J. Luo, M.S. Park, J. Whittle, S.I. Ahamed, and H. Oh. Towards Developing a Voice-activated Self-monitoring Application (VoiS) for Adults with Diabetes and Hypertension. in 2022 IEEE 46th Annual Computers, Software, and Applications Conference (COMPSAC). 2022. Los Alamitos, CA, USA: IEEE. p. 512-519. [DOI]https://doi.org/10.1109/COMPSAC54236.2022.00095.
37. Patel, M.A., J.M. Bock, J.H. Blumin, D.R. Friedland, J.A. Adams, L. Tong, K.I. Osinski, and J. Luo, Demographic differences in the treatment of unilateral vocal fold paralysis. Laryngoscope Investigative Otolaryngology, 2022. 2022(1): p. 1-7. [DOI]https://doi.org/10.1002/lio2.920.
38. Osafo, N.K., D.R. Friedland, M.S. Harris, J. Adams, C. Davis, K. Osinski, L. Tong, and J. Luo, Standardization of Outcome Measures for Intratympanic Steroid Treatment for Idiopathic Sudden Sensorineural Hearing Loss. Otology & Neurotology, 2022. 43(10): p. 1137-1143. [DOI]https://doi.org/10.1097/mao.0000000000003709.
39. Luo, Y., Q. Lu, X. Hu, J. Luo, and Z. Wang. Exploring Hidden Semantics in Neural Networks with Symbolic Regression. in Proceedings of the Genetic and Evolutionary Computation Conference. 2022. Boston, Massachusetts. p. 982–990. [DOI]https://doi.org/10.1145/3512290.3528758.
40. Tong, L., M. Khani, and J. Luo. Dr. Diagnosis: A Visualization Model for Diagnosing Diabetic Retinopathy Severity andDiscovering Plaque Patterns in Retinal Images. in International Conference on AI in Aging and Age-relatedDiseases (AIHC 2022). 2022. Online. [DOI]https://virtual.oxfordabstracts.com/#/event/public/1834/session/56860.
41. Lu, Q., C. Xu, J. Luo, and Z. Wang, AB-GEP: Adversarial bandit gene expression programming for symbolic regression. Swarm and Evolutionary Computation, 2022: p. 101197. [DOI]https://doi.org/10.1016/j.swevo.2022.101197.
42. Kumar, D., B.T. Woodson, D.R. Friedland, J.A. Adams, L. Tong, and J. Luo. Healthcare Disparity Impact on Ordering Polysomnography in a High Risk OSA Population. in 2022 Combined Otolaryngology Spring Meetings. 2022. Taxes, TX, USA. [DOI]https://www.researchposters.com/Posters/COSM/COSM2022/F009.pdf.
43. Hernandez, L.V., S.K. Ravi, N.M. Guda, A. Gresenz, and J. Luo, MICRO-COST ESTIMATES OF PROCEDURES IN A COMMUNITY-BASED AMBULATORY ENDOSCOPY CENTER: WHEN DO WE SWITCH TO SINGLE-USE ENDOSCOPES? Gastrointestinal Endoscopy, 2022. 95(6): p. AB133-AB134. [DOI]https://doi.org/10.1016/j.gie.2022.04.362.
44. He, B., Q. Lu, Q. Yang, J. Luo, and Z. Wang. Taylor genetic programming for symbolic regression. in Proceedings of the Genetic and Evolutionary Computation Conference. 2022. Boston, Massachusetts: Association for Computing Machinery. p. 946–954. [DOI]https://doi.org/10.1145/3512290.3528757.
45. Harvey, E., K. Stark, D.R. Friedland, J.A. Adams, M.S. Harris, L. Tong, K. Osinksi, and J. Luo, Impact of Demographics and Clinical Features on Initial Treatment Pathway for Vestibular Schwannoma. Otology & Neurotology, 2022: p. 10.1097/MAO.0000000000003652. [DOI]https://doi.org/10.1097/mao.0000000000003652.
46. Harvey, E., E. Peterson, M. Espahbodi, A.B.D.R. Friedland, J.A. Adams, and J. Luo. Impact of Demographics and Clinical Features on Initial Treatment Decision Making in Vestibular Schwannoma. in Combined Otolaryngology Spring Meetings: COSM. 2022. Dallas, Texas, USA. p. ANS 2022 POSTER H036. [DOI]https://www.researchposters.com/Posters/COSM/COSM2022/H036.pdf.
47. Harvey, E., E. Peterson, M. Espahbodi, A.B.D.R. Friedland, J.A. Adams, and J. Luo. The Efficacy of CT Angiography in Assessing Vascular Injury in Patients with Temporal Bone Fracture. in Combined Otolaryngology Spring Meetings: COSM. 2022. Dallas, Texas, USA. p. ANS 2022 POSTER H035. [DOI]https://www.researchposters.com/Posters/COSM/COSM2022/i025.pdf.
48. Alarifi, M., A.M. Jabour, M. Wu, A. Aldosary, M. Almanaa, and J. Luo, Proposed Questions to Assess the Extent of Knowledge in Understanding the Radiology Report Language. International Journal of Environmental Research and Public Health, 2022. 19(18): p. 11808. [DOI]10.3390/ijerph191811808.
49. Alanazi, E.M. and J. Luo. Evaluating a Prototype of a Smart Patient-Oriented Obstetric Ultrasound Report (SPOUR): Second Trimester Scan. in AMDIS/HIMSS Physicians’ Executive Symposium. 2022. Orange County Convention Center, Orlando, Florida.
50. Alanazi, E.M., T.M. Alanzi, M. Wu, and J. Luo, Patients’ unmet information needs and gaps of obstetric ultrasound exam: A qualitative content analysis of social media platforms. Informatics in Medicine Unlocked, 2022. 28: p. 100830. [DOI]https://doi.org/10.1016/j.imu.2021.100830.
    
    2021
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51. Xu, C., Q. Lu, J. Luo, and Z. Wang. Adversarial bandit gene expression programming for symbolic regression. in Proceedings of the Genetic and Evolutionary Computation Conference Companion. 2021. Lille, France. p. 269-270. [DOI]https://doi.org/10.1145/3449726.3459499.
52. White, S.W., J.M. Bock, J.H. Blumin, D.R. Friedland, J.A. Adams, L. Tong, K. Osinski, and J. Luo, Analysis of socioeconomic factors in laryngology clinic utilization for treatment of dysphonia. Laryngoscope Investigative Otolaryngology, 2021. 2021: p. 1-8. [DOI]https://doi.org/10.1002/lio2.715.
53. Thomas, A., V. Flanary, D.R. Friedland, J.A. Adams, L. Tong, K. Osinski, and J. Luo, The impact of social determinants of health and clinical comorbidities on post-tympanotomy tube otorrhea. International Journal of Pediatric Otorhinolaryngology, 2021: p. 110986. [DOI]https://doi.org/10.1016/j.ijporl.2021.110986.
54. Poetker, D.M., D.R. Friedland, J.A. Adams, L. Tong, K. Osinski, and J. Luo, Socioeconomic Determinants of Tertiary Rhinology Care Utilization. OTO open, 2021. 5(2): p. 2473974X211009830. [DOI]https://doi.org/10.1177/2473974X211009830.
55. Luo, J., L. Tong, B.H. Crotty, M. Somai, B. Taylor, K. Osinski, and B. George, Telemedicine Adoption during the COVID-19 Pandemic: Gaps and Inequalities. Applied Clinical Informatics, 2021. 12(04): p. 836-844. [DOI]https://doi.org/10.1055/s-0041-1733848.
56. Lu, Q., S. Zhou, F. Tao, J. Luo, and Z. Wang, Enhancing gene expression programming based on space partition and jump for symbolic regression. Information Sciences, 2021. 547: p. 553-567. [DOI]https://doi.org/10.1016/j.ins.2020.08.061.
57. iplagat, A.B., P.M. Kako, L. Mkandawire-Valhmu, D. Chelagat, S.H. Gwon, J. Luo, and M.V. Dixon, The HIV transmission risk factors and opportunities for use of mHealth in HIV prevention among emerging adult population in the Sub-Saharan Africa context: a review of the literature. International Journal of Health Promotion and Education, 2021: p. 1-15. [DOI]https://doi.org/10.1080/14635240.2021.1995464.
58. erg, C., M. Carvan, R. Hesselbach, Z. Luo, D.H. Petering, M. Pickart, H. Tomasiewicz, D.N. Weber, R. Shukla, and B. Goldberg, Meeting the COVID Challenge to a Research-intensive Pre-college Science Education Program. Journal of STEM Outreach, 2021. 4(2): p. 1-11. [DOI]https://doi.org/10.15695/jstem/v4i2.01.
59. Anisuzzaman, D., H. Barzekar, L. Tong, J. Luo, and Z. Yu, A deep learning study on osteosarcoma detection from histological images. Biomedical signal processing and control, 2021. 69: p. 102931. [DOI]https://arxiv.org/abs/2011.01177.
60. Alarifi, M., T. Patrick, A. Jabour, M. Wu, and J. Luo, Health Consumer Social Economic Factors and Health Conditions as Predictor for Health Literacy in Radiology Domain. Journal of Medical Imaging and Health Informatics, 2021. 11(11): p. 2716-2721. [DOI]https://doi.org/10.1166/jmihi.2021.3864.
61. Alarifi, M., T. Patrick, A. Jabour, M. Wu, and J. Luo, Understanding patient needs and gaps in radiology reports through online discussion forum analysis. Insights into imaging, 2021. 12(1): p. 1-9. [DOI]https://doi.org/10.1186/s13244-020-00930-2.
62. Alarifi, M., T. Patrick, A. Jabour, M. Wu, and J. Luo, Designing a Consumer-Friendly Radiology Report using a Patient-Centered Approach. Journal of digital imaging, 2021: p. 1-12. [DOI]https://doi.org/10.1007/s10278-021-00448-z.
63. Alanazi, E.M., A. Abdou, and J. Luo, Predicting risk of stroke from lab tests using machine learning algorithms: Development and evaluation of prediction models. JMIR Formative Research, 2021. 5(12): p. e23440. [DOI]https://doi.org/10.2196/23440.

    
    2020 and before
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64. Tong, L., L.V. Hernandez, and J. Luo, PREDICTING GASTROINTESTINAL (GI) HEMORRHAGE USING A MACHINE LEARNING APPROACH: RISK FACTORS AND PREDICTIVE ANALYSIS IN CLINICAL STUDIES. Gastroenterology, 2020. 158(6): p. S-16. [DOI]https://doi.org/10.1016/S0016-5085(20)30721-6.
65. Tong, L., L.V. Hernandez, J. Cofino, J.O. Johannessen, N.M. Guda, and J. Luo, ASSOCIATION MODELING BETWEEN PATIENTS’AGE AND COMPLICATION RATE FOR ENDOSCOPIC PROCEDURES. Gastroenterology, 2020. 158(6): p. S-1242. [DOI]https://doi.org/10.1016/S0016-5085(20)33766-5.
66. Liu, H., T. Tang, J. Luo, M. Zhao, B. Zheng, and Y. Wu, An anomaly detection method based on double encoder–decoder generative adversarial networks. Industrial Robot: the international journal of robotics research and application, 2020. 48(5): p. 643-648. [DOI]https://doi.org/10.1108/IR-09-2020-0200.
67. Hernandez, L., L. Tong, J. Cofino, J.O. Johannessen, N.M. Guda, V. Muddana, and J. Luo, ASSOCIATION BETWEEN ATTENDING ENDOSCOPISTS’EXPERIENCE AND COMPLICATION RATES FOR ALL ENDOSCOPIC PROCEDURES: A 10-YEAR LONGITUDINAL STUDY. Gastrointestinal Endoscopy, 2020. 91(6): p. AB525. [DOI]https://doi.org/10.1016/j.gie.2020.03.3230.
68. Chesley, N., H. Meier, J. Luo, I. Apchemengich, and W. Davies, Social factors shaping the adoption of lead-filtering point-of-use systems: an observational study of an MTurk sample. Journal of Water and Health, 2020. 18(4): p. 505-521. [DOI]https://doi.org/10.2166/wh.2020.053.
69. Alarifi, M., T. Patrick, A. Jabour, M. Wu, and J. Luo, Full Radiology Report through Patient Web Portal: A Literature Review. International Journal of Environmental Research and Public Health, 2020. 17(10): p. 3673. [DOI]https://doi.org/10.3390/ijerph17103673.
70. Zolnoori, M., K.W. Fung, T.B. Patrick, P. Fontelo, H. Kharrazi, A. Faiola, Y.S.S. Wu, C.E. Eldredge, J. Luo, and M. Conway, A systematic approach for developing a corpus of patient reported adverse drug events: a case study for SSRI and SNRI medications. Journal of Biomedical Informatics, 2019. 90: p. 103091. [DOI]https://doi.org/10.1016/j.jbi.2018.12.005.
71. Zolnoori, M., K.W. Fung, T.B. Patrick, P. Fontelo, H. Kharrazi, A. Faiola, N.D. Shah, Y.S.S. Wu, C.E. Eldredge, and J. Luo, The PsyTAR dataset: From patients generated narratives to a corpus of adverse drug events and effectiveness of psychiatric medications. Data in brief, 2019. 24: p. 103838. [DOI]https://doi.org/10.1016/j.dib.2019.103838.
72. Wu, M. and J. Luo, Wearable technology applications in healthcare: a literature review. Online J Nurs Inform, 2019. 23. [DOI]https://dx.doi.org/10.2196%2F18907.
73. Tong, L., J. Luo, R. Cisler, and M. Cantor. Machine learning-based modeling of big clinical trials data for adverse outcome prediction: A case study of death events. in 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC). 2019. Milwaukee, WI, USA: IEEE. p. 269-274. [DOI]https://doi.org/10.1109/COMPSAC.2019.10218.
74. Eldredge, C., J.E. Andrews, M. Zolnoori, T.B. Patrick, J. Gallagher, C.A. Lam, and J. Luo. Challenges to a Data Driven Approach to Population Level Analysis of Hypersensitivity Events in Cancer Clinical Trials. in AMIA. 2019. Washington DC. [DOI]http://toc.proceedings.com/52630webtoc.pdf.
75. Benson, L.C., S.C. Cobb, A.S. Hyngstrom, K.G. Keenan, J. Luo, and K.M. O’Connor, A principal components analysis approach to quantifying foot clearance and foot clearance variability. J Appl Biomech, 2019. 35: p. 116-22. [DOI]https://doi.org/10.1123/jab.2018-0187.
76. Barzekar, H., F. Ebrahimzadeh, J. Luo, M. Karami, Z. Robati, and P. Goodarzi, Adoption of Hospital Information System Among Nurses: a Technology Acceptance Model Approach. Acta Informatica Medica, 2019. 27(5): p. 305. [DOI]https://dx.doi.org/10.5455%2Faim.2019.27.305-310.
77. Zolnoori, M., C. Ngufor, A. Faiola, C. Eldredge, J. Luo, S. Sohn, J.E. Balls-Berry, A. Tafti, N.D. Shah, and T.B. Patrick. Identify Factors Affecting Drug Discontinuation in Patients with Depression: Text Analysis of Patient Drug Review Posts. in American Medical Informatics Association Annual Symposium. 2018. WASHINGTON, D.C. [DOI]https://doi.org/10.2196%2F10726.
78. Zolnoori, M., K.W. Fung, T. Patrick, P. Fontelo, H. Kharrazi, A. Faiola, Y.S.S. Wu, C.E. Eldredge, J. Luo, M. Conway, J. Zhu, and S.K. Park, A systematic approach for developing a corpus of adverse drug events associated with psychiatric medications. Journal of Biomedical Informatics, 2018. [DOI]https://doi.org/10.1016/j.jbi.2018.12.005.
79. Zhao, Y., N.J. Fesharaki, H. Liu, and J. Luo, Sublanguage Pattern Mining to Induce Knowledge Model: Application in Medical Image Reports Knowledge Representation. BMC Medical Informatics and Decision Making, 2018. 18(1): p. e61. [DOI]https://doi.org/10.1186/s12911-018-0645-3.
80. Zhao, Y., N.J. Fesharaki, X. Li, T.B. Patrick, and J. Luo, Semantic-Enhanced Query Expansion System for Retrieving Medical Image Notes. Journal of Medical Systems, 2018. 42: p. 1-11. [DOI]https://doi.org/10.1007/s10916-018-0954-1.
81. Tong, L., N. Zhou, R. Cisler, M.N. Cantor, and J. Luo. Machine Learning-based Prediction of Death Events in Clinical Studies Using Big Clinical Trial Data. in UWM Health Research Symposium. 2018. Milwaukee, WI. [DOI]https://doi.org/10.1109/COMPSAC.2019.10218.
82. Tang, T., S. Chen, M. Zhao, W. Huang, and J. Luo, Very large-scale data classification based on K-means clustering and multi-kernel SVM. Soft Computing, 2018: p. 1-9. [DOI]https://doi.org/10.1007/s00500-018-3041-0.
83. Tang, T., S. Chen, and J. Luo, A new support vector selection strategy and a local-global regularization method for improving online SVM learning. Electronics Letters, 2018. 54(12): p. 735-736. [DOI]10.1049/el.2018.0765.
84. MICHLIG, J.R., A.C. LANG, R.L. WANDREY, N.A. CHESLEY, J. LUO, and W.H. Davies. Emerging Adults Reactions to the American Academy of Pediatrics Guidelines for Adolescent Media Use. in Midwestern Psychological Association Annual Conference. 2018. Chicago.
85. Luo, J., C. Erbe, and D.R. Friedland, Unique Clinical Language Patterns Among Expert Vestibular Providers Can Predict Vestibular Diagnoses. Otology & Neurotology, 2018. 39(9): p. 1163-1171. [DOI]https://doi.org/10.1097/mao.0000000000001930.
86. Luo, J., C. Erbe, and D.R. Friedland. Unique Clinical Language Patterns among Expert Vestibular Providers can Predict Vestibular Diagnoses. in Otology & Neurotology Conference. 2018. p. 1163-1171. [DOI]https://doi.org/10.1097/mao.0000000000001930.
87. Eldredge, C., A.K. Singavi, J. Gallagher, C. Lam, and J. Luo. Big Data Analysis of Drug Induced Hypersensitivity and Anaphylaxis Reactions in Clinical Cancer Trials. in American Academy of Allergy Asthma & Immunology and World Allergy Organization Joint Congress (AAAAI/WAO Joint Congress). 2018. Orlando, FL. [DOI]https://doi.org/10.1016/j.jaci.2017.12.279.
88. Eldredge, C., A. Singavi, C. Lam, J.L. Gallagher, and J. Luo, Big Data Analysis of Drug Induced Hypersensitivity and Anaphylaxis Reactions in Clinical Cancer Trials. Journal of Allergy and Clinical Immunology, 2018. 141(2): p. AB87. [DOI]https://doi.org/10.1016/j.jaci.2017.12.279.
89. Benson, L.C., S.C. Cobb, A.S. Hyngstrom, K.G. Keenan, J. Luo, and K.M. O’Connor, Identifying trippers and non-trippers based on knee kinematics during obstacle-free walking. Human movement science, 2018. 62: p. 58-66. [DOI]https://doi.org/10.1016/j.humov.2018.09.009.
90. Zhao, Y., T. Patrick, and J. Luo. Radiology Semantic Model for Query Expansion. in College of Health Science Symposium. 2017. Milwaukee.
91. Luo, J., M. Wu, and W. Chen, Geographical Distribution and Trends of Clinical Trial Recruitment Sites in Developing and Developed Countries. Journal of Health Informatics in Developing Countries (JHIDC), 2017. 11(1). [DOI]https://www.jhidc.org/index.php/jhidc/article/view/157.
92. Luo, J., C. Pelfrey, and G.-q. Zhang. Visualizing and evaluating the growth of multi-institutional collaboration based on research network analysis. in CTSA Bibliometrics Group Program Meeting. 2017. Chicago.
93. Luo, J., W. Chen, M. Wu, and C. Weng, Systematic data ingratiation of clinical trial recruitment locations for geographic-based query and visualization. International Journal of Medical Informatics, 2017. 108: p. 85-91. [DOI]https://doi.org/10.1016/j.ijmedinf.2017.10.003.
94. Ejiwale, M.O., T. Patrick, and J. Luo. m2Health Application, A Consumer Health Informatics Tool for Evidence-Based Self-Management Care Against Postpartum Infection. in CHS Research Symposium. 2017. Milwaukee, WI.
95. Benson, L.C., S.C. Cobb, A. Hyngstrom, K.G. Keenan, J. Luo, and K.M. O’Connor. Using a Single Ankle-Worn Accelerometer to Predict Lower Extremity Joint Range of Motion. in Congress of the International Society of Biomechanics (ISB’2017). 2017. Brisbane, Australia. [DOI]https://media.isbweb.org/images/conferences/isb-congresses/2017/ISB2017-Full-Abstract-Book.pdf.
96. Alarifi, M., J. Luo, M. Almanaa, and E. Altuwayjiri. Physicians Satisfaction With Clinical Decision Support System:  An Examination Of Alerts And Alert Fatigue. in 2nd International Saudi Health Informatics Conference (ISHIC 2017). 2017. Riyadh, Kingdom Of Saudi Arabia.
97. Zolnoori, M., T. Patrick, M. Conway, A. Faiola, and J. Luo. Evaluating Acceptability and Efficacy of Antidepressant Medications using Patients Comments in Social Media. in American Medical Informatics Association Annual Symposium. 2016. Chicago.
98. Luo, J., M. Wu, D. Gopukumar, and Y. Zhao, Big data application in biomedical research and health care: a literature review. Biomedical Informatics Insights, 2016. 8: p. BII. S31559. [DOI]https://doi.org/10.4137%2FBII.S31559.
99. Luo, J., C. Eldredge, C.C. Cho, and R.A. Cisler, Population analysis of adverse events in different age groups using big clinical trials data. JMIR Medical Informatics, 2016. 4(4): p. e30. [DOI]https://doi.org/10.2196/medinform.6437.
100. Luo, J. and R.A. Cisler, Discovering Outliers of Potential Drug Toxicities Using a Large-scale Data-driven Approach. Journal of Cancer Informatics, 2016. 15: p. 211. [DOI]https://doi.org/10.4137/cin.s39549.
101. Benson, L., S. Cobb, A. Hyngstrom, K. Keenan, J. Luo, and K. O’Connor. Predicting walking foot clearance from sagittal plane joint coordination. in College of Health Sciences Spring Research Symposium. 2016. Second Place in Student Competition, Milwaukee WI.
102. Nambison, P., Z. Luo, T. Patrick, and R. Cisler. Social Medical, Big Data and Public Health Informatics: Towards a Systematic Detection of Depression from Tweets. in Hawaii International Conference on System Sciences (HICSS). 2015. Hawaii. p. 2906 – 2913.
103. Nambisan, P., Z. Luo, A. Kapoor, T.B. Patrick, and R.A. Cisler. Social media, big data, and public health informatics: Ruminating behavior of depression revealed through twitter. in 2015 48th Hawaii International Conference on System Sciences. 2015. Hawaii: IEEE. p. 2906-2913. [DOI]https://doi.org/10.1109/HICSS.2015.351.
104. Nambisan, P., Z. Luo, and A. Kapoor. Social media and big data: Can Tweet moods predict illness and hospital/doc visits in a region?​. in UWM Geek Week. 2015. Milwaukee.
105. Luo, Z., G.-Q. Zhang, S. Wentz, L. Cui, and R. Xu, SimQ: Real-Time Retrieval of Similar Consumer Health Questions. Journal of Medical Internet Research (JMIR), 2015. 17(2): p. e43. [DOI]https://doi.org/10.2196/jmir.3388.
106. Luo, Z., M. Wu, and Y. Zhao, Big Data in Medical Informatics. Journal of Medical Informatics (Chinese Journal), 2015(5): p. 2-9. [DOI]https://doi.org/10.3969/j.issn.1000-3428.2011.01.037.
107. Luo, J. and T. Patrick. Bridging the Representation Gap of Medical Image and Clinical Note through Semantic Association Mining. in AMIA 2015 Annual Symposium. 2015. San Francisco, CA, USA.
108. Kadapa, K.K. and J. Luo. Automatic Semantic Annotation of Medical Images Using Entities Extracted from Clinical Notes. in Spring Symposium of the Center for Advanced Computational Imaging. 2015. Milwaukee, WI, UWA.
109. Kadapa, K., T. Patrick, and J. Luo. Briding the Gap of Medical Imaging and Text Representation. in UWM Geek Week. 2015. Milwaukee.
110. Sahoo, S.S., S. Tao, A. Parchman, Z. Luo, L. Cui, P. Mergler, R. Lanese, J.S. Barnholtz-Sloan, N.J. Meropol, and G.-Q. Zhang, Trial Prospector: Matching Patients with Cancer Research Studies using an Automated and Scalable Approach. Journal of Cancer Informatics, 2014. 13: p. 157-166. [DOI]https://doi.org/10.4137/cin.s19454.
111. Nambison, P., J. Luo, and A. Kapoor. Social Media and Big Data: Can tweet moods predict illness and hospital visits in a region? . in APHA conference 141st Annual Meeting. 2014. New Orleans, LA.
112. Nambisan, P., J. Luo, and A. Kapoor. Social media and big data: Can Tweet moods predict illness and hospital/doc visits in a region? in American Public Health Association Anual Meeting. 2014. New Orleans, LA.
113. Luo, J., C. Pelfrey, and G.Q. Zhang. Visualizing and Evaluating the Growth of Multi-Institutional Collaboration Based on Research Network Analysis. in Proceedings of AMIA Clinical Research Informatics Summit. 2014. San Francisco. p. 112-117. [DOI]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4419767/.
114. Luo, J., C. Apperson-Hansen, C.M. Pelfrey, and G.-Q. Zhang, RMS: a platform for managing cross-disciplinary and multi-institutional research project collaboration. BMC Journal of Medical Informatics and Decision Making, 2014. 14(1): p. 106. [DOI]https://doi.org/10.1186/s12911-014-0106-6.
115. Cui, L., R. Xu, Z. Luo, S. Wentz, K. Scarberry, and G.-Q. Zhang, Multi-topic assignment for exploratory navigation of consumer health information in NetWellness using formal concept analysis. BMC Journal of Medical Informatics and Decision Making, 2014. 14(1): p. 63. [DOI]https://doi.org/10.1186/1472-6947-14-63.
116. Wu, M., Z. Luo, and C. Weng, Discussion and Research on Personalized Medicine – A Literature Review. Journal of Medical Informatics (Chinese Journal), 2013. 34(10): p. 2-7. [DOI]https://d.wanfangdata.com.cn/periodical/yxqbgz201310001.
117. Weng, C., Z. Luo, and S.B. Johnson. An Approach to Eligibility Criteria Extraction and Representation. in 2013 Summit on Clinical Research Informatics. 2013. San Francisco. [DOI]https://doi.org/10.1136/amiajnl-2011-000321.
118. Luo, Z., G.Q. Zhang, J. Teagno, and R. Xu. Large-Scale Analysis of Serious Adverse Events Reporting in Clinical Trials Funded by For-Profit and Not-For-Profit Agencies. in AMIA Joint Summits on Translational Science. 2013. San Francisco. [DOI]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814483/.
119. Luo, Z., G.-Q. Zhang, and R. Xu. Mining Patterns of Adverse Events Using Aggregated Clinical Trial Results. in AMIA Joint Summit on Translational Science 2013. San Franciso, USA. p. 112-116. [DOI]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3814483/.
120. Luo, Z., R. Miotto, and C. Weng, A human-computer collaborative approach to identifying common data elements in clinical trial eligibility criteria. Journal of Biomedical Informatics, 2013. 46(1): p. 33-9. [DOI]10.1016/j.jbi.2012.07.006.
121. Luo, Z., S.S. Sahoo, and G.Q. Zhang. ICaRe: A Web Services-based Unified Informatics Portal for the Cleveland CTSC. in CTSA Informatics Key Function Committee meeting. 2012. Chicago. p. 47.
122. Luo, Z., S.S. Sahoo, and G.Q. Zhang. A Pipeline for Rendering and Analyzing Large Institutional Research Networks. in CTSA Informatics Key Function Committee meeting. 2012. Chicago. p. Page 44.
123. Weng, C., X. Wu, Z. Luo, M.R. Boland, D. Theodoratos, and S.B. Johnson, EliXR: An Approach to Eligibility Criteria Extraction and Representation. Journal of the American Medical Informatics Association (JAMIA), 2011. 18: p. i116-i124. [DOI]https://doi.org/10.1136/amiajnl-2011-000321.
124. Miao, X.-f., Z. Luo, and L. Hong, Routing protocol simulation research based on SUMO. Journal Computer Engineering (Chinese Journal), 2011. 37(1): p. 107-109. [DOI]https://doi.org/10.3969/j.issn.1000-3428.2011.01.037.
125. Luo, Z., M. Yetisgen-Yildiz, and C. Weng, Dynamic categorization of clinical research eligibility criteria by hierarchical clustering. Journal of Biomedical Informatics, 2011. 44(6): p. 927-935. [DOI]10.1016/j.jbi.2011.06.001.
126. Luo, Z., S.B. Johnson, A.M. Lai, and C. Weng. Extracting Temporal Constraints from Clinical Research Eligibility Criteria Using Conditional Random Fields. in American Medical Informatics Association Annual Symposium 2011. 2011. Washington, DC. p. 843-852. [DOI]https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3243135/.
127. Weng, C. and Z. Luo. Dynamic Categorization of Clinical Research Eligibility Criteria. in Proc of AMIA Fall Symp. 2010. Washington DC. p. 306.
128. Luo, Z., S.B. Johnson, and C. Weng. Semi-Automatically Inducing Semantic Classes of Clinical Research Eligibility Criteria Using UMLS and Hierarchical Clustering. in American Medical Informatics Association Annual Symposium. 2010. Washington, DC. p. 487-491. [DOI]https://pubmed.ncbi.nlm.nih.gov/21347026/.
129. Luo, Z., R. Duffy, S. Johnson, and C. Weng. Corpus-based Approach to Creating a Semantic Lexicon for Clinical Research Eligibility Criteria from UMLS. in AMIA Jt Summits Transl Sci Proc. 2010. Bethesda, MD, USA. p. 26-30. [DOI]https://www.ncbi.nlm.nih.gov/pubmed/21347142.
130. Graham, C., D. Bell, and Z. Luo, Multi-agent reinforcement learning–an exploration using Q-learning. Research and Development in Intelligent Systems XXVI. 2010: Springer. [DOI]https://doi.org/10.1007/978-1-84882-983-1_21.
131. Wu, Q., X. Huang, D.A. Bell, G. Qi, and Z. Luo. Incremental Knowledge Base for Uncertain Reasoning. in Fuzzy Systems and Knowledge Discovery, 2008. FSKD’08. 2008. Jinan, Shandong, China: IEEE. p. 187-192. [DOI]https://doi.org/10.1109/FSKD.2008.117.
132. Luo, Z., D.A. Bell, and B. McCollum. Discover Relevant Environment Feature Using Concurrent Reinforcement Learning. in Twenty-Third Conference on Artificial Intelligence. 2008. Chicago, USA. p. 1816-1818. [DOI]https://aaai-22.aaai.org/Library/AAAI/2008/aaai08-298.php.
133. Luo, Z., D. Bell, B. McCollum, and Q. Wu. Learning to select relevant perspective in a dynamic environment. in Neural Networks, 2008. IJCNN 2008.(IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on. 2008. Hong Kong: IEEE. p. 666-673. [DOI]https://doi.org/10.1109/IJCNN.2008.4633866.
134. Wu, Q., D.A. Bell, R.H. Khokhar, G. Qi, and Z. Luo. Autonomous Robot Control Using Evidential Reasoning. in Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on. 2007. Haikou, Hainan, China: IEEE. p. 550-554. [DOI]https://doi.org/10.1109/FSKD.2007.200.
135. Luo, Z., D. Bell, and B. McCollum. Skill combination for reinforcement learning. in Intelligent Data Engineering and Automated Learning-IDEAL 2007. 2007. Birmingham, UK. p. 87-96. [DOI]https://doi.org/10.1007/978-3-540-77226-2_10.
136. Luo, Z., D. Bell, and Q. Wu. Reinforcement Learning Sub-goal Discovery Using States Visited Statistic Method. in The 17th Irish conference on Artificial Intelligence and Cognitive Science (AICS). 2006. Belfast, UK. p. 113-120.

Peer-reviewed Conference Abstracts & Posters