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Feifan Liu PhD

TitleAssociate Professor
InstitutionUMass Chan Medical School
DepartmentPopulation and Quantitative Health Sciences
AddressUMass Chan Medical School
368 Plantation Street AS9-1075
Worcester MA 01605
Phone774-455-4586
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    Other Positions
    InstitutionT.H. Chan School of Medicine
    DepartmentPopulation and Quantitative Health Sciences
    DivisionHealth Informatics And Implementation Science

    InstitutionT.H. Chan School of Medicine
    DepartmentRadiology

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentMasters in Clinical Investigation

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentPopulation Health Sciences


    Collapse Biography 
    Collapse education and training
    Shandong University, Jinan, , ChinaBSElectrical Engineering
    Shandong University, Jinan, , ChinaMSScience
    Chinese Academy of Sciences, Beijing, , ChinaPHDComputer Science
    University of Texas at Dallas, Dallas, USAPostdoc Fellow08/2009Machine Learning in Language Understanding

    Collapse Overview 
    Collapse overview

    Dr. Liu completed doctoral training in pattern recognition and artificial intelligence, with strong expertise in natural language processing, machine learning (deep learning), and biomedical informatics. He is currently an Associate Professor in Health Informatics and the founding director of the innovative AI for Health (iAI4Health) lab. He was awarded as an NIH AIM-AHEAD leadership fellow in 2022 and has been selected to serve as a scientific advisor for NIH All of US research scholar program and NIH AIM-AHEAD leadership fellowship program since 2023. His research focuses on exploiting advanced computational models to analyze heterogeneous and complex healthcare data for knowledge extraction, predictive modeling and preventative data analytics, in the areas of suicide risk prediction, HIV prevention, cancer informatics, and cardiometabolic disease management.   

    Dr. Liu has published more than 70 peer-reviewed manuscripts (over 30 first-author) on premium journals and top computer science conferences. His research has been continuously funded by NIH as PI, MPI, or leading data scientists. Dr. Liu participated in NSF and NIH study sections in the areas of machine learning, natural language processing, and clinical predictive modeling. Through developing advanced machine learning methods, Dr. Liu has won first place in two international challenge tasks: Medical Visual Question Answering (2018) and Gene Mutation/Disease Relation Extraction (2019).

    Recently, Dr. Liu's research has focused on applying AI techniques to advance health equity, assessing and mitigating potential biases related to data processing and algorithmic training.



    Collapse Research 
    Collapse research activities and funding
    R01HL125089     (Yu)Dec 1, 2014 - Nov 30, 2019
    NIH/NHLBI
    EHR Anticoagulants Pharmacovigilance
    Role Description: To explore innovative and intelligent biomedical natural language process approaches to detect ADEs in patients' electronic health records (EHRs), an important step towards ADE surveillance and pharmacovigilance
    Role: Subaward PI

    R01MH112138     (Boudreaux, Kiefe)Sep 5, 2016 - Jun 30, 2021
    NIH/NIMH
    A System of Safety (SOS): Preventing Suicide through Healthcare System Transformation
    Role Description: To study the implementation of best practice suicide-related care processes that embody the Zero Suicide Essential Elements of Care across emergency departments, inpatient medical and behavioral health units, and primary care clinics associated with a large healthcare system
    Role: Co-I, Data Scientist, NLP Lead

    R01MH118220     (Boudreaux, Wang)Mar 1, 2019 - Nov 30, 2024
    NIH/NIMH
    Deriving a Clinical Decision Rule for Suicide Risk in the Emergency Department Setting
    Role Description: To derive a clinical decision rule to support universal suicide risk detection and optimize patient care workflow in adult patients.
    Role: Co-I, data scientist, leading machine learning-based risk prediction

    R01MH124685     (Boudreaux)Jan 1, 2021 - Nov 30, 2024
    NIH/NIMH
    Telehealth to Improve Prevention of Suicide (TIPS) in Eds
    Role Description: To evaluate whether telemental health evaluation and intervention services can successfully overcome poor access to behavioral health and substandard suicide-related care in emergency departments (EDs).
    Role: Co-I and Data Scientist

    R21CA269425     (Epstein, Liu)Sep 1, 2022 - Mar 31, 2025
    NIH/NCI
    Identifying Recurrent Non-Hodgkin Lymphoma in Electronic Health Data
    Role Description: To develop innovative computational methods to efficiently and accurately identify recurrent NHL in electronic health data. It is the first step towards large-scale, population-based analyses of this important yet understudied patient outcome
    Role: MPI

    R03MH130275     (Liu, Janamnuaysook, Phanuphak)Jul 1, 2023 - Jun 30, 2025
    NIH/NIMH
    Applying Deep Learning for Predicting Retention in PrEP Care and Effective PrEP Use among Key Populations at Risk for HIV in Thailand
    Role Description: To explore advanced machine learning techniques for identifying protective and risk factors for retention in PrEP care and effective PrEP use among key populations (men who have sex with men and transgender women) in Thailand.
    Role: MPI

    R21LM014032     (Liu)Sep 1, 2023 - Aug 30, 2025
    NIH/NLM
    DeepCertainty: Deep Learning for Contextual Diagnostic Uncertainty Measurement in Radiology Reports
    Role Description: To develop a deep learning-based natural language processing model, DeepCertainty, for accurately assessing the diagnostic uncertainty conveyed in CT pulmonary angiogram reports with interpretable evidence.
    Role: PI

    CAPES Pilot     (Liu)Oct 1, 2023 - Sep 30, 2024
    NIMH CAPES Center
    Multi-site Validation Study for Suicide Risk Prediction: Integrating the OHDSI Research Network
    Role Description: To integrate OMOP common data model and OHDSI network to facilitate validating machine learning-based suicide risk predictive modeling across healthcare institutions, clinical settings, and diverse sociodemographic groups (e.g., racial/ethnic minority populations).
    Role: PI

    R34 (P50 MH129701-5212)     (Liu, Rothschild)Oct 5, 2023 - Oct 4, 2026
    NIH/NIMH
    P50 MH129701-5212
    Role Description: To address the translation gap from research to clinical practice by systematically assessing and improving a suicide risk algorithm’s generalizability and adaptability from an original development setting to a new healthcare system
    Role: MPI

    Collapse Bibliographic 
    Collapse selected publications
    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
    Newest   |   Oldest   |   Most Cited   |   Most Discussed   |   Timeline   |   Field Summary   |   Plain Text
    PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. Ostropolets A, Albogami Y, Conover M, Banda JM, Baumgartner WA, Blacketer C, Desai P, DuVall SL, Fortin S, Gilbert JP, Golozar A, Ide J, Kanter AS, Kern DM, Kim C, Lai LYH, Li C, Liu F, Lynch KE, Minty E, Neves MI, Ng DQ, Obene T, Pera V, Pratt N, Rao G, Rappoport N, Reinecke I, Saroufim P, Shoaibi A, Simon K, Suchard MA, Swerdel JN, Voss EA, Weaver J, Zhang L, Hripcsak G, Ryan PB. Reproducible variability: assessing investigator discordance across 9 research teams attempting to reproduce the same observational study. J Am Med Inform Assoc. 2023 04 19; 30(5):859-868. PMID: 36826399.
      Citations: 1     Fields:    Translation:Humans
    2. Nagawa CS, Ito Fukunaga M, Faro JM, Liu F, Anderson E, Kamberi A, Orvek EA, Davis M, Pbert L, Cutrona SL, Houston TK, Sadasivam RS. Characterizing Pandemic-Related Changes in Smoking Over Time in a Cohort of Current and Former Smokers. Nicotine Tob Res. 2023 01 05; 25(2):203-210. PMID: 35137213.
      Citations: 7     Fields:    Translation:HumansPHPublic Health
    3. Wang B, Liu F, Deveaux L, Ash A, Gerber B, Allison J, Herbert C, Poitier M, MacDonell K, Li X, Stanton B. Predicting Adolescent Intervention Non-responsiveness for Precision HIV Prevention Using Machine Learning. AIDS Behav. 2023 May; 27(5):1392-1402. PMID: 36255592.
      Citations: 1     Fields:    Translation:Humans
    4. Dabbagh Z, McKee MD, Pirraglia PA, Clements KM, Liu F, Amante DJ, Shukla P, Gerber BS. The Expanding Use of Continuous Glucose Monitoring in Type 2 Diabetes. Diabetes Technol Ther. 2022 07; 24(7):510-515. PMID: 35231190.
      Citations: 4     Fields:    Translation:Humans
    5. Deer RR, Rock MA, Vasilevsky N, Carmody L, Rando H, Anzalone AJ, Basson MD, Bennett TD, Bergquist T, Boudreau EA, Bramante CT, Byrd JB, Callahan TJ, Chan LE, Chu H, Chute CG, Coleman BD, Davis HE, Gagnier J, Greene CS, Hillegass WB, Kavuluru R, Kimble WD, Koraishy FM, K?hler S, Liang C, Liu F, Liu H, Madhira V, Madlock-Brown CR, Matentzoglu N, Mazzotti DR, McMurry JA, McNair DS, Moffitt RA, Monteith TS, Parker AM, Perry MA, Pfaff E, Reese JT, Saltz J, Schuff RA, Solomonides AE, Solway J, Spratt H, Stein GS, Sule AA, Topaloglu U, Vavougios GD, Wang L, Haendel MA, Robinson PN. Characterizing Long COVID: Deep Phenotype of a Complex Condition. EBioMedicine. 2021 Dec; 74:103722. PMID: 34839263.
      Citations: 79     Fields:    Translation:HumansCells
    6. Sharafeldin N, Bates B, Song Q, Madhira V, Shao YR, Liu F, Bergquist T, Su J, Topaloglu U. Reply to K. Takada et al. J Clin Oncol. 2021 12 10; 39(35):3997-3998. PMID: 34623872.
      Citations:    Fields:    
    7. Liu F, Zhou P, Baccei SJ, Masciocchi MJ, Amornsiripanitch N, Kiefe CI, Rosen MP. Qualifying Certainty in Radiology Reports through Deep Learning-Based Natural Language Processing. AJNR Am J Neuroradiol. 2021 10; 42(10):1755-1761. PMID: 34413062.
      Citations: 3     Fields:    Translation:Humans
    8. Boudreaux ED, Rundensteiner E, Liu F, Wang B, Larkin C, Agu E, Ghosh S, Semeter J, Simon G, Davis-Martin RE. Applying Machine Learning Approaches to Suicide Prediction Using Healthcare Data: Overview and Future Directions. Front Psychiatry. 2021; 12:707916. PMID: 34413800.
      Citations:    
    9. Sharafeldin N, Bates B, Song Q, Madhira V, Yan Y, Dong S, Lee E, Kuhrt N, Shao YR, Liu F, Bergquist T, Guinney J, Su J, Topaloglu U. Outcomes of COVID-19 in Patients With Cancer: Report From the National COVID Cohort Collaborative (N3C). J Clin Oncol. 2021 07 10; 39(20):2232-2246. PMID: 34085538.
      Citations: 64     Fields:    Translation:Humans
    10. Wang B, Liu F, Deveaux L, Ash A, Gosh S, Li X, Rundensteiner E, Cottrell L, Adderley R, Stanton B. Adolescent HIV-related behavioural prediction using machine learning: a foundation for precision HIV prevention. AIDS. 2021 05 01; 35(Suppl 1):S75-S84. PMID: 33867490.
      Citations: 3     Fields:    Translation:Humans
    11. Rando HM, Bennett TD, Byrd JB, Bramante C, Callahan TJ, Chute CG, Davis HE, Deer R, Gagnier J, Koraishy FM, Liu F, McMurry JA, Moffitt RA, Pfaff ER, Reese JT, Relevo R, Robinson PN, Saltz JH, Solomonides A, Sule A, Topaloglu U, Haendel MA. Challenges in defining Long COVID: Striking differences across literature, Electronic Health Records, and patient-reported information. medRxiv. 2021 Mar 26. PMID: 33791733.
      Citations:    
    12. Liu F, Zheng X, Yu H, Tjia J. Neural Multi-Task Learning for Adverse Drug Reaction Extraction. AMIA Annu Symp Proc. 2020; 2020:756-762. PMID: 33936450.
      Citations:    Fields:    Translation:Humans
    13. Rawat BPS, Jagannatha A, Liu F, Yu H. Inferring ADR causality by predicting the Naranjo Score from Clinical Notes. AMIA Annu Symp Proc. 2020; 2020:1041-1049. PMID: 33936480.
      Citations: 5     Fields:    Translation:Humans
    14. Liu F, Wang B, Larkin C, Kiefe C, Boudreaux E. Identify suicidal encounters in emergency department (ED) setting using machine learning and natural language processing. APHA Annual Meeting and Expo. 2020.
    15. Peng C, He M, Cutrona SL, Kiefe CI, Liu F, Wang Z. Theme Trends and Knowledge Structure on Mobile Health Apps: Bibliometric Analysis. JMIR Mhealth Uhealth. 2020 07 27; 8(7):e18212. PMID: 32716312.
      Citations: 22     Fields:    Translation:Humans
    16. Liu F., Zheng X., Wang B., Kiefe C. DeepGeneMD: A Joint Deep Learning Model for Extracting Gene Mutation-Disease Knowledge from PubMed Literature. BioNLP-OST at Empirical Methods in Natural Language Processing (EMNLP). 2019.
    17. Liu F, Pradhan R, Druhl E, Freund E, Liu W, Sauer BC, Cunningham F, Gordon AJ, Peters CB, Yu H. Learning to detect and understand drug discontinuation events from clinical narratives. J Am Med Inform Assoc. 2019 10 01; 26(10):943-951. PMID: 31034028.
      Citations: 9     Fields:    Translation:Humans
    18. Liu F., Peng Y., Rosen M.P. An Effective Deep Transfer Learning and Information Fusion Framework for Medical Visual Question Answering. Experimental IR Meets Multilinguality, Multimodality, and Interaction. 2019; 11696.
    19. Li R, Hu B, Liu F, Liu W, Cunningham F, McManus DD, Yu H. Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach. JMIR Med Inform. 2019 Feb 08; 7(1):e10788. PMID: 30735140.
      Citations:    
    20. Jagannatha A, Liu F, Liu W, Yu H. Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0). Drug Saf. 2019 01; 42(1):99-111. PMID: 30649735.
      Citations: 46     Fields:    Translation:Humans
    21. Liu F, Jagannatha A, Yu H. Towards Drug Safety Surveillance and Pharmacovigilance: Current Progress in Detecting Medication and Adverse Drug Events from Electronic Health Records. Drug Saf. 2019 01; 42(1):95-97. PMID: 30649734.
      Citations: 18     Fields:    Translation:Humans
    22. Munkhdalai T, Liu F, Yu H. Clinical Relation Extraction Toward Drug Safety Surveillance Using Electronic Health Record Narratives: Classical Learning Versus Deep Learning. JMIR Public Health Surveill. 2018 Apr 25; 4(2):e29. PMID: 29695376.
      Citations:    
    23. Liu F, Chen J, Jagannatha A, Yu H. Learning for Biomedical Information Extraction: Methodological Review of Recent Advances. arXiv:1606.07993. 2016. View Publication.
    24. Liu F, Yu H. Learning to rank figures within a biomedical article. PLoS One. 2014; 9(3):e61567. PMID: 24625719.
      Citations: 2     Fields:    Translation:Humans
    25. Liu F, Moosavinasab S, Agarwal S, Bennett A, Yu H. Automatically Identifying Health- and Clinical-Related Content in Wikipedia. Proceedings of the 14th World Conference on Medical and Health Informatics (MEDINFO). 2013. View Publication.
    26. Liu F, Moosavinasab S, Houston TK, Yu H. MedTxting: learning based and knowledge rich SMS-style medical text contraction. AMIA Annu Symp Proc. 2012; 2012:558-67. PMID: 23304328.
      Citations:    Fields:    Translation:Humans
    27. Agarwal S, Liu F, Yu H. Simple and efficient machine learning frameworks for identifying protein-protein interaction relevant articles and experimental methods used to study the interactions. BMC Bioinformatics. 2011 Oct 03; 12 Suppl 8:S10. PMID: 22151701.
      Citations: 4     Fields:    Translation:Humans
    28. Liu F, Antieau LD, Yu H. Toward automated consumer question answering: automatically separating consumer questions from professional questions in the healthcare domain. J Biomed Inform. 2011 Dec; 44(6):1032-8. PMID: 21856442.
      Citations: 12     Fields:    Translation:Humans
    29. Liu F, Tur G, Hakkani-T?r D, Yu H. Towards spoken clinical-question answering: evaluating and adapting automatic speech-recognition systems for spoken clinical questions. J Am Med Inform Assoc. 2011 Sep-Oct; 18(5):625-30. PMID: 21705457.
      Citations: 6     Fields:    Translation:Humans
    30. Liu F, Liu F, Liu Y. A Supervised Framework for Keyword Extraction from Meeting Transcripts. IEEE Transactions on Audio, Speech and Language Processing. 2011; 19(3):538-548. View Publication.
    31. Cao Y, Liu F, Simpson P, Antieau L, Bennett A, Cimino JJ, Ely J, Yu H. AskHERMES: An online question answering system for complex clinical questions. J Biomed Inform. 2011 Apr; 44(2):277-88. PMID: 21256977.
      Citations: 43     Fields:    
    32. Liu F, Liu F, Liu Y. Learning from Chinese-English Parallel Data for Chinese Tense Prediction. Proceedings of International Joint Conference on Natural Language Processing (IJCNLP 2011). 2011. View Publication.
    33. Yu H, Liu F, Ramesh BP. Automatic figure ranking and user interfacing for intelligent figure search. PLoS One. 2010 Oct 07; 5(10):e12983. PMID: 20949102.
      Citations: 10     Fields:    
    34. Li Z, Liu F, Antieau L, Cao Y, Yu H. Lancet: a high precision medication event extraction system for clinical text. J Am Med Inform Assoc. 2010 Sep-Oct; 17(5):563-7. PMID: 20819865.
      Citations: 24     Fields:    Translation:Humans
    35. Cao Y, Li Z, Liu F, Agarwal S, Zhang Q, Yu H. An IR-aided machine learning framework for the BioCreative II.5 Challenge. IEEE/ACM Trans Comput Biol Bioinform. 2010 Jul-Sep; 7(3):454-61. PMID: 20671317.
      Citations: 3     Fields:    
    36. Liu F, Liu Y. Identification of Soundbite and Its Speaker Name Using Transcripts of Broadcast News Speech. ACM Transactions on Asian Language Information Processing. 2010; 9(1). View Publication.
    37. Liu F, Liu Y. Exploring Correlation between ROUGE and Human Evaluation on Meeting Summaries. IEEE Transactions on Audio, Speech and Language Processing. 2010; 18(1):187-196. View Publication.
    38. Liu F, Wang D, Li B, Liu Y. . Improving Blog Polarity Classification via Topic Analysis and Adaptive Methods. Proceedings of NAACL-HLT. 2010. View Publication.
    39. Liu F, Pennell D, Liu F, Liu Y. . Unsupervised Approaches to Automatic Keyword Extraction Using Meeting Transcripts. Proceedings of NAACL-HLT. 2009. View Publication.
    40. Liu F, Liu Y. . Correlation between ROUGE and Human Evaluation of Extractive Meeting Summaries. Proceedings of ACL. 2008. View Publication.
    41. Liu F, Liu Y. . Look Who is Talking: Soundbite Speaker Name Recognition in Broadcast News Speech. Proceedings of NAACL/HLT. 2007. View Publication.
    42. Liu F, Liu Y. Unsupervised Language Model Adaptation Incorporating Name Entity Information. Proceedings of ACL. 2007. View Publication.
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