• Awards

    • Singapore Data Science Consortium Dissertation Research Fellowship (PhD student) 2021
    • Second runner-up Physionet Challenge 2020                                                                
    • Finalist for MedTech Innovator Asia Pacific 2020
    • Graduate Student Research Award (my PhD student) 2020
    • Gold and Silver medals for Kaggle Medical Imaging AI competitions 2019
    • 1st Runner-up ISIC 2018: Skin Lesion Analysis Towards Melanoma Detection Competition,  2018
    • Top 5 (Team “Eagle Eye”) in The Digital Mammography DREAM Challenge 2017
    • Merit Award of MINDEF Data Challenge and Hackathon 2015
    • McKinsey Insight Program, 2015
    • MIT Teaching & Learning Laboratory Kaufman Teaching Certificate, 2015
    • Second runner-up of Best Student Paper Award, KDD Working Group, AMIA, 2014

    Ongoing Research Grants

    • Co-Principal Investigator, “JARVIS: Transforming Chronic Care for Diabetes, Hypertension and HyperLipidemia (DHL) with AI”, AI Singapore, S$25 Mil                                                                                                                                        2021 ~ 2026
    • Principal Investigator, “Surgical Risk Stratification and Outcomes Prediction”, AI Singapore 100E program (sponsored by Singapore General Hospital), S$350,000                                                                                                                           2020~2022
    • Co-Principal Investigator, “Automating the detection of frailty”, NUHS Seed Grant, S$95,000         2020~2022
    • Principal Investigator, “An AI assistant to radiologists that reads mammograms to automatically detect breast cancers and generate diagnostic reports: a technology combines the learning of images and free text”, Ministry of Health, Health Service Research Grant, S$1.04 Mil          2018~2022
    • Co-Principal Investigator, “An Explainable AI System for Community Care”, AI.SG Healthcare Grand Challenge, S$5 Mil       2019-2021
    • Co-Investigator “Development of a novel imaging-based machine-learning algorithm for the screening of osteoporosis using dental radiographs”, iHealthTech, $100K                                                                                                                                 2019-2021
    • Principal Investigator, “Al Assisted Breast Cancer Diagnosis: Prototype Develop and Clinical Validation”, Singapore-MIT Alliance Research and Technology, S$244K                                                                                                                               2019-2021
    • Co-Investigator, “Automatic X-ray fracture detection using deep machine learningfactors impacting model performance”, NUHS Seed Grant, S$172K        2019-2021
    • Principal Investigator, “Artificial Intelligence Models to Assist Breast Cancer Diagnosis with Mammogram Image Data”, NUHS, S$167K           2018~2020
    • Principal Investigator, NUS-USydn Joint Research and Joint Seminar Grant, S$40K                       2020~2021
    • Principal Investigator, JSPS-NUS Joint Research and Joint Seminar Grant, S$38K                         2018~2019
    • Co-Investigator, Clinical Scientist Award, NUHS, $3 Mil                                                           2017~2022
    • Co-Investigator, National Medical Research Council, Center Grant in collaboration with Khoo Teck Puat Hospital, S$1.5 Mil           2017~2022

    Recent Professional Service

    • International Advisory Board, “Lancet Digital Health”                                                                
    • Editorial Board member, “Applied Clinical Information Journal”                                                
    • Reviewer, Radiology: Artificial Intelligence                                                                            
    • Reviewer, Signal, Image and Video Processing (SIVP)                                                            
    • Reviewer, Nature Scientific Data                                                                                         
    • Editorial board member, “Healthcare Data Science” Journal                                                   
    • Chapter Chair, OHDSI, Singapore                                                                                        
    • Program Committee, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)    
    • Reviewer, Journal of Medical Internet Research                                                                         
    • Reviewer, Informatics (Journal),                                                                                        

    Research Interests

    • Artificial Intelligence Solutions for Healthcare Challenges
    • Casual Inference for Evidence-based Medicine
    • Deep learning models for medical image analysis
    • Generative models, such as Generative Adversarial Network (GAN), for Medical Time Series Analysis
    • Reinforcement Learning and Recommendation System for Treatment Optimization
    • Federated Learning for Cross-Institute Research
  • Selected Publications

    1. Ng D, Lan X, Yao MM, Chan WP, Mengling Feng. Federated learning: a collaborative effort to achieve better medical imaging models for individual sites that have small labelled datasets. Quantitative Imaging in Medicine and Surgery. 2021 Feb;11(2):852.
    2. Liu, S., See, K.C., Ngiam, K.Y., Celi, L.A., Sun, X. and Mengling Feng., 2020. Reinforcement learning for clinical decision support in critical care: comprehensive review. Journal of medical Internet research22(7), p.e18477 (IF 5.3).
    3. van den Boom, W., Hoy, M., Sankaran, J., Liu, M., Chahed, H.,  See, K.C and Mengling Feng., 2020. The search for optimal oxygen saturation targets in critically ill patients: observational data from large ICU databasesChest (IF 9.65)157(3), pp.566-573.
    4. Mengling Feng, et al. "Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms." JAMA network open 3.3 (2020): e200265-e200265 (IF 5).
    5. Mengling Feng et al. Transthoracic Echocardiography and Mortality in Sepsis: Analysis of the MIMIC-III Database. Intensive Care Medicine (IF 12). In press.
    6. Fuchs, Lior, Matthew Anstey, Mengling Feng, Ronen Toledano, Slava Kogan, Michael D. Howell, Peter Clardy, Leo Celi, Daniel Talmor, and Victor Novack. Quantifying the mortality impact of do-not-resuscitate orders in the ICU. Critical care medicine (IF 7.05) 45, no. 6 (2017): 1019-1027.