Wang, Fei

Deep learning for healthcare: review, opportunities and challenges

Miotto, R., Wang, F., Wang, S., Jiang, X., & Dudley, J. T. (2018) · Briefings in Bioinformatics

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 3,076

Federated Learning for Healthcare Informatics

Xu, J., Glicksberg, B. S., Su, C., Walker, P., Bian, J., & Wang, F. (2021) · Journal of Healthcare Informatics Research

Privacy-Preserving Technologies in DataMachine Learning in Healthcare

Cited by 1,542

Federated Learning for Healthcare Informatics

Xu, J., Glicksberg, B. S., Su, C., Walker, P., Bian, J., & Wang, F. (2019) · arXiv

Privacy-Preserving Technologies in DataMachine Learning in Healthcare

Cited by 1,538

AI in Health: State of the Art, Challenges, and Future Directions

Wang, F., & Preininger, A. (2019) · Yearbook of Medical Informatics

Artificial Intelligence in Healthcare and EducationMachine Learning in Healthcare

Cited by 398

Federated Learning of Electronic Health Records Improves Mortality Prediction in Patients Hospitalized with COVID-19

Vaid, A., Jaladanki, S. K., Xu, J., Teng, S., Kumar, A., Lee, S., Somani, S., Paranjpe, I., Freitas, J. K. D., Wanyan, T., et al. (2020) · JMIR Medical Informatics

Machine Learning in HealthcarePrivacy-Preserving Technologies in Data

Cited by 253

Should Health Care Demand Interpretable Artificial Intelligence or Accept “Black Box” Medicine?

Wang, F., Kaushal, R., & Khullar, D. (2020) · Annals of Internal Medicine

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 244

Deep representation learning of patient data from Electronic Health Records (EHR): A systematic review

Si, Y., Du, J., Li, Z., Jiang, X., Miller, T., Wang, F., Jim Zheng, W., & Roberts, K. (2021) · Journal of Biomedical Informatics

Machine Learning in HealthcareElectronic Health Records Systems

Cited by 235

Predictive Modeling of the Hospital Readmission Risk from Patients’ Claims Data Using Machine Learning: A Case Study on COPD

Min, X., Yu, B., & Wang, F. (2019) · Scientific Reports

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 170

Algorithmic fairness in computational medicine

Xu, J., Xiao, Y., Wang, W. H., Ning, Y., Shenkman, E. A., Bian, J., & Wang, F. (2022) · eBioMedicine

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 170

AD-linked R47H- TREM2 mutation induces disease-enhancing microglial states via AKT hyperactivation

Sayed, F. A., Kodama, L., Fan, L., Carling, G. K., Udeochu, J. C., Le, D., Li, Q., Zhou, L., Wong, M. Y., Horowitz, R., et al. (2021) · Science Translational Medicine

Neuroinflammation and Neurodegeneration MechanismsAlzheimer's disease research and treatments

Cited by 155

Data-driven subtyping of Parkinson's disease using longitudinal clinical records: a cohort study

Zhang, X., Chou, J., Liang, J., Xiao, C., Zhao, Y., Sarva, H., Henchcliffe, C., & Wang, F. (2019) · Scientific Reports

Parkinson's Disease Mechanisms and TreatmentsMachine Learning in Healthcare

Cited by 137

Recent advances in biomedical literature mining

Zhao, S., Su, C., Lu, Z., & Wang, F. (2021) · Briefings in Bioinformatics

Biomedical Text Mining and OntologiesAdvanced Text Analysis Techniques

Cited by 134

A translational perspective towards clinical AI fairness

Liu, M., Ning, Y., Teixayavong, S., Mertens, M., Xu, J., Ting, D. S. W., Cheng, L. T.-E., Ong, J. C. L., Teo, Z. L., Tan, T. F., et al. (2023) · npj Digital Medicine

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 82

High-throughput target trial emulation for Alzheimer’s disease drug repurposing with real-world data

Zang, C., Zhang, H., Xu, J., Zhang, H., Fouladvand, S., Havaldar, S., Cheng, F., Chen, K., Chen, Y., Glicksberg, B. S., et al. (2023) · Nature Communications

Advanced Causal Inference TechniquesAlzheimer's disease research and treatments

Cited by 69

A scoping review on multimodal deep learning in biomedical images and texts

Sun, Z., Lin, M., Zhu, Q., Xie, Q., Wang, F., Lu, Z., & Peng, Y. (2023) · Journal of Biomedical Informatics

Multimodal Machine Learning ApplicationsArtificial Intelligence in Healthcare and Education

Cited by 69

A scoping review of fair machine learning techniques when using real-world data

Huang, Y., Guo, J., Chen, W.-H., Lin, H.-Y., Tang, H., Wang, F., Xu, H., & Bian, J. (2024) · Journal of Biomedical Informatics

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 61

Learning across Diverse Biomedical Data Modalities and Cohorts: Challenges and Opportunities for Innovation

Rajendran, S., Pan, W., Sabuncu, M. R., Chen, Y., Zhou, J., & Wang, F. (2024) · Patterns

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 47

Data heterogeneity in federated learning with Electronic Health Records: Case studies of risk prediction for acute kidney injury and sepsis diseases in critical care

Rajendran, S., Xu, Z., Pan, W., Ghosh, A., & Wang, F. (2023) · PLOS Digital Health

Machine Learning in HealthcarePrivacy-Preserving Technologies in Data

Cited by 46

Leveraging generative AI for clinical evidence synthesis needs to ensure trustworthiness

Zhang, G., Jin, Q., Jered McInerney, D., Chen, Y., Wang, F., Cole, C. L., Yang, Q., Wang, Y., Malin, B. A., Peleg, M., et al. (2024) · Journal of Biomedical Informatics

Artificial Intelligence in Healthcare and EducationMeta-analysis and systematic reviews

Cited by 40

TaGiTeD: Predictive Task Guided Tensor Decomposition for Representation Learning from Electronic Health Records

Yang, K., Li, X., Liu, H., Mei, J., Xie, G., Zhao, J., Xie, B., & Wang, F. (2017) · Proceedings of the AAAI Conference on Artificial Intelligence

Machine Learning in HealthcareTensor decomposition and applications

Cited by 30

DCMN: Double Core Memory Network for Patient Outcome Prediction with Multimodal Data

Feng, Y., Xu, Z., Gan, L., Chen, N., Yu, B., Chen, T., & Wang, F. (2019) · 2019 IEEE International Conference on Data Mining (ICDM)

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 15

Patient Similarity Learning with Selective Forgetting

Qian, W., Zhao, C., Shao, H., Chen, M., Wang, F., & Huai, M. (2022) · 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

Privacy-Preserving Technologies in DataMachine Learning in Healthcare

Cited by 11

Protocol for the development of a reporting guideline for causal and counterfactual prediction models in biomedicine

Xu, J., Guo, Y., Wang, F., Xu, H., Lucero, R., Bian, J., & Prosperi, M. (2022) · BMJ Open

Meta-analysis and systematic reviewsAdvanced Causal Inference Techniques

Cited by 6

Identification of outcome-oriented progression subtypes from mild cognitive impairment to Alzheimer's disease using electronic health records

Xu, J., Yin, R., Huang, Y., Gao, H., Wu, Y., Guo, J., Smith, G. E., DeKosky, S. T., Wang, F., Guo, Y., et al. (2023) · medRxiv

Dementia and Cognitive Impairment ResearchMachine Learning in Healthcare

Cited by 5