Grants per year
Personal profile
Research Interests
His research interests include machine learning, natural language processing, time series analysis, integrative genomic analysis and big data analytics, with a focus on medical and clinical applications. He is the Chief AI Scientist at Northwestern University Clinical and Translational Sciences Institute (NUCATS).
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Electrical Engineering and Computer Science, PhD, MIT
… → 2015
Research interests keywords
- Autism Spectrum Disorders
- Bioinformatics
- Biomedical Ontologies
- Blood Cancer (leukemia and lymphomas)
- Computational Biology
- Critical Care
- Genomics
- Medical Informatics
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Dive into the research topics where Yuan Luo is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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A Family-Genetic Study of Language in Autism
Losh, M. C., Cole, J. S., Goldrick, M. A., Kraus, N., Krizman, J. L., Lau, J. C., Luo, Y., Norton, E. S., Speights, M. L. & Voigt, R.
National Institute on Deafness and Other Communication Disorders
9/1/23 → 6/30/28
Project: Research project
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Precise Prediction and Treatment of Seizures After Intracranial Hemorrhage
Naidech, A. M., Naidech, A. M., Cella, D., Cella, D., Luo, Y., Luo, Y., Schuele, S. U., Schuele, S. U., Tipton, E. & Tipton, E.
National Institute of Neurological Disorders and Stroke
4/1/23 → 3/31/28
Project: Research project
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Personalized risk assessment in Neurofibromatosis
Washington University in St. Louis, National Institute of Neurological Disorders and Stroke
4/1/23 → 3/31/27
Project: Research project
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A comparative study of pretrained language models for long clinical text
Li, Y., Wehbe, R. M., Ahmad, F. S., Wang, H. & Luo, Y., Jan 18 2023, In: Journal of the American Medical Informatics Association : JAMIA. 30, 2, p. 340-347 8 p.Research output: Contribution to journal › Article › peer-review
9 Scopus citations -
A comprehensive SARS-CoV-2–human protein–protein interactome reveals COVID-19 pathobiology and potential host therapeutic targets
Zhou, Y., Liu, Y., Gupta, S., Paramo, M. I., Hou, Y., Mao, C., Luo, Y., Judd, J., Wierbowski, S., Bertolotti, M., Nerkar, M., Jehi, L., Drayman, N., Nicolaescu, V., Gula, H., Tay, S., Randall, G., Wang, P., Lis, J. T., Feschotte, C., & 3 others, Jan 2023, In: Nature biotechnology. 41, 1, p. 128-139 12 p.Research output: Contribution to journal › Article › peer-review
Open Access30 Scopus citations -
Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: International observational federated study based on electronic health records through the 4CE consortium
The Consortium For Clinical Characterization Of COVID-19 By EHR (4CE), Jan 2023, In: PloS one. 18, 1 January, e0266985.Research output: Contribution to journal › Article › peer-review
Open Access2 Scopus citations -
AD-BERT: Using pre-trained language model to predict the progression from mild cognitive impairment to Alzheimer's disease
Mao, C., Xu, J., Rasmussen, L., Li, Y., Adekkanattu, P., Pacheco, J., Bonakdarpour, B., Vassar, R., Shen, L., Jiang, G., Wang, F., Pathak, J. & Luo, Y., Aug 2023, In: Journal of Biomedical Informatics. 144, 104442.Research output: Contribution to journal › Article › peer-review
1 Scopus citations -
Artificial intelligence-based clinical decision support in pediatrics
Ramgopal, S., Sanchez-Pinto, L. N., Horvat, C. M., Carroll, M. S., Luo, Y. & Florin, T. A., Jan 2023, In: Pediatric research. 93, 2, p. 334-341 8 p.Research output: Contribution to journal › Review article › peer-review
10 Scopus citations
Datasets
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Metadata record for the manuscript: Preoperative magnetic resonance imaging use and oncologic outcomes in premenopausal breast cancer patients
Zeng, Z. (Contributor), Amin, A. (Creator), Roy, A. (Contributor), Pulliam, N. E. (Creator), Karavites, L. C. (Creator), Espino, S. (Contributor), Helenowski, I. (Creator), Li, X. (Contributor), Luo, Y. (Creator) & Khan, S. A. (Creator), figshare, 2020
DOI: 10.6084/m9.figshare.12777140, https://springernature.figshare.com/articles/dataset/Metadata_record_for_the_manuscript_Preoperative_magnetic_resonance_imaging_use_and_oncologic_outcomes_in_premenopausal_breast_cancer_patients/12777140
Dataset
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Datasets and metadata supporting the published article: Somatic Genetic Aberrations in Benign Breast Disease and the Risk of Subsequent Breast Cancer
Zeng, Z. (Contributor), Vo, A. (Creator), Li, X. (Contributor), Shidfar, A. (Creator), Saldana, P. (Creator), Blanco Jr, L. Z. (Creator), Xuei, X. (Contributor), Luo, Y. (Creator), Khan, S. A. (Creator) & Clare, S. E. (Creator), figshare, 2020
DOI: 10.6084/m9.figshare.12191793.v1, https://springernature.figshare.com/articles/Datasets_and_metadata_supporting_the_published_article_Somatic_Genetic_Aberrations_in_Benign_Breast_Disease_and_the_Risk_of_Subsequent_Breast_Cancer/12191793/1
Dataset
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Additional file 1 of Deep learning for cancer type classification and driver gene identification
Zeng, Z. (Creator), Mao, C. (Creator), Vo, A. (Creator), Li, X. (Creator), Nugent, J. O. (Creator), Khan, S. A. (Creator), Clare, S. E. (Creator) & Luo, Y. (Creator), figshare, 2021
DOI: 10.6084/m9.figshare.16864948, https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Deep_learning_for_cancer_type_classification_and_driver_gene_identification/16864948
Dataset
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Sepsis subphenotyping based on organ dysfunction trajectory
Xu, Z. (Creator), Mao, C. (Creator), Su, C. (Creator), Zhang, H. (Creator), Siempos, I. (Creator), Torres, L. K. (Creator), Pan, D. (Creator), Luo, Y. (Creator), Schenck, E. J. (Creator), Wang, F. (Creator), Su, C. (Creator), Pan, D. (Creator), Luo, Y. (Creator) & Wang, F. (Creator), figshare, 2022
DOI: 10.6084/m9.figshare.c.6077785.v1, https://springernature.figshare.com/collections/Sepsis_subphenotyping_based_on_organ_dysfunction_trajectory/6077785/1
Dataset
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Comparison between machine learning methods for mortality prediction for sepsis patients with different social determinants
Wang, H. (Creator), Li, Y. (Creator), Naidech, A. M. (Creator), Luo, Y. (Creator) & Luo, Y. (Creator), figshare, 2022
DOI: 10.6084/m9.figshare.c.6051531, https://springernature.figshare.com/collections/Comparison_between_machine_learning_methods_for_mortality_prediction_for_sepsis_patients_with_different_social_determinants/6051531
Dataset