Projects per year
Personal profile
Education
- 2014-2018 Ph.D., Department of Computer Science and Engineering, Yuan Ze University
- 2012-2014 M.S., Department of Computer Science and Engineering, Yuan Ze University
- 2005-2010 B.Eng., Information Technology, Da Lat University, Vietnam
Experience
- 2023.02- Associate Professor, International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University
- 2023.02- Associate Professor, Professional Master Program in Artificial Intelligence in Medicine, Taipei Medical University
- 2020.06-2023.01 Assistant Professor, International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University
- 2019.08-2023.01 Assistant Professor, Professional Master Program in Artificial Intelligence in Medicine, Taipei Medical University
- 2018.08-2019.08 Postdoctoral Research Fellow, School of Humanities, Nanyang Technological University, Singapore
Awards
- TMU Research Paper Excellence Award 2023 (Taipei Medical University)
- TMU Young Scholar Research Award 2023 (Taipei Medical University)
- Outstanding Curriculum Award for Open Education 2023 (Taiwan Open Curriculum and Education Consortium - TOCEC)
- Creative Award (2023 H.Spectrum+)
- Best Oral Presenter Award (20th Asia Pacific Bioinformatics Conference-APBC2022)
- TMU Excellent Research Paper Award (Taipei Medical University)
- Future Tech Awards (Taiwan FUTEX 2021)
Research Interests
- Artificial Intelligence (Machine Learning & Deep Learning)
- Bioinformatics & Computational Biology
- Genomics, Proteomics, Radiomics
- Medical informatics
Related Link
Fingerprint
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- 1 Similar Profiles
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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運用圖變換器和深度表示學習預測基於序列的蛋白質功能(3/3)
Le, N. Q. K. (PI)
8/1/24 → 7/31/25
Project: A - Government Institution › b - National Science and Technology Council
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Sequence-Based Protein Function Prediction Using Graph Transformers and Deep Representative Learning
Le, N. Q. K. (PI)
8/1/22 → 7/31/25
Project: A - Government Institution › b - National Science and Technology Council
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運用圖變換器和深度表示學習預測基於序列的蛋白質功能(2/3)
Le, N. Q. K. (PI)
8/1/23 → 7/31/24
Project: A - Government Institution › b - National Science and Technology Council
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非小細胞肺癌的可解釋基因分型：基於CT放射組學之可解釋人工智慧
Le, N. Q. K. (PI)
1/1/23 → 12/31/23
Project: B - Project of TMU › h - Higher Education Sprout Project
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Deepnlp-Dna: a Pre-Trained Nlp Model for Dna Sequence Representation Using Deep Transformers and 2d Convolutional Neural Networks
Le, N. Q. K. (PI)
8/1/22 → 7/31/23
Project: A - Government Institution › b - National Science and Technology Council
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A computational predictor for autophagy-related proteins using interpretable machine learning and genetic algorithm
Nguyen, N. T. K., Vo, T. H., Lin, S. H. & Le, N. Q. K., Mar 2024, In: Gene Reports. 34, 101876.Research output: Contribution to journal › Article › peer-review
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Application of data science and bioinformatics in RNA therapeutics
Thi, H. V., Hoang, T.-N., Le, N. Q. K. & Chu, D.-T., 2024, RNA Therapeutics Part A. Chu, D.-T. & Than, V. T. (eds.). Academic Press, Vol. 203. p. 83-97 15 p. (Progress in Molecular Biology and Translational Science).Research output: Chapter in Book/Report/Conference proceeding › Chapter
2 Citations (Scopus) -
Artificial intelligence in time-lapse system: advances, applications, and future perspectives in reproductive medicine
Luong, T. M. T. & Le, N. Q. K., Feb 2024, In: Journal of Assisted Reproduction and Genetics. 41, 2, p. 239-252 14 p.Research output: Contribution to journal › Review article › peer-review
5 Citations (Scopus) -
Beyond black-box models: explainable AI for embryo ploidy prediction and patient-centric consultation
Luong, T. M. T., Ho, N. T., Hwu, Y. M., Lin, S. Y., Ho, J. Y. P., Wang, R. S., Lee, Y. X., Tan, S. J., Lee, Y. R., Huang, Y. L., Hsu, Y. C., Le, N. Q. K. & Tzeng, C. R., 2024, (Accepted/In press) In: Journal of Assisted Reproduction and Genetics. 41, 9, p. 2349-2358 10 p.Research output: Contribution to journal › Article › peer-review
2 Citations (Scopus) -
Deep Learning-based Integrated System for Intraoperative Blood Loss Quantification in Surgical Sponges
Nguyen, D., Le, M. H. N., Huynh, P. K., Le, T. Q., Charles-Okezie, C., Diaz, M. J., Sabet, C., Dang, H. T., Nguyen, T., Nguyen, H., Tran, M., Le, N. Q. K. & Muncey, A., 2024, (Accepted/In press) In: IEEE Journal of Biomedical and Health Informatics.Research output: Contribution to journal › Article › peer-review
Datasets
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Additional file 4 of TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings
Ho, Q.-T. (Contributor), Phan, D.-V. (Contributor), Ou, Y.-Y. (Contributor), Nguyen, T.-T.-D. (Contributor) & Le, N.-Q.-K. (Contributor), Figshare, 2020
DOI: 10.6084/m9.figshare.13126671.v1, https://doi.org/10.6084%2Fm9.figshare.13126671.v1
Dataset
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Additional file 2 of TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings
Phan, D.-V. (Contributor), Le, N.-Q.-K. (Contributor), Ou, Y.-Y. (Contributor), Ho, Q.-T. (Contributor) & Nguyen, T.-T.-D. (Contributor), Figshare, 2020
DOI: 10.6084/m9.figshare.13126665.v1, https://doi.org/10.6084%2Fm9.figshare.13126665.v1
Dataset
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TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings
Nguyen, T.-T.-D. (Contributor), Le, N.-Q.-K. (Contributor), Ho, Q.-T. (Contributor), Phan, D.-V. (Contributor) & Ou, Y.-Y. (Contributor), Figshare, 2020
DOI: 10.6084/m9.figshare.c.5182812.v1, https://springernature.figshare.com/collections/TNFPred_identifying_tumor_necrosis_factors_using_hybrid_features_based_on_word_embeddings/5182812/1
Dataset
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Additional file 3 of TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings
Phan, D.-V. (Contributor), Le, N.-Q.-K. (Contributor), Ho, Q.-T. (Contributor), Ou, Y.-Y. (Contributor) & Nguyen, T.-T.-D. (Contributor), Figshare, 2020
DOI: 10.6084/m9.figshare.13126668.v1, https://doi.org/10.6084%2Fm9.figshare.13126668.v1
Dataset
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Additional file 5 of TNFPred: identifying tumor necrosis factors using hybrid features based on word embeddings
Ho, Q.-T. (Contributor), Nguyen, T.-T.-D. (Contributor), Le, N.-Q.-K. (Contributor), Ou, Y.-Y. (Contributor) & Phan, D.-V. (Contributor), Figshare, 2020
DOI: 10.6084/m9.figshare.13126674.v1, https://doi.org/10.6084%2Fm9.figshare.13126674.v1
Dataset