DeepCare: A Deep Dynamic Memory Model for Predictive Medicine

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A Novel and Reliable Framework of Patient Deterioration Prediction in Intensive Care Unit Based on Long Short-Term Memory-Recurrent Neural Network

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Distilling Knowledge from Publicly Available Online EMR Data to Emerging Epidemic for Prognosis

Ma, L., Ma, X., Gao, J., Jiao, X., Yu, Z., Zhang, C., Ruan, W., Wang, Y., Tang, W., & Wang, J. (2021) · International World Wide Web Conference (WWW) · doi:10.1145/3442381.3449855 · Cited by 27

Predicting unplanned readmissions in the intensive care unit: a multimodality evaluation

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Unveiling the frontiers of deep learning: Innovations shaping diverse domains

Ahmed, S. F., Alam, M. S. B., Kabir, M., Afrin, S., Rafa, S. J., Mehjabin, A., & Gandomi, A. H. (2025) · Applied Intelligence · doi:10.1007/s10489-025-06259-x · Cited by 30

Capturing Feature-Level Irregularity in Disease Progression Modeling

Zheng, K., Wang, W., Gao, J., Ngiam, K. Y., Ooi, B. C., & Yip, W. L. J. (2017) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3132847.3132944 · Cited by 27

AMRNN: attended multi-task recurrent neural networks for dynamic illness severity prediction

Chen, W., Long, G., Yao, L., & Sheng, Q. Z. (2019) · World Wide Web · doi:10.1007/s11280-019-00720-x · Cited by 26

STIDM: A Spatial and Temporal Aware Intrusion Detection Model

Han, X., Yin, R., Lü, Z., Jiang, B., Liu, Y., Liu, S., Wang, C., & Li, N. (2020) · IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) · doi:10.1109/trustcom50675.2020.00058 · Cited by 26

Introduction to Deep Learning

Indrakumari, R., Poongodi, T., & Singh, K. (2021) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-66519-7_1 · Cited by 26

Predicting healthcare trajectories from medical records: a deep learning approach

Pham, T., Tran, T., Phung, D., & Venkatesh, S. (2017) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2017.04.001 · Cited by 447

Temporal modeling of patient journeys using deep learning on longitudinal health records

Jasthi, V. N. (2024) · International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences · doi:10.37082/ijirmps.v12.i2.232692

Finding Algebraic Structure of Care in Time: A Deep Learning ApproachPreprint

Nguyen, P., Tran, T., & Venkatesh, S. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1711.07980 · Cited by 5

Multi-Way adaptive Time Aware LSTM for irregularly collected sequential ICU data

Cissoko, M. B. H., Castelain, V., & Lachiche, N. (2024) · Expert Systems with Applications · doi:10.1016/j.eswa.2024.125548 · Cited by 14

Predicting and interpreting healthcare trajectories from irregularly collected sequential patient data using AMITA

Cissoko, M. B. H., Castelain, V., & Lachiche, N. (2025) · Information Sciences · doi:10.1016/j.ins.2025.121977 · Cited by 3