Benjamin Shickel
Orcid: 0000-0002-5304-7027
According to our database1,
Benjamin Shickel
authored at least 30 papers
between 2016 and 2024.
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Bibliography
2024
A multi-cohort study on prediction of acute brain dysfunction states using selective state space models.
CoRR, 2024
Temporal Cross-Attention for Dynamic Embedding and Tokenization of Multimodal Electronic Health Records.
CoRR, 2024
Acute kidney injury prediction for non-critical care patients: a retrospective external and internal validation study.
CoRR, 2024
Evaluation of General Large Language Models in Contextually Assessing Semantic Concepts Extracted from Adult Critical Care Electronic Health Record Notes.
CoRR, 2024
CIS-UNet: Multi-Class Segmentation of the Aorta in Computed Tomography Angiography via Context-Aware Shifted Window Self-Attention.
CoRR, 2024
2023
The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU).
CoRR, 2023
APRICOT: Acuity Prediction in Intensive Care Unit (ICU): Predicting Stability, Transitions, and Life-Sustaining Therapies.
CoRR, 2023
Identifying acute illness phenotypes via deep temporal interpolation and clustering network on physiologic signatures.
CoRR, 2023
Computable Phenotypes to Characterize Changing Patient Brain Dysfunction in the Intensive Care Unit.
CoRR, 2023
Dynamic Delirium Prediction in the Intensive Care Unit using Machine Learning on Electronic Health Records.
Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023
2022
Evaluation of federated learning variations for COVID-19 diagnosis using chest radiographs from 42 US and European hospitals.
J. Am. Medical Informatics Assoc., 2022
Frontiers Artif. Intell., 2022
Multi-dimensional patient acuity estimation with longitudinal EHR tokenization and flexible transformer networks.
Frontiers Digit. Health, 2022
Frontiers Digit. Health, 2022
2021
Deep Multi-Modal Transfer Learning for Augmented Patient Acuity Assessment in the Intelligent ICU.
Frontiers Digit. Health, 2021
Multi-Task Prediction of Clinical Outcomes in the Intensive Care Unit using Flexible Multimodal Transformers.
CoRR, 2021
2020
Interpretable Multi-Task Deep Neural Networks for Dynamic Predictions of Postoperative Complications.
CoRR, 2020
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data.
CoRR, 2020
Automatic Detection and Classification of Cognitive Distortions in Mental Health Text.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020
Automated Emotional Valence Prediction in Mental Health Text via Deep Transfer Learning.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020
2019
Added Value of Intraoperative Data for Predicting Postoperative Complications: Development and Validation of a MySurgeryRisk Extension.
CoRR, 2019
2018
Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis.
IEEE J. Biomed. Health Informatics, 2018
The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring.
CoRR, 2018
CoRR, 2018
2017
Hashtag Healthcare: From Tweets to Mental Health Journals Using Deep Transfer Learning.
CoRR, 2017
2016
Proceedings of the 3rd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, 2016
Proceedings of the 3rd Workshop on Computational Linguistics and Clinical Psychology: From Linguistic Signal to Clinical Reality, 2016
Proceedings of the Twenty-Ninth International Florida Artificial Intelligence Research Society Conference, 2016
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016