Tyler J. Loftus

Orcid: 0000-0001-5354-443X

According to our database1, Tyler J. Loftus authored at least 15 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2024
Temporal Cross-Attention for Dynamic Embedding and Tokenization of Multimodal Electronic Health Records.
CoRR, 2024

2023
Commentary: Machine learning in clinical decision-making.
Frontiers Digit. Health, May, 2023

The Potential of Wearable Sensors for Assessing Patient Acuity in Intensive Care Unit (ICU).
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

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

Phenotype clustering in health care: A narrative review for clinicians.
Frontiers Artif. Intell., 2022

Personalized decision-making for acute cholecystitis: Understanding surgeon judgment.
Frontiers Digit. Health, 2022

2021
Editorial: Machine Learning in Clinical Decision-Making.
Frontiers Digit. Health, 2021

2020
Development of Computable Phenotype to Identify and Characterize Transitions in Acuity Status in Intensive Care Unit.
CoRR, 2020

Application of Deep Interpolation Network for Clustering of Physiologic Time Series.
CoRR, 2020

Interpretable Multi-Task Deep Neural Networks for Dynamic Predictions of Postoperative Complications.
CoRR, 2020

2019
Mysteries, Epistemological Modesty, and Artificial Intelligence in Surgery.
Frontiers Artif. Intell., 2019

Added Value of Intraoperative Data for Predicting Postoperative Complications: Development and Validation of a MySurgeryRisk Extension.
CoRR, 2019

2018
DeepSOFA: A Real-Time Continuous Acuity Score Framework using Deep Learning.
CoRR, 2018


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