التفاصيل البيبلوغرافية
| العنوان: |
Sensitivity and Specificity aggregated across all timepoints for each test-set, for SWIFT models using 1, 2, 3, 4 and 5 prior inputs. |
| المؤلفون: |
Akshaya V. Annapragada (10204226), Joseph L. Greenstein (11276514), Sanjukta N. Bose (11276511), Bradford D. Winters (11864597), Sridevi V. Sarma (6647354), Raimond L. Winslow (11276517) |
| سنة النشر: |
2021 |
| المجموعة: |
Smithsonian Institution: Digital Repository |
| مصطلحات موضوعية: |
Molecular Biology, Biotechnology, Developmental Biology, Cancer, Science Policy, Infectious Diseases, Virology, Biological Sciences not elsewhere classified, poor clinical outcomes, optimal resource allocation, div >< p, deep learning model, deep learning approach, identifying patients likely, inform clinical interventions, w , f , critically ill patients, , 19 patients, critically ill, significant driver, patient triaging, novel data, hypoxemic events, effective intervention, echnique ), cardiac arrest, brain injury, average mse |
| الوصف: |
2 prior inputs is the model architecture used for SWIFT-5 and SWIFT-30 presented in the paper. For SWIFT-5, 2 prior inputs corresponds to 10 minutes of prior data input, while for SWIFT-30, 2 prior inputs corresponds to 60 minutes of prior data. (TIF) |
| نوع الوثيقة: |
still image |
| اللغة: |
unknown |
| Relation: |
https://figshare.com/articles/figure/Sensitivity_and_Specificity_aggregated_across_all_timepoints_for_each_test-set_for_SWIFT_models_using_1_2_3_4_and_5_prior_inputs_/17323619 |
| DOI: |
10.1371/journal.pcbi.1009712.s002 |
| الاتاحة: |
https://doi.org/10.1371/journal.pcbi.1009712.s002 |
| Rights: |
CC BY 4.0 |
| رقم الانضمام: |
edsbas.E31CC7BF |
| قاعدة البيانات: |
BASE |