Clinical XLNet: Modeling sequential clinical notes and predicting prolonged mechanical ventilation
Clinical notes contain rich data, which is unexploited in predictive modeling compared to
structured data. In this work, we developed a new text representation Clinical XLNet for …
structured data. In this work, we developed a new text representation Clinical XLNet for …
[PDF][PDF] Predicting in-hospital mortality by combining clinical notes with time-series data
In intensive care units (ICUs), patient health is monitored through (1) continuous vital signals
from various medical devices, and (2) clinical notes consisting of opinions and summaries …
from various medical devices, and (2) clinical notes consisting of opinions and summaries …
Clinicalbert: Modeling clinical notes and predicting hospital readmission
Clinical notes contain information about patients that goes beyond structured data like lab
values and medications. However, clinical notes have been underused relative to structured …
values and medications. However, clinical notes have been underused relative to structured …
A customizable deep learning model for nosocomial risk prediction from critical care notes with indirect supervision
TR Goodwin, D Demner-Fushman - Journal of the American …, 2020 - academic.oup.com
Objective Reliable longitudinal risk prediction for hospitalized patients is needed to provide
quality care. Our goal is to develop a generalizable model capable of leveraging clinical …
quality care. Our goal is to develop a generalizable model capable of leveraging clinical …
Multimodal temporal-clinical note network for mortality prediction
H Yang, L Kuang, FQ Xia - Journal of Biomedical Semantics, 2021 - Springer
Background Mortality prediction is an important task to achieve smart healthcare, especially
for the management of intensive care unit. It can provide a reference for doctors to quickly …
for the management of intensive care unit. It can provide a reference for doctors to quickly …
Improving clinical outcome predictions using convolution over medical entities with multimodal learning
Early prediction of mortality and length of stay (LOS) of a patient is vital for saving a patient's
life and management of hospital resources. Availability of Electronic Health Records (EHR) …
life and management of hospital resources. Availability of Electronic Health Records (EHR) …
Combining structured and unstructured data for predictive models: a deep learning approach
Background The broad adoption of electronic health records (EHRs) provides great
opportunities to conduct health care research and solve various clinical problems in …
opportunities to conduct health care research and solve various clinical problems in …
Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients
Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes
and efficient utilization of resources. Accessibility of electronic health records (EHR) has …
and efficient utilization of resources. Accessibility of electronic health records (EHR) has …
Improving hospital mortality prediction with medical named entities and multimodal learning
Clinical text provides essential information to estimate the acuity of a patient during hospital
stays in addition to structured clinical data. In this study, we explore how clinical text can …
stays in addition to structured clinical data. In this study, we explore how clinical text can …
Comparison of neural language modeling pipelines for outcome prediction from unstructured medical text notes
Machine learning techniques and algorithm-based approaches are becoming more and
more vital to support clinical decision-making. In the medical area, natural language …
more vital to support clinical decision-making. In the medical area, natural language …