AIMC Topic: Electronic Health Records
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Class imbalance in out-of-distribution datasets: Improving the robustness of the TextCNN for the classification of rare cancer types.
Journal of biomedical informatics
Nov 22, 2021
In the last decade, the widespread adoption of electronic health record documentation has created huge opportunities for information mining. Natural language processing (NLP) techniques using machine and deep learning are becoming increasingly widesp...
Combining data augmentation and domain information with TENER model for Clinical Event Detection.
BMC medical informatics and decision making
Nov 16, 2021
BACKGROUND: In recent years, with the development of artificial intelligence, the use of deep learning technology for clinical information extraction has become a new trend. Clinical Event Detection (CED) as its subtask has attracted the attention fr...
Development and Validation of a Natural Language Processing Tool to Identify Injuries in Infants Associated With Abuse.
Academic pediatrics
Nov 12, 2021
OBJECTIVES: Medically minor but clinically important findings associated with physical child abuse, such as bruises in pre-mobile infants, may be identified by frontline clinicians yet the association of these injuries with child abuse is often not r...
Natural language processing of head CT reports to identify intracranial mass effect: CTIME algorithm.
The American journal of emergency medicine
Nov 9, 2021
BACKGROUND: The Mortality Probability Model (MPM) is used in research and quality improvement to adjust for severity of illness and can also inform triage decisions. However, a limitation for its automated use or application is that it includes the v...
Identification of asthma control factor in clinical notes using a hybrid deep learning model.
BMC medical informatics and decision making
Nov 9, 2021
BACKGROUND: There are significant variabilities in guideline-concordant documentation in asthma care. However, assessing clinician's documentation is not feasible using only structured data but requires labor-intensive chart review of electronic heal...
Identification of Uncontrolled Symptoms in Cancer Patients Using Natural Language Processing.
Journal of pain and symptom management
Nov 4, 2021
CONTEXT: For patients with cancer, uncontrolled pain and other symptoms are the leading cause of unplanned hospitalizations. Early access to specialty palliative care (PC) is effective to reduce symptom burden, but more efficient approaches are neede...
Using explainable machine learning to identify patients at risk of reattendance at discharge from emergency departments.
Scientific reports
Nov 2, 2021
Short-term reattendances to emergency departments are a key quality of care indicator. Identifying patients at increased risk of early reattendance could help reduce the number of missed critical illnesses and could reduce avoidable utilization of em...
Interpretable time-aware and co-occurrence-aware network for medical prediction.
BMC medical informatics and decision making
Nov 2, 2021
BACKGROUND: Disease prediction based on electronic health records (EHRs) is essential for personalized healthcare. But it's hard due to the special data structure and the interpretability requirement of methods. The structure of EHR is hierarchical: ...
Development and Validation of a Deep Learning Model for Earlier Detection of Cognitive Decline From Clinical Notes in Electronic Health Records.
JAMA network open
Nov 1, 2021
IMPORTANCE: Detecting cognitive decline earlier among older adults can facilitate enrollment in clinical trials and early interventions. Clinical notes in longitudinal electronic health records (EHRs) provide opportunities to detect cognitive decline...
Novelelectronic health records applied for prediction of pre-eclampsia: Machine-learning algorithms.
Pregnancy hypertension
Oct 28, 2021
OBJECTIVE: To predict risk of pre-eclampsia (PE) in women using machine learning (ML) algorithms, based on electronic health records (EHR) collected at the early second trimester.
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