Use of unstructured text in prognostic clinical prediction models: a systematic review
Objective This systematic review aims to assess how information from unstructured text is
used to develop and validate clinical prognostic prediction models. We summarize the …
used to develop and validate clinical prognostic prediction models. We summarize the …
Machine learning applied to electronic health record data in home healthcare: a scoping review
Objective Despite recent calls for home healthcare (HHC) to integrate informatics, the
application of machine learning in HHC is relatively unknown. Thus, this study aimed to …
application of machine learning in HHC is relatively unknown. Thus, this study aimed to …
Home healthcare clinical notes predict patient hospitalization and emergency department visits
Background About 30% of home healthcare patients are hospitalized or visit an emergency
department (ED) during a home healthcare (HHC) episode. Novel data science methods are …
department (ED) during a home healthcare (HHC) episode. Novel data science methods are …
Artificial intelligence and clinical deterioration
Research-based AI-driven systems to predict clinical deterioration are increasingly being
developed, but few are being implemented into clinical workflows. Escobar et al.(AAM) …
developed, but few are being implemented into clinical workflows. Escobar et al.(AAM) …
Healthcare process modeling to phenotype clinician behaviors for exploiting the signal gain of clinical expertise (HPM-ExpertSignals): development and evaluation of …
SC Rossetti, C Knaplund, D Albers… - Journal of the …, 2021 - academic.oup.com
Objective There are signals of clinicians' expert and knowledge-driven behaviors within
clinical information systems (CIS) that can be exploited to support clinical prediction …
clinical information systems (CIS) that can be exploited to support clinical prediction …
[HTML][HTML] Healthcare related event prediction from textual data with machine learning: A Systematic Literature Review
In the field of healthcare, as well as many others, textual descriptions of events are logged.
With the use of Natural Language Processing (NLP), these texts are used to train event …
With the use of Natural Language Processing (NLP), these texts are used to train event …
Using nursing notes to improve clinical outcome prediction in intensive care patients: A retrospective cohort study
K Huang, TF Gray, S Romero-Brufau… - Journal of the …, 2021 - academic.oup.com
Objective Electronic health record documentation by intensive care unit (ICU) clinicians may
predict patient outcomes. However, it is unclear whether physician and nursing notes differ …
predict patient outcomes. However, it is unclear whether physician and nursing notes differ …
Principles for real-world implementation of bedside predictive analytics monitoring
LP Moorman - Applied Clinical Informatics, 2021 - thieme-connect.com
A new development in the practice of medicine is Artificial Intelligence-based predictive
analytics that forewarn clinicians of future deterioration of their patients. This proactive …
analytics that forewarn clinicians of future deterioration of their patients. This proactive …
The use of artificial intelligence and machine learning in surgery: a comprehensive literature review
Interest in the use of artificial intelligence (AI) and machine learning (ML) in medicine has
grown exponentially over the last few years. With its ability to enhance speed, precision, and …
grown exponentially over the last few years. With its ability to enhance speed, precision, and …
Explainable AI for clinical risk prediction: a survey of concepts, methods, and modalities
Recent advancements in AI applications to healthcare have shown incredible promise in
surpassing human performance in diagnosis and disease prognosis. With the increasing …
surpassing human performance in diagnosis and disease prognosis. With the increasing …