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Redundancy-aware topic modeling for patient record notes
The clinical notes in a given patient record contain much redundancy, in large part due to
clinicians' documentation habit of copying from previous notes in the record and pasting into …
clinicians' documentation habit of copying from previous notes in the record and pasting into …
Utilizing uncoded consultation notes from electronic medical records for predictive modeling of colorectal cancer
Objective Machine learning techniques can be used to extract predictive models for
diseases from electronic medical records (EMRs). However, the nature of EMRs makes it …
diseases from electronic medical records (EMRs). However, the nature of EMRs makes it …
Mining the clinical narrative: All text are not equal
Over the past decade, the application of data science techniques to clinical data has allowed
practitioners and researchers to develop a sundry of analytical models. These models have …
practitioners and researchers to develop a sundry of analytical models. These models have …
[PDF][PDF] A comparison of dimensionality reduction techniques for unstructured clinical text
Much of clinical data is free text, which is challenging to use together with machine learning,
visualization tools, and clinical decision rules. In this paper, we compare supervised and …
visualization tools, and clinical decision rules. In this paper, we compare supervised and …
Modeling clinical context: rediscovering the social history and evaluating language from the clinic to the wards
Social, behavioral, and cultural factors are clearly linked to health and disease outcomes.
The medical social history is a critical evaluation of these factors performed by healthcare …
The medical social history is a critical evaluation of these factors performed by healthcare …
[ספר][B] Machine learning for disease prediction
AJ Frandsen - 2016 - search.proquest.com
Millions of people in the United States alone suffer from undiagnosed or late-diagnosed
chronic diseases such as Chronic Kidney Disease and Type II Diabetes. Catching these …
chronic diseases such as Chronic Kidney Disease and Type II Diabetes. Catching these …
Supervised embedding of textual predictors with applications in clinical diagnostics for pediatric cardiology
Objective Electronic health records possess critical predictive information for machine-
learning-based diagnostic aids. However, many traditional machine learning methods fail to …
learning-based diagnostic aids. However, many traditional machine learning methods fail to …
Leveraging structural characteristics of interdependent networks to model non-linear cascading risks
This paper describes our continuing efforts to forge new ground in identifying the effects of
interdependency on acquisition and, if needed, uncovering early indicators of …
interdependency on acquisition and, if needed, uncovering early indicators of …
[PDF][PDF] Exploring temporal patterns in emergency department triage notes with topic models
Topic modeling is an unsupervised machine-learning task of discovering topics, the
underlying thematic structure in a text corpus. Dynamic topic models are capable of …
underlying thematic structure in a text corpus. Dynamic topic models are capable of …
Beyond Modeling: The Emergent Role of Informatics in Advancing Healthcare Knowledge
KJ Feldman - 2018 - curate.nd.edu
Throughout the history of modern medicine the observation of patient characteristics, health,
and treatment has been driven by a desire to advance knowledge around human health and …
and treatment has been driven by a desire to advance knowledge around human health and …