AIMC Topic: Medical Records Systems, Computerized
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AI-Generated Draft Replies Integrated Into Health Records and Physicians' Electronic Communication.
JAMA network open
Apr 1, 2024
IMPORTANCE: Timely tests are warranted to assess the association between generative artificial intelligence (GenAI) use and physicians' work efforts.
Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Technique.
Journal of digital imaging
Aug 24, 2022
Since radiology reports needed for clinical practice and research are written and stored in free-text narrations, extraction of relative information for further analysis is difficult. In these circumstances, natural language processing (NLP) techniqu...
eARDS: A multi-center validation of an interpretable machine learning algorithm of early onset Acute Respiratory Distress Syndrome (ARDS) among critically ill adults with COVID-19.
PloS one
Sep 24, 2021
We present an interpretable machine learning algorithm called 'eARDS' for predicting ARDS in an ICU population comprising COVID-19 patients, up to 12-hours before satisfying the Berlin clinical criteria. The analysis was conducted on data collected f...
A Preliminary Characterization of Canonicalized and Non-Canonicalized Section Headers Across Variable Clinical Note Types.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
In the electronic health record, the majority of clinically relevant information is stored within clinical notes. Most clinical notes follow a set organizational structure composed of canonicalized section headers that facilitate clinical review and ...
AllergyMap: An Open Source Corpus of Allergy Mention Normalizations.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Allergy mention normalization is challenging because of the wide range of possible allergens including medications, foods, plants, animals, and consumer products. This paper describes the process of mapping free-text allergy information from an elect...
Ontological representation, classification and data-driven computing of phenotypes.
Journal of biomedical semantics
Dec 21, 2020
BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological studies. The development of computable...
Ethical Use of Electronic Health Record Data and Artificial Intelligence: Recommendations of the Primary Care Informatics Working Group of the International Medical Informatics Association.
Yearbook of medical informatics
Apr 17, 2020
OBJECTIVE: To create practical recommendations for the curation of routinely collected health data and artificial intelligence (AI) in primary care with a focus on ensuring their ethical use.
Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk.
Scientific reports
Jan 24, 2020
To compare different deep learning architectures for predicting the risk of readmission within 30 days of discharge from the intensive care unit (ICU). The interpretability of attention-based models is leveraged to describe patients-at-risk. Several ...
Use of Natural Language Processing to identify Obsessive Compulsive Symptoms in patients with schizophrenia, schizoaffective disorder or bipolar disorder.
Scientific reports
Oct 2, 2019
Obsessive and Compulsive Symptoms (OCS) or Obsessive Compulsive Disorder (OCD) in the context of schizophrenia or related disorders are of clinical importance as these are associated with a range of adverse outcomes. Natural Language Processing (NLP)...
Assessing data availability and quality within an electronic health record system through external validation against an external clinical data source.
BMC medical informatics and decision making
Jul 25, 2019
BACKGROUND: Approximately 20% of deaths in the US each year are attributable to smoking, yet current practices in the recording of this health risk in electronic health records (EHRs) have not led to discernable changes in health outcomes. Several gr...
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