AIMC Topic: Electronic Health Records

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Detecting Evidence of Intra-abdominal Surgical Site Infections from Radiology Reports Using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Free-text reports in electronic health records (EHRs) contain medically significant information - signs, symptoms, findings, diagnoses - recorded by clinicians during patient encounters. These reports contain rich clinical information which can be le...

Improving the 'Fitness for Purpose' of Common Data Models through Realism Based Ontology.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Common data models are designed and built based on requirements that are aimed towards fitness for purpose. But when common data models are used as lenses through which reality is observed from the perspective according to which they are built, then ...

Intelligent Word Embeddings of Free-Text Radiology Reports.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Radiology reports are a rich resource for advancing deep learning applications in medicine by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to th...

Leveraging text skeleton for de-identification of electronic medical records.

BMC medical informatics and decision making
BACKGROUND: De-identification is the first step to use these records for data processing or further medical investigations in electronic medical records. Consequently, a reliable automated de-identification system would be of high value.

Causal risk factor discovery for severe acute kidney injury using electronic health records.

BMC medical informatics and decision making
BACKGROUND: Acute kidney injury (AKI), characterized by abrupt deterioration of renal function, is a common clinical event among hospitalized patients and it is associated with high morbidity and mortality. AKI is defined in three stages with stage-3...

Automated ICD-9 Coding via A Deep Learning Approach.

IEEE/ACM transactions on computational biology and bioinformatics
ICD-9 (the Ninth Revision of International Classification of Diseases) is widely used to describe a patient's diagnosis. Accurate automated ICD-9 coding is important because manual coding is expensive, time-consuming, and inefficient. Inspired by the...

Machine Learning Methods to Extract Documentation of Breast Cancer Symptoms From Electronic Health Records.

Journal of pain and symptom management
CONTEXT: Clinicians document cancer patients' symptoms in free-text format within electronic health record visit notes. Although symptoms are critically important to quality of life and often herald clinical status changes, computational methods to a...

Deep neural models for ICD-10 coding of death certificates and autopsy reports in free-text.

Journal of biomedical informatics
We address the assignment of ICD-10 codes for causes of death by analyzing free-text descriptions in death certificates, together with the associated autopsy reports and clinical bulletins, from the Portuguese Ministry of Health. We leverage a deep n...