AIMC Topic: Electronic Health Records

Clear Filters Showing 1691 to 1700 of 2670 articles

Using a Clinical Knowledge Base to Assess Comorbidity Interrelatedness Among Patients with Multiple Chronic Conditions.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Decision support tools increasingly integrate clinical knowledge such as medication indications and contraindications with electronic health record (EHR) data to support clinical care and patient safety. The availability of this encoded information a...

Handling Temporality of Clinical Events for Drug Safety Surveillance.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Using longitudinal data in electronic health records (EHRs) for post-marketing adverse drug event (ADE) detection allows for monitoring patients throughout their medical history. Machine learning methods have been shown to be efficient and effective ...

Finding Cervical Cancer Symptoms in Swedish Clinical Text using a Machine Learning Approach and NegEx.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Detection of early symptoms in cervical cancer is crucial for early treatment and survival. To find symptoms of cervical cancer in clinical text, Named Entity Recognition is needed. In this paper the Clinical Entity Finder, a machine-learning tool tr...

Towards a Generalizable Time Expression Model for Temporal Reasoning in Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Accurate temporal identification and normalization is imperative for many biomedical and clinical tasks such as generating timelines and identifying phenotypes. A major natural language processing challenge is developing and evaluating a generalizabl...

Data-driven Temporal Prediction of Surgical Site Infection.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Analysis of data from Electronic Health Records (EHR) presents unique challenges, in particular regarding nonuniform temporal resolution of longitudinal variables. A considerable amount of patient information is available in the EHR - including blood...

A Study of Concept Extraction Across Different Types of Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Our research investigates methods for creating effective concept extractors for specialty clinical notes. First, we present three new "specialty area" datasets consisting of Cardiology, Neurology, and Orthopedics clinical notes manually annotated wit...

Reviewing 741 patients records in two hours with FASTVISU.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The secondary use of electronic health records opens up new perspectives. They provide researchers with structured data and unstructured data, including free text reports. Many applications been developed to leverage knowledge from free-text reports,...

Development and Validation of an Algorithm to Identify Nonalcoholic Fatty Liver Disease in the Electronic Medical Record.

Digestive diseases and sciences
BACKGROUND AND AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. Risk factors for NAFLD disease progression and liver-related outcomes remain incompletely understood due to the lack of computa...

Outcome Prediction in Clinical Treatment Processes.

Journal of medical systems
Clinical outcome prediction, as strong implications for health service delivery of clinical treatment processes (CTPs), is important for both patients and healthcare providers. Prior studies typically use a priori knowledge, such as demographics or p...