Practice Management

Information Technology

Latest AI and machine learning research in information technology for healthcare professionals.

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ProFUSO: Business process and ontology-based framework to develop ubiquitous computing support systems for chronic patients' management.

New advances in telemedicine, ubiquitous computing, and artificial intelligence have supported the e...

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

BACKGROUND: Acute kidney injury (AKI), characterized by abrupt deterioration of renal function, is a...

Matching biomedical ontologies based on formal concept analysis.

BACKGROUND: The goal of ontology matching is to identify correspondences between entities from diffe...

Mobile technology and telemedicine for shoulder range of motion: validation of a motion-based machine-learning software development kit.

BACKGROUND: Mobile technology offers the prospect of delivering high-value care with increased patie...

Ensemble of shape functions and support vector machines for the estimation of discrete arm muscle activation from external biceps 3D point clouds.

BACKGROUND: Muscle activation level is currently being captured using impractical and expensive devi...

Using Technology in Global Otolaryngology.

Technology is integral to the diverse diagnostics and interventions of Otolaryngology. Historically,...

Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.

With the proliferation of heterogeneous health care data in the last three decades, biomedical ontol...

Informatics and machine learning to define the phenotype.

For the past decade, the focus of complex disease research has been the genotype. From technological...

Automated chart review utilizing natural language processing algorithm for asthma predictive index.

BACKGROUND: Thus far, no algorithms have been developed to automatically extract patients who meet A...

Ascertainment of asthma prognosis using natural language processing from electronic medical records.

NLP algorithm successfully determined asthma prognosis (i.e., no remission, long-term remission, and...

Applying natural language processing techniques to develop a task-specific EMR interface for timely stroke thrombolysis: A feasibility study.

OBJECTIVE: To reduce errors in determining eligibility for intravenous thrombolytic therapy (IVT) in...

Predicting Chronic Disease Hospitalizations from Electronic Health Records: An Interpretable Classification Approach.

Urban living in modern large cities has significant adverse effects on health, increasing the risk o...

Labeling for Big Data in radiation oncology: The Radiation Oncology Structures ontology.

PURPOSE: Leveraging Electronic Health Records (EHR) and Oncology Information Systems (OIS) has great...

The eXtensible ontology development (XOD) principles and tool implementation to support ontology interoperability.

Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With ...

Delirium Prediction using Machine Learning Models on Preoperative Electronic Health Records Data.

Electronic Health Records (EHR) are mainly designed to record relevant patient information during th...

Harnessing electronic medical records to advance research on multiple sclerosis.

BACKGROUND: Electronic medical records (EMR) data are increasingly used in research, but no studies ...

Improving the interoperability of biomedical ontologies with compound alignments.

BACKGROUND: Ontologies are commonly used to annotate and help process life sciences data. Although t...

Prediction of venous thromboembolism using semantic and sentiment analyses of clinical narratives.

Venous thromboembolism (VTE) is the third most common cardiovascular disorder. It affects people of ...

How Confounder Strength Can Affect Allocation of Resources in Electronic Health Records.

When electronic health record (EHR) data are used, multiple approaches may be available for measurin...

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