Practice Management

Information Technology

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

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The hospital of tomorrow in 10 points.

Technology has advanced rapidly in recent years and is continuing to do so, with associated changes ...

Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.

BACKGROUND: Allowing patients to access their own electronic health record (EHR) notes through onlin...

Prediction of Adverse Events in Patients Undergoing Major Cardiovascular Procedures.

Electronic health records (EHR) provide opportunities to leverage vast arrays of data to help preven...

Early recognition of multiple sclerosis using natural language processing of the electronic health record.

BACKGROUND: Diagnostic accuracy might be improved by algorithms that searched patients' clinical not...

A study of EMR-based medical knowledge network and its applications.

BACKGROUND AND OBJECTIVE: Electronic medical records (EMRs) contain an amount of medical knowledge w...

Ensembles of NLP Tools for Data Element Extraction from Clinical Notes.

Natural Language Processing (NLP) is essential for concept extraction from narrative text in electro...

Accelerating Chart Review Using Automated Methods on Electronic Health Record Data for Postoperative Complications.

Manual Chart Review (MCR) is an important but labor-intensive task for clinical research and quality...

Knowledge as a Service at the Point of Care.

An electronic health record (EHR) can assist the delivery of high-quality patient care, in part by p...

Interpretable Deep Models for ICU Outcome Prediction.

Exponential surge in health care data, such as longitudinal data from electronic health records (EHR...

Reliability of Robotic Telemedicine for Assessing Critically Ill Patients with the Full Outline of UnResponsiveness Score and Glasgow Coma Scale.

PURPOSE: Telemedicine is increasingly utilized in the evaluation of critically ill patients, includi...

Effectiveness of Electroconvulsive Therapy Augmentation on Clozapine-Resistant Schizophrenia.

OBJECTIVE: This retrospective case series study of the effectiveness of electroconvulsive therapy (E...

Developing the Quantitative Histopathology Image Ontology (QHIO): A case study using the hot spot detection problem.

Interoperability across data sets is a key challenge for quantitative histopathological imaging. The...

Doctor AI: Predicting Clinical Events via Recurrent Neural Networks.

Leveraging large historical data in electronic health record (EHR), we developed Doctor AI, a generi...

Learning Optimal Individualized Treatment Rules from Electronic Health Record Data.

Medical research is experiencing a paradigm shift from "one-size-fits-all" strategy to a precision m...

Large-scale identification of patients with cerebral aneurysms using natural language processing.

OBJECTIVE: To use natural language processing (NLP) in conjunction with the electronic medical recor...

The Pre-Eclampsia Ontology: A Disease Ontology Representing the Domain Knowledge Specific to Pre-Eclampsia.

Pre-eclampsia (PE) is a clinical syndrome characterized by new-onset hypertension and proteinuria at...

Feasibility of Antegrade Contrast-enhanced US Nephrostograms to Evaluate Ureteral Patency.

Purpose To demonstrate the feasibility of contrast material-enhanced ulrasonographic (US) nephrostog...

Predicting early psychiatric readmission with natural language processing of narrative discharge summaries.

The ability to predict psychiatric readmission would facilitate the development of interventions to ...

Semi-supervised learning of the electronic health record for phenotype stratification.

Patient interactions with health care providers result in entries to electronic health records (EHRs...

A machine learning-based framework to identify type 2 diabetes through electronic health records.

OBJECTIVE: To discover diverse genotype-phenotype associations affiliated with Type 2 Diabetes Melli...

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