Practice Management

Information Technology

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

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Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records.

Machine learning has become ubiquitous and a key technology on mining electronic health records (EHR...

Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.

The wide adoption of electronic health record systems in health care generates big real-world data t...

The impact of extraneous features on the performance of recurrent neural network models in clinical tasks.

Electronic Medical Records (EMR) are a rich source of patient information, including measurements re...

Incorporating medical code descriptions for diagnosis prediction in healthcare.

BACKGROUND: Diagnosis aims to predict the future health status of patients according to their histor...

Multi-objective ensemble deep learning using electronic health records to predict outcomes after lung cancer radiotherapy.

Accurately predicting treatment outcome is crucial for creating personalized treatment plans and fol...

A continual prediction model for inpatient acute kidney injury.

Acute kidney injury (AKI) commonly occurs in hospitalized patients and can lead to serious medical c...

The Hearing Impairment Ontology: A Tool for Unifying Hearing Impairment Knowledge to Enhance Collaborative Research.

Hearing impairment (HI) is a common sensory disorder that is defined as the partial or complete inab...

The Real Era of the Art of Medicine Begins with Artificial Intelligence.

Physicians have been performing the art of medicine for hundreds of years, and since the ancient era...

EXTraction of EMR numerical data: an efficient and generalizable tool to EXTEND clinical research.

BACKGROUND: Electronic medical records (EMR) contain numerical data important for clinical outcomes ...

Natural language processing for disease phenotyping in UK primary care records for research: a pilot study in myocardial infarction and death.

BACKGROUND: Free text in electronic health records (EHR) may contain additional phenotypic informati...

Interpreting patient-Specific risk prediction using contextual decomposition of BiLSTMs: application to children with asthma.

BACKGROUND: Predictive modeling with longitudinal electronic health record (EHR) data offers great p...

Using machine learning to selectively highlight patient information.

BACKGROUND: Electronic medical record (EMR) systems need functionality that decreases cognitive over...

A Research Roadmap: Connected Health as an Enabler of Cancer Patient Support.

The evidence that quality of life is a positive variable for the survival of cancer patients has pro...

ECG AI-Guided Screening for Low Ejection Fraction (EAGLE): Rationale and design of a pragmatic cluster randomized trial.

BACKGROUND: A deep learning algorithm to detect low ejection fraction (EF) using routine 12-lead ele...

Decentralized distribution-sampled classification models with application to brain imaging.

BACKGROUND: In this age of big data, certain models require very large data stores in order to be in...

A Super-Learner Model for Tumor Motion Prediction and Management in Radiation Therapy: Development and Feasibility Evaluation.

In cancer radiation therapy, large tumor motion due to respiration can lead to uncertainties in tumo...

An Effective LSTM Recurrent Network to Detect Arrhythmia on Imbalanced ECG Dataset.

To reduce the high mortality rate from cardiovascular disease (CVD), the electrocardiogram (ECG) bea...

Deep representation learning for individualized treatment effect estimation using electronic health records.

Utilizing clinical observational data to estimate individualized treatment effects (ITE) is a challe...

Identification of postoperative complications using electronic health record data and machine learning.

BACKGROUND: Using the American College of Surgeons National Surgical Quality Improvement Program (NS...

Aggregating the syntactic and semantic similarity of healthcare data towards their transformation to HL7 FHIR through ontology matching.

BACKGROUND AND OBJECTIVE: Healthcare systems deal with multiple challenges in releasing information ...

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