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Information Technology

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

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Leveraging electronic health record data to inform hospital resource management : A systematic data mining approach.

Early identification of resource needs is instrumental in promoting efficient hospital resource mana...

Influenza forecasting for French regions combining EHR, web and climatic data sources with a machine learning ensemble approach.

Effective and timely disease surveillance systems have the potential to help public health officials...

CQL4NLP: Development and Integration of FHIR NLP Extensions in Clinical Quality Language for EHR-driven Phenotyping.

Lack of standardized representation of natural language processing (NLP) components in phenotyping a...

Deep EHR Spotlight: a Framework and Mechanism to Highlight Events in Electronic Health Records for Explainable Predictions.

The wide adoption of Electronic Health Records (EHR) has resulted in large amounts of clinical data ...

Integration of NLP2FHIR Representation with Deep Learning Models for EHR Phenotyping: A Pilot Study on Obesity Datasets.

HL7 Fast Healthcare Interoperability Resources (FHIR) is one of the current data standards for enabl...

Development of the Joint Commission of Taiwan's Smart Healthcare Standard.

It is well known that information technology (IT) can play a pivotal role in enhancing healthcare qu...

NATURAL LANGUAGE PROCESSING BASED MACHINE LEARNING MODEL USING CARDIAC MRI REPORTS TO IDENTIFY HYPERTROPHIC CARDIOMYOPATHY PATIENTS.

Hypertrophic Cardiomyopathy (HCM) is the most common genetic heart disease in the US and is known to...

Toward an Automatic Quality Assessment of Voice-Based Telemedicine Consultations: A Deep Learning Approach.

Maintaining a high quality of conversation between doctors and patients is essential in telehealth s...

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Early prediction of patient outcomes is important for targeting preventive care. This protocol descr...

Digital Data Sources and Their Impact on People's Health: A Systematic Review of Systematic Reviews.

Digital data sources have become ubiquitous in modern culture in the era of digital technology but ...

Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administ...

Multi-domain clinical natural language processing with MedCAT: The Medical Concept Annotation Toolkit.

Electronic health records (EHR) contain large volumes of unstructured text, requiring the applicatio...

Machine learning and deep learning to predict mortality in patients with spontaneous coronary artery dissection.

Machine learning (ML) and deep learning (DL) can successfully predict high prevalence events in very...

Contextual embedding bootstrapped neural network for medical information extraction of coronary artery disease records.

Coronary artery disease (CAD) is the major cause of human death worldwide. The development of new CA...

A scalable approach for developing clinical risk prediction applications in different hospitals.

OBJECTIVE: Machine learning (ML) algorithms are now widely used in predicting acute events for clini...

Opportunities and Challenges in Democratizing Immunology Datasets.

The field of immunology is rapidly progressing toward a systems-level understanding of immunity to t...

Review of Temporal Reasoning in the Clinical Domain for Timeline Extraction: Where we are and where we need to be.

Understanding a patient's medical history, such as how long symptoms last or when a procedure was pe...

Characterizing chronological accumulation of comorbidities in healthy veterans: a computational approach.

Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personali...

Leveraging data and AI to deliver on the promise of digital health.

Rising rates of NCDs threaten fragile healthcare systems in low- and middle-income countries. Fortun...

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