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Information Technology

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

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Predicting inadequate postoperative pain management in depressed patients: A machine learning approach.

Widely-prescribed prodrug opioids (e.g., hydrocodone) require conversion by liver enzyme CYP-2D6 to ...

Automated Fundus Image Quality Assessment in Retinopathy of Prematurity Using Deep Convolutional Neural Networks.

PURPOSE: Accurate image-based ophthalmic diagnosis relies on fundus image clarity. This has importan...

Natural Language Processing-Identified Problem Opioid Use and Its Associated Health Care Costs.

Use of prescription opioids and problems of abuse and addiction have increased over the past decade....

Automatic Disease Annotation From Radiology Reports Using Artificial Intelligence Implemented by a Recurrent Neural Network.

OBJECTIVE: Radiology reports are rich resources for biomedical researchers. Before utilization of ra...

Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction.

Current approaches to predicting a cardiovascular disease (CVD) event rely on conventional risk fact...

Development of a cardiac-centered frailty ontology.

BACKGROUND: A Cardiac-centered Frailty Ontology can be an important foundation for using NLP to asse...

Machine Learning Can Improve Estimation of Surgical Case Duration: A Pilot Study.

Operating room (OR) utilization is a significant determinant of hospital profitability. One aspect o...

Semi-supervised encoding for outlier detection in clinical observation data.

BACKGROUND AND OBJECTIVE: Electronic Health Record (EHR) data often include observation records that...

An ontological foundation for ocular phenotypes and rare eye diseases.

BACKGROUND: The optical accessibility of the eye and technological advances in ophthalmic diagnostic...

The practical implementation of artificial intelligence technologies in medicine.

The development of artificial intelligence (AI)-based technologies in medicine is advancing rapidly,...

Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide.

Suicide accounts for nearly 800,000 deaths per year worldwide with rates of both deaths and attempts...

Artificial intelligence-based decision-making for age-related macular degeneration.

Artificial intelligence (AI) based on convolutional neural networks (CNNs) has a great potential to ...

Quantitative analysis of manual annotation of clinical text samples.

BACKGROUND: Semantic interoperability of eHealth services within and across countries has been the m...

Automated data extraction and ensemble methods for predictive modeling of breast cancer outcomes after radiation therapy.

PURPOSE: The purpose of this study was to compare the effectiveness of ensemble methods (e.g., rando...

EHR phenotyping via jointly embedding medical concepts and words into a unified vector space.

BACKGROUND: There has been an increasing interest in learning low-dimensional vector representations...

Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.

Cancer stage is rarely captured in structured form in the electronic health record (EHR). We evaluat...

Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records.

Dentists are more often treating patients with Cardiovascular Diseases (CVD) in their clinics; there...

Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.

Accurate image-based medical diagnosis relies upon adequate image quality and clarity. This has impo...

Using Machine Learning to Predict the Information Seeking Behavior of Clinicians Using an Electronic Medical Record System.

Poor electronic medical record (EMR) usability is detrimental to both clinicians and patients. A bet...

Standardizing Heterogeneous Annotation Corpora Using HL7 FHIR for Facilitating their Reuse and Integration in Clinical NLP.

Manually annotated clinical corpora are commonly used as the gold standards for the training and eva...

Optimizing Corpus Creation for Training Word Embedding in Low Resource Domains: A Case Study in Autism Spectrum Disorder (ASD).

Automating the extraction of behavioral criteria indicative of Autism Spectrum Disorder (ASD) in ele...

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