Information Technology

Assessing Resolvability and Consistency in OBO Foundry Ontologies: Pilot Study.

Ontologies listed in the OBO Foundry are often regarded as reliable choices to be reused but ontology interoperability of them remains unknown. This study evaluated the resolvability of URIs and consistency of axioms in the OBO Foundry library, BFO ontology, and CIDO ontology. All had nonresolvable URIs, but the OBO library and the CIDO had additional interoperability issues regarding the use of i...

CellProfiler Analyst 3.0: accessible data exploration and machine learning for image analysis.

SUMMARY: Image-based experiments can yield many thousands of individual measurements describing each object of interest, such as cells in microscopy screens. CellProfiler Analyst is a free, open-source software package designed for the exploration of quantitative image-derived data and the training of machine learning classifiers with an intuitive user interface. We have now released CellProfiler ...

OBO Foundry in 2021: operationalizing open data principles to evaluate ontologies.

Biological ontologies are used to organize, curate and interpret the vast quantities of data arising from biological experiments. While this works wel...

Machine learning approaches improve risk stratification for secondary cardiovascular disease prevention in multiethnic patients.

OBJECTIVES: Identifying high-risk patients is crucial for effective cardiovascular disease (CVD) prevention. It is not known whether electronic health...

Assessment of Automating Safety Surveillance From Electronic Health Records: Analysis for the Quality and Safety Review System.

BACKGROUND AND OBJECTIVES: In an effort to improve and standardize the collection of adverse event data, the Agency for Healthcare Research and Qualit...

Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.

The potential of artificial intelligence (AI) applied to clinical data from electronic health records (EHRs) to improve early detection for pancreatic...

Dynamic Survival Analysis for EHR Data with Personalized Parametric Distributions.

The widespread availability of high-dimensional electronic healthcare record (EHR) datasets has led to significant interest in using such data to deri...

Privacy-protecting, reliable response data discovery using COVID-19 patient observations.

OBJECTIVE: To utilize, in an individual and institutional privacy-preserving manner, electronic health record (EHR) data from 202 hospitals by analyzi...

Electronic phenotyping of health outcomes of interest using a linked claims-electronic health record database: Findings from a machine learning pilot project.

OBJECTIVE: Claims-based algorithms are used in the Food and Drug Administration Sentinel Active Risk Identification and Analysis System to identify oc...

Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning.

OBJECTIVE: The characteristics of clinician activities while interacting with electronic health record (EHR) systems can influence the time spent in E...

Predicting ventilator-associated pneumonia with machine learning.

Ventilator-associated pneumonia (VAP) is the most common and fatal nosocomial infection in intensive care units (ICUs). Existing methods for identifyi...

A Convolutional Neural Network for Improved Anomaly-Based Network Intrusion Detection.

Cybersecurity protects and recovers computer systems and networks from cyber attacks. The importance of cybersecurity is growing commensurately with p...

A Deep Learning Framework for Automated ICD-10 Coding.

The International Statistical Classification of Diseases and Related Health Problems (ICD) is one of the widely used classification system for diagnos...

Consolidated EHR Workflow for Endoscopy Quality Reporting.

Although colonoscopy is the most frequently performed endoscopic procedure, the lack of standardized reporting is impeding clinical and translational ...

Comparison of Knowledge Databases to Be Used in Automated Monitoring of Orthopedic Medical Devices.

Surveillance and traceability of medical devices (MD) is a challenge in health care systems. In the perspective of reusing EHR data to automate the mo...

Automated NLP Extraction of Clinical Rationale for Treatment Discontinuation in Breast Cancer.

PURPOSE: Key oncology end points are not routinely encoded into electronic medical records (EMRs). We assessed whether natural language processing (NL...

Classifying Pseudogout Using Machine Learning Approaches With Electronic Health Record Data.

OBJECTIVE: Identifying pseudogout in large data sets is difficult due to its episodic nature and a lack of billing codes specific to this acute subtyp...

Generative transfer learning for measuring plausibility of EHR diagnosis records.

OBJECTIVE: Due to a complex set of processes involved with the recording of health information in the Electronic Health Records (EHRs), the truthfulne...

Natural language processing to measure the frequency and mode of communication between healthcare professionals and family members of critically ill patients.

OBJECTIVE: To apply natural language processing (NLP) techniques to identify individual events and modes of communication between healthcare professio...

Development of a "meta-model" to address missing data, predict patient-specific cancer survival and provide a foundation for clinical decision support.

OBJECTIVE: Like most real-world data, electronic health record (EHR)-derived data from oncology patients typically exhibits wide interpatient variabil...