AIMC Topic: Electronic Health Records

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Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.

Methods of information in medicine Jul 14, 2021
OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients fr...
Humans Natural Language Processing International Classification of Diseases Asthma Algorithms Phenotype Adolescent Electronic Health Records Child, Preschool Child
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Artificial intelligence and the future of life sciences.

Drug discovery today Jul 8, 2021
Over the past few decades, the number of health and 'omics-related data' generated and stored has grown exponentially. Patient information can be collected in real time and explored using various artificial intelligence (AI) tools in clinical trials;...
Artificial Intelligence Electronic Health Records Drug Design Data Science Humans Pharmacology Clinical Trials as Topic Biotechnology Biological Science Disciplines Mobile Applications Drug Development Natural Language Processing Publishing
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Semantic Textual Similarity in Japanese Clinical Domain Texts Using BERT.

Methods of information in medicine Jul 8, 2021
BACKGROUND: Semantic textual similarity (STS) captures the degree of semantic similarity between texts. It plays an important role in many natural language processing applications such as text summarization, question answering, machine translation, i...
Natural Language Processing Japan Information Storage and Retrieval Semantics Humans Electronic Health Records
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Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort.

PLoS computational biology Jul 6, 2021
Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of electronic health records (EHRs) offers a unique opportunity to build machine learning algorithms to identify drug-drug interactions that drive adverse e...
Aged Aged, 80 and over Young Adult Adult Algorithms Retrospective Studies Liver Male Electronic Health Records Humans Models, Statistical Middle Aged Female Anti-Inflammatory Agents, Non-Steroidal Machine Learning Adolescent Drug Interactions Computational Biology Chemical and Drug Induced Liver Injury
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A machine learning based exploration of COVID-19 mortality risk.

PloS one Jul 2, 2021
Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring efficient resource allocation and treatment planning. This study aimed to develop and compare prognosis prediction machine learning models based on invas...
Adult Male Middle Aged Comorbidity Humans Risk COVID-19 SARS-CoV-2 Severity of Illness Index Pandemics Symptom Assessment Forecasting Models, Theoretical Aged Electronic Health Records Support Vector Machine Aged, 80 and over Female Triage Young Adult
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Using Artificial Intelligence to Make Use of Electronic Health Records Less Painful-Fighting Fire With Fire.

JAMA network open Jul 1, 2021
Artificial Intelligence Electronic Health Records Fires Humans
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Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Identify and Estimate Survival in a Longitudinal Cohort of Patients With Lung Cancer.

JAMA network open Jul 1, 2021
IMPORTANCE: Electronic health records (EHRs) provide a low-cost means of accessing detailed longitudinal clinical data for large populations. A lung cancer cohort assembled from EHR data would be a powerful platform for clinical outcome studies.
ROC Curve Electronic Health Records Lung Neoplasms Female Humans Area Under Curve Survivors Male Machine Learning Survival Analysis Boston Cohort Studies Algorithms Prognosis
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Augmented intelligence to predict 30-day mortality in patients with cancer.

Future oncology (London, England) Jun 30, 2021
An augmented intelligence tool to predict short-term mortality risk among patients with cancer could help identify those in need of actionable interventions or palliative care services. An algorithm to predict 30-day mortality risk was developed us...
Electronic Health Records Female Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Male Humans Artificial Intelligence Machine Learning Algorithms Decision Support Systems, Clinical Middle Aged Socioeconomic Factors Risk Assessment Neoplasms Adolescent
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Using NLP in openEHR archetypes retrieval to promote interoperability: a feasibility study in China.

BMC medical informatics and decision making Jun 26, 2021
BACKGROUND: With the development and application of medical information system, semantic interoperability is essential for accurate and advanced health-related computing and electronic health record (EHR) information sharing. The openEHR approach can...
China Natural Language Processing Feasibility Studies Semantics Humans Electronic Health Records
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Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID).

Scientific reports Jun 17, 2021
In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortality can significantly improve triage, bed allocation, timely management, and possibly, outcome. The study objective is to develop and validate individu...
Middle Aged Risk Assessment India Triage Proportional Hazards Models Propensity Score Patient Admission SARS-CoV-2 Humans Risk Factors Machine Learning Aged COVID-19 Male Prospective Studies Prognosis Retrospective Studies Electronic Health Records Female
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