AIMC Topic: Electronic Health Records

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Generalized Extraction and Classification of Span-Level Clinical Phrases.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Much of the critical information in a patient's electronic health record (EHR) is hidden in unstructured text. As such, there is an increasing role for automated text extraction and summarization to make this information available in a way that can b...
Natural Language Processing Information Storage and Retrieval Humans Electronic Health Records
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A Computable Phenotype for Acute Respiratory Distress Syndrome Using Natural Language Processing and Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Acute Respiratory Distress Syndrome (ARDS) is a syndrome of respiratory failure that may be identified using text from radiology reports. The objective of this study was to determine whether natural language processing (NLP) with machine learning per...
Diagnosis, Computer-Assisted Aged Unified Medical Language System Length of Stay Adult Radiography, Thoracic Cohort Studies Predictive Value of Tests Male Humans Respiratory Distress Syndrome Natural Language Processing Middle Aged Electronic Health Records Area Under Curve Female Supervised Machine Learning Risk Factors
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Ascertaining Depression Severity by Extracting Patient Health Questionnaire-9 (PHQ-9) Scores from Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
The Patient Health Questionnaire-9 (PHQ-9) is a validated instrument for assessing depression severity. While some electronic health record (EHR) systems capture PHQ-9 scores in a structured format, unstructured clinical notes remain the only source ...
Humans Electronic Health Records Depressive Disorder Patient Health Questionnaire Adult Severity of Illness Index Natural Language Processing Information Storage and Retrieval
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Towards stroke prediction using electronic health records.

BMC medical informatics and decision making Dec 4, 2018
BACKGROUND: As of 2014, stroke is the fourth leading cause of death in Japan. Predicting a future diagnosis of stroke would better enable proactive forms of healthcare measures to be taken. We aim to predict a diagnosis of stroke within one year of t...
Prognosis Electronic Health Records Stroke Japan Medical Informatics Applications Humans Neural Networks, Computer
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Impact of a Pharmacist-Led Intervention on 30-Day Readmission and Assessment of Factors Predictive of Readmission in African American Men With Heart Failure.

American journal of men's health Nov 28, 2018
Heart failure (HF) is responsible for more 30-day readmissions than any other condition. Minorities, particularly African American males (AAM), are at much higher risk for readmission than the general population. In this study, demographic, social, a...
Incidence Predictive Value of Tests Heart Failure Patient Readmission Academic Medical Centers Black or African American Georgia Pharmacists Male Middle Aged Risk Assessment Humans Case-Control Studies Machine Learning Prognosis Electronic Health Records Hospitalization Aged Adult
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Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study.

PLoS medicine Nov 27, 2018
BACKGROUND: Pythia is an automated, clinically curated surgical data pipeline and repository housing all surgical patient electronic health record (EHR) data from a large, quaternary, multisite health institute for data science initiatives. In an eff...
Data Mining Young Adult Surgical Procedures, Operative Adult Automation Male Female Middle Aged Humans Reproducibility of Results Comorbidity Machine Learning Risk Factors Adolescent Retrospective Studies Aged Health Status Electronic Health Records Risk Assessment Postoperative Complications
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Adversarial MACE Prediction After Acute Coronary Syndrome Using Electronic Health Records.

IEEE journal of biomedical and health informatics Nov 20, 2018
Acute coronary syndrome (ACS), as an emergent and severe syndrome due to decreased blood flow in the coronary arteries, is a leading cause of death and serious long-term disability globally. ACS is usually caused by one of three problems: ST elevatio...
Deep Learning Models, Statistical Heart Failure Acute Coronary Syndrome Medical Informatics Electronic Health Records Aged Middle Aged Diagnosis, Computer-Assisted Humans
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Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

PLoS medicine Nov 20, 2018
BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of ca...
Aged, 80 and over Young Adult Adult Male Female Reproducibility of Results Risk Factors Aged Time Factors Socioeconomic Factors Health Status Age Factors Emergency Service, Hospital Middle Aged Risk Assessment England Adolescent Humans Machine Learning Electronic Health Records Needs Assessment Data Mining Sex Factors Health Services Needs and Demand Patient Admission
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Applying Artificial Intelligence to Address the Knowledge Gaps in Cancer Care.

The oncologist Nov 16, 2018
BACKGROUND: Rapid advances in science challenge the timely adoption of evidence-based care in community settings. To bridge the gap between what is possible and what is practiced, we researched approaches to developing an artificial intelligence (AI)...
Clinical Decision-Making Humans Neoplasms Artificial Intelligence Decision Support Systems, Clinical Patient Selection Electronic Health Records Feasibility Studies Medical Oncology Clinical Trials as Topic Evidence-Based Medicine
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How Cognitive Machines Can Augment Medical Imaging.

AJR. American journal of roentgenology Nov 13, 2018
OBJECTIVE: Artificial intelligence (AI) neural networks rapidly convert disparate facts and data into highly predictive analytic models. Machine learning maps image-patient phenotype correlations opaque to standard statistics. Deep learning performs ...
Algorithms Electronic Health Records Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer Artificial Intelligence Machine Learning Natural Language Processing Diagnostic Imaging
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