AIMC Topic: Algorithms

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Using Neural Multi-task Learning to Extract Substance Abuse Information from Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Substance abuse carries many negative health consequences. Detailed information about patients' substance abuse history is usually captured in free-text clinical notes. Automatic extraction of substance abuse information is vital to assess patients' ...
Female Male Substance-Related Disorders Substance Abuse Detection Information Storage and Retrieval Machine Learning Algorithms Electronic Health Records Humans Neural Networks, Computer
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Disease comorbidity-guided drug repositioning: a case study in schizophrenia.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
UNLABELLED: The key to any computational drug repositioning is the availability of relevant data in machine-understandable format. While large amount of genetic, genomic and chemical data are publicly available, large-scale higher-level disease and d...
Antipsychotic Agents Humans Genomics Drug Repositioning Natural Language Processing Databases, Factual Schizophrenia Drug Discovery Knowledge Bases Comorbidity Information Storage and Retrieval Algorithms Phenotype
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Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Accurate image-based medical diagnosis relies upon adequate image quality and clarity. This has important implications for clinical diagnosis, and for emerging methods such as telemedicine and computer-based image analysis. In this study, we trained ...
Retinopathy of Prematurity Telemedicine Infant, Premature Reproducibility of Results Deep Learning ROC Curve Area Under Curve Fundus Oculi Retina Humans Neural Networks, Computer Algorithms Infant, Newborn
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A Preliminary Study of Clinical Concept Detection Using Syntactic Relations.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Concept detection is an integral step in natural language processing (NLP) applications in the clinical domain. Clinical concepts are detailed (e.g., "pain in left/right upper/lower arm/leg") and expressed in diverse phrase types (e.g., noun, verb, a...
Humans Algorithms Pattern Recognition, Automated Unified Medical Language System Electronic Health Records Natural Language Processing Semantics
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A Hybrid Residual Network and Long Short-Term Memory Method for Peptic Ulcer Bleeding Mortality Prediction.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
The prediction of patient mortality, which can detect high-risk patients, is a significant yet challenging problem in medical informatics. Thanks to the wide adoption of electronic health records (EHRs), many data-driven methods have been proposed to...
Humans Electronic Health Records Neural Networks, Computer Risk Assessment Algorithms ROC Curve Area Under Curve Peptic Ulcer Hemorrhage
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Methodological Advances in the Study of Hidden Variables: A Demonstration on Clinical Alcohol Use Disorder Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Research in the domain of psychopathology has been hindered by hidden variables-variables that are important to understanding and treating psychopathological illnesses but are unmeasured. Recent methodological advances in machine learning have culmin...
Psychopathology Data Interpretation, Statistical Humans Datasets as Topic Algorithms Alcoholism
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Ensemble-based Methods to Improve De-identification of Electronic Health Record Narratives.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Text de-identification is an application of clinical natural language processing that offers significant efficiency and scalability advantages. Hence, various learning algorithms have been applied to this task to yield better performance. Instead of ...
Natural Language Processing Data Anonymization Methods Humans Machine Learning Algorithms Electronic Health Records
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Phenotyping through Semi-Supervised Tensor Factorization (PSST).

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
A computational phenotype is a set of clinically relevant and interesting characteristics that describe patients with a given condition. Various machine learning methods have been proposed to derive phenotypes in an automatic, high-throughput manner....
Hypertension Humans Algorithms Machine Learning Diabetes Mellitus, Type 2 Phenotype Computational Biology Electronic Health Records
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Clinical Document Classification Using Labeled and Unlabeled Data Across Hospitals.

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Reviewing radiology reports in emergency departments is an essential but laborious task. Timely follow-up of patients with abnormal cases in their radiology reports may dramatically affect the patient's outcome, especially if they have been discharge...
Neural Networks, Computer Algorithms Natural Language Processing Information Storage and Retrieval Emergency Service, Hospital Classification Supervised Machine Learning Radiology Information Systems
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Optimizing Corpus Creation for Training Word Embedding in Low Resource Domains: A Case Study in Autism Spectrum Disorder (ASD).

AMIA ... Annual Symposium proceedings. AMIA Symposium Dec 5, 2018
Automating the extraction of behavioral criteria indicative of Autism Spectrum Disorder (ASD) in electronic health records (EHRs) can contribute significantly to the effort to monitor the condition. Word embedding algorithms such as Word2Vec can enco...
Humans Machine Learning Algorithms Information Storage and Retrieval Semantics Autism Spectrum Disorder Terminology as Topic Electronic Health Records Natural Language Processing
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