AIMC Topic: Symptom Assessment

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Evaluation of the prediction of CoVID-19 recovered and unrecovered cases using symptoms and patient's meta data based on support vector machine, neural network, CHAID and QUEST Models.

European review for medical and pharmacological sciences Sep 1, 2021
OBJECTIVE: This paper aims to develop four prediction models for recovered and unrecovered cases using descriptive data of patients and symptoms of CoVID-19 patients. The developed prediction models aim to extract the important variables in predictin...
COVID-19 SARS-CoV-2 Neural Networks, Computer Metadata Symptom Assessment Support Vector Machine Models, Theoretical Humans
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COVID-19 SignSym: a fast adaptation of a general clinical NLP tool to identify and normalize COVID-19 signs and symptoms to OMOP common data model.

Journal of the American Medical Informatics Association : JAMIA Jun 12, 2021
The COVID-19 pandemic swept across the world rapidly, infecting millions of people. An efficient tool that can accurately recognize important clinical concepts of COVID-19 from free text in electronic health records (EHRs) will be valuable to acceler...
Humans Information Storage and Retrieval Natural Language Processing Symptom Assessment Electronic Health Records Deep Learning COVID-19
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[Patient-tailored approach in tertiary care expert centres using individual dynamic network analysis].

Tijdschrift voor psychiatrie Jan 1, 2021
BACKGROUND: Patients with mental health disorders often have difficulty perceiving associations between multiple symptoms, such as inter-relations between somatic and psychological symptoms. This difficulty may be particularly challenging in patients...
Neural Networks, Computer Outcome Assessment, Health Care Humans Psychiatric Status Rating Scales Patient-Centered Care Symptom Assessment Mental Health Services Tertiary Healthcare Mental Disorders
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Big Data Analytics + Virtual Clinical Semantic Network (vCSN): An Approach to Addressing the Increasing Clinical Nuances and Organ Involvement of COVID-19.

ASAIO journal (American Society for Artificial Internal Organs : 1992) Jan 1, 2021
The coronavirus disease 2019 (COVID-19) pandemic has revealed deep gaps in our understanding of the clinical nuances of this extremely infectious viral pathogen. In order for public health, care delivery systems, clinicians, and other stakeholders to...
Models, Theoretical Medical Informatics Data Science Semantic Web Symptom Assessment Semantics COVID-19 Big Data Reproducibility of Results Artificial Intelligence Machine Learning Humans
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Natural language processing of symptoms documented in free-text narratives of electronic health records: a systematic review.

Journal of the American Medical Informatics Association : JAMIA Apr 1, 2019
OBJECTIVE: Natural language processing (NLP) of symptoms from electronic health records (EHRs) could contribute to the advancement of symptom science. We aim to synthesize the literature on the use of NLP to process or analyze symptom information doc...
Databases, Bibliographic Symptom Assessment Natural Language Processing Data Mining Narration Algorithms Humans Electronic Health Records
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Towards Constructing a New Taxonomy for Psychiatry Using Self-reported Symptoms.

Studies in health technology and informatics Jan 1, 2015
The Diagnostic and Statistical Manual (DSM) has served as the gold standard for psychiatric diagnosis for the past several decades in the USA, and DSM diagnoses mirror mental health and substance abuse diagnoses in ICD-9 and ICD-10. However, DSM diag...
Vocabulary, Controlled Unsupervised Machine Learning Symptom Assessment San Francisco Terminology as Topic Mental Disorders Self Report Humans Natural Language Processing Psychiatry
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