Asthma Clinical Trials

Showing 61-80 of 4,312 trials

Using NLP and Neural Networks to Autonomously Identify Severe Asthma and Determine Study Eligibility in a Large Healthcare System

NCT06389058

The study aims to to use new technologies (ML, AI, NLP), to autonomously identify moderate to severe asthma populations within an EHR system, describe differences in treatment patterns across different populations, and determine trial eligibility. Primary Objectives Please ensure you detail primary objectives Aim 1. Determine and validate a diagnosis of severe asthma (SA) using predictive features obtained from the Scripps Health EHR. * Aim 1a: Use ML applied to structured EHR data to predict SA. Use the opinion of 2 specialty-trained physicians and ATS guidelines to determine model accuracy. * Aim 1b: Use NLP applied to unstructured text to predict SA. Determine model accuracy as above in Aim 1a. * Aim 1c: Use a combination of ML applied to structured data to predict SA. Determine model accuracy as above in Aim 1a.

Severe Asthma

San Diego State University31,795 participantsStarted May 2023

San Diego, California, United States

COMPLETED

Prediction of Outcomes With a Miniaturized Transesophageal Echocardiography Probe in Patients With Acute Respiratory Distress Syndrome

NCT03763773

The Superior Vena cava Respiratory Collapse Index (cVCS) is a haemodynamic parameter measured exclusively by transoesophageal ultrasound (TEE), which is used to assess cardiac precharge-dependence status. This may be an important prognostic factor in ARDS because it is a sign of hypervolemia and right heart failure.

Acute Respiratory Distress Syndrome

University Hospital, Lille50 participantsStarted Apr 2019

Lille, France

RECRUITING

Swiss Paediatric Airway Cohort

NCT03505216

The Swiss Paediatric Airway Cohort (SPAC) is a national, prospective clinical cohort of children and adolescents who visit physicians in Switzerland for recurrent wheeze, cough, and exercise- or sleep-related respiratory problems. SPAC aims to answer important questions on clinical phenotypes, prognosis, diagnosis and treatment. SPAC is part of routine care, and only clinically indicated investigations are done. The comprehensive baseline assessment includes a detailed questionnaire to families, plus test results, diagnoses and treatments from hospital records. Follow-up is via monthly questionnaires the first 12 months and thereafter annual questionnaires to families, and data from follow-up visits. Currently, 4344 patients from 10 clinics and hospitals in Switzerland (Aarau, Basel, Bern, Chur, Horgen, Lausanne, Luzern, St. Gallen, Worb, Zurich) have been enrolled. SPAC provides real-life data on children visiting the Swiss health care system for common respiratory problems. It will provide a research platform for health services research, and for nested clinical and transitional studies. Publications and plain language summaries are listed on the study website: https://www.spac-study.ch/publikationen/

AsthmaWheezingCough+3 more

University of Bern6,000 participantsStarted Jun 2017

Vienna, Austria • Aarau, Switzerland • Basel, Switzerland +9 more locations

Using NLP and Neural Networks to Autonomously Identify Severe Asthma and Determine Study Eligibility in a Large Healthcare System

Prediction of Outcomes With a Miniaturized Transesophageal Echocardiography Probe in Patients With Acute Respiratory Distress Syndrome

Swiss Paediatric Airway Cohort

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