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Precision Health Database


Precision Health Database|Search|PHGKB

Heart, Lung, Blood and Sleep Disorders

Last data update: May 31, 2023. (Total: 60044 Documents since 2012)
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Detecting acute respiratory diseases in the pediatric population using cough sound features and machine learning: A systematic review.
Roneel V Sharan et al. Int J Med Inform 2023 176105093
Prediction of persistent chronic cough in patients with chronic cough using machine learning.
Wansu Chen et al. ERJ open research 2023 9(2)
Development and validation of a respiratory-responsive vocal biomarker-based tool for generalizable detection of respiratory impairment: independent case-control studies in multiple respiratory conditions including asthma, chronic obstructive pulmonary disease, and COVID-19.
Savneet Kaur et al. Journal of medical Internet research 2023
Machine learning-enabled risk prediction of chronic obstructive pulmonary disease with unbalanced data.
Wang Xuchun et al. Computer methods and programs in biomedicine 2023 230107340
Developing and Validating Clinical Features-Based Machine Learning Algorithms to Predict Influenza Infection in Influenza-like Illness Patients.
Hung Shang-Kai et al. Biomedical journal 2022
Derivation of a clinical-based model to detect invasive bacterial infections in febrile infants.
Yaeger Jeffrey P et al. Journal of hospital medicine 2022
Predicting the Need for Intubation among COVID-19 Patients Using Machine Learning Algorithms: A Single-Center Study.
Nopour Raoof et al. Medical journal of the Islamic Republic of Iran 2022 3630
An intelligent prediagnosis system for disease prediction and examination recommendation based on electronic medical record and a medical-semantic-aware convolution neural network (MSCNN) for pediatric chronic cough.
Zhu Zhu et al. Translational pediatrics 2022 11(7) 1216-1233
Making cough count in tuberculosis care
AJ Zimmer et al, Comm Medicine, July 6, 2022
Clinical Analysis of Primary Tracheobronchial Tumors in Children and Evaluation of the Predicting Models for Mucoepidermoid Carcinoma.
Zhang Chen et al. Current medical science 2022
Machine learning for detecting COVID-19 from cough sounds: An ensemble-based MCDM method.
Chowdhury Nihad Karim et al. Computers in biology and medicine 2022 145105405
Effect Evaluation of Artificial Intelligence-Based Electronic Health PDCA Nursing Model in the Treatment of Mycoplasma Pneumonia in Children.
Zhao Yan et al. Journal of healthcare engineering 2022 20221956944
Bias and privacy in AI's cough-based COVID-19 recognition
HB Espinoza et al, Lancet Digital Health, December 2021
A Systematic Review of Clinical Prediction Rules for the Diagnosis of Influenza.
Ebell Mark H et al. Journal of the American Board of Family Medicine : JABFM 2021 34(6) 1123-1140
A Deep Learning Model to Predict Knee Osteoarthritis Based on Nonimage Longitudinal Medical Record.
Ningrum Dina Nur Anggraini et al. Journal of multidisciplinary healthcare 2021 142477-2485
Identifying acute exacerbations of chronic obstructive pulmonary disease using patient-reported symptoms and cough feature analysis
S Claxton et al, NPJ Digital Medicine, July 2, 2021
Clinical presentation of COVID-19 - a model derived by a machine learning algorithm.
Yousef Malik et al. Journal of integrative bioinformatics 2021
Ruling In and Ruling Out COVID-19: Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging and Test Data.
D'Ambrosia Christopher et al. Journal of medical Internet research 2020 Nov
COVID-19 Cough Classification using Machine Learning and Global Smartphone Recordings
M Pahar et al, ARXIV, December 3, 2020
CLINICAL CHARACTERISTICS AND PROGNOSTIC FACTORS FOR ICU ADMISSION OF PATIENTS WITH COVID-19: A RETROSPECTIVE STUDY USING MACHINE LEARNING AND NATURAL LANGUAGE PROCESSING.
Izquierdo Jose Luis et al. Journal of medical Internet research 2020 Oct
Pay Attention to the cough: Early Diagnosis of COVID-19 using Interpretable Symptoms Embeddings with Cough Sound Signal Processing
A Pal et al, ARXIV, October 6, 2020
Diagnosing Chronic Obstructive Airway Disease: a diagnostic accuracy study of a smartphone delivered algorithm combining patient-reported symptoms and cough analysis for use in acute care consultations.
P Porter et al, MEDRXIV, September 25, 2020
Analysis of clinical features and imaging signs of COVID-19 with the assistance of artificial intelligence.
Ren H-W et al. European review for medical and pharmacological sciences 2020 Aug 24(15) 8210-8218
Scientists Developing App Based On Sound Of COVID-19 Cough05
J Hobson et al, WBUR, April 16, 2020
Continuous Sound Collection Using Smartphones and Machine Learning to Measure Cough.
Kvapilova Lucia et al. Digital biomarkers 3(3) 166-175
Understanding the importance of key risk factors in predicting chronic bronchitic symptoms using a machine learning approach.
Deng Huiyu et al. BMC medical research methodology 2019 19(1) 70
Digital endpoints library can aid clinical trials for new medicines
J Goldsack et al, Stat News, November 6, 2019
Human versus machine in medicine: can scientific literature answer the question?
TS Cook, Lancet Digital Health, September 24, 2019
A.I. Is Learning From Humans. Many Humans.
C Metz, NY Times, August 16, 2019
A prospective multicentre study testing the diagnostic accuracy of an automated cough sound centred analytic system for the identification of common respiratory disorders in children.
Porter Paul et al. Respiratory research 2019 Jun 20(1) 81
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