Related references
Note: Only part of the references are listed.Assessment of Dual-Tree Complex Wavelet Transform to Improve SNR in Collaboration with Neuro-Fuzzy System for Heart-Sound Identification
Bassam Al-Naami et al.
ELECTRONICS (2022)
Automated Detection of Left Bundle Branch Block from ECG Signal Utilizing the Maximal Overlap Discrete Wavelet Transform with ANFIS
Bassam Al-Naami et al.
COMPUTERS (2022)
Development of a decision support system tool to predict the pulmonary function using artificial neural network approach
Saba Kalantary et al.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE (2021)
A Machine Learning Application to Predict Early Lung Involvement in Scleroderma: A Feasibility Evaluation
Giuseppe Murdaca et al.
DIAGNOSTICS (2021)
Application of Machine Learning in Pulmonary Function Assessment Where Are We Now and Where Are We Going?
Paresh C. Giri et al.
FRONTIERS IN PHYSIOLOGY (2021)
Deep neural network analyses of spirometry for structural phenotyping of chronic obstructive pulmonary disease
Sandeep Bodduluri et al.
JCI INSIGHT (2020)
Design and Development of Smartphone-Enabled Spirometer With a Disease Classification System Using Convolutional Neural Network
Sudipto Trivedy et al.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2020)
An automatic system supporting clinical decision for chronic obstructive pulmonary disease
Ernesto Iadanza et al.
HEALTH AND TECHNOLOGY (2020)
Diagnosing asthma and chronic obstructive pulmonary disease with machine learning
Dimitris Spathis et al.
HEALTH INFORMATICS JOURNAL (2019)
Artificial intelligence outperforms pulmonologists in the interpretation of pulmonary function tests
Marko Topalovic et al.
EUROPEAN RESPIRATORY JOURNAL (2019)
An Expert Diagnostic System to Automatically Identify Asthma and Chronic Obstructive Pulmonary Disease in Clinical Settings
Almir Badnjevic et al.
SCIENTIFIC REPORTS (2018)
Pulmonary Function Tests for the Radiologist
Hsiang-Jer Tseng et al.
RADIOGRAPHICS (2017)
Automated Interpretation of Pulmonary Function Tests in Adults with Respiratory Complaints
Marko Topalovic et al.
RESPIRATION (2017)
Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease
Almir Badnjevic et al.
BMC MEDICAL INFORMATICS AND DECISION MAKING (2015)
A Low-Cost Mobile Adaptive Tracking System for Chronic Pulmonary Patients in Home Environment
Ali Hakan Isik et al.
TELEMEDICINE AND E-HEALTH (2013)
Evaluation of Flow-Volume Spirometric Test Using Neural Network Based Prediction and Principal Component Analysis
Anandan Kavitha et al.
JOURNAL OF MEDICAL SYSTEMS (2011)
Chest diseases diagnosis using artificial neural networks
Orhan Er et al.
EXPERT SYSTEMS WITH APPLICATIONS (2010)
Diagnosis of Airway Obstruction or Restrictive Spirometric Patterns by Multiclass Support Vector Machines
Deniz Sahin et al.
JOURNAL OF MEDICAL SYSTEMS (2010)
Prediction of Spirometric Forced Expiratory Volume (FEV1) Data Using Support Vector Regression
A. Kavitha et al.
MEASUREMENT SCIENCE REVIEW (2010)
How many hidden layers and nodes?
D. Stathakis
INTERNATIONAL JOURNAL OF REMOTE SENSING (2009)
Prediction of Forced Expiratory Volume in Pulmonary Function Test using Radial Basis Neural Networks and k-means Clustering
Sujatha C. Manoharan et al.
JOURNAL OF MEDICAL SYSTEMS (2009)
Comparison of Two ANN Methods for Classification of Spirometer Data
Sujatha C. Manoharan et al.
MEASUREMENT SCIENCE REVIEW (2008)
Detection of obstructive respiratory abnormality using flow-volume spirometry and radial basis function neural networks
Mahesh Veezhinathan et al.
JOURNAL OF MEDICAL SYSTEMS (2007)
Interpretative strategies for lung function tests
R Pellegrino et al.
EUROPEAN RESPIRATORY JOURNAL (2005)
Standardisation of spirometry
MR Miller et al.
EUROPEAN RESPIRATORY JOURNAL (2005)
Learning capability and storage capacity of two-hidden-layer feedforward networks
GB Huang
IEEE TRANSACTIONS ON NEURAL NETWORKS (2003)
Share Paper
