Newborn Cry-Based Diagnostic System to Distinguish between Sepsis and Respiratory Distress Syndrome Using Combined Acoustic Features
出版年份 2022 全文链接
标题
Newborn Cry-Based Diagnostic System to Distinguish between Sepsis and Respiratory Distress Syndrome Using Combined Acoustic Features
作者
关键词
-
出版物
Diagnostics
Volume 12, Issue 11, Pages 2802
出版商
MDPI AG
发表日期
2022-11-16
DOI
10.3390/diagnostics12112802
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Machine Learning-Based Cry Diagnostic System for Identifying Septic Newborns
- (2022) Fatemeh Salehian Matikolaie et al. JOURNAL OF VOICE
- A classification of MRI brain tumor based on two stage feature level ensemble of deep CNN models
- (2022) Nahid Ferdous Aurna et al. COMPUTERS IN BIOLOGY AND MEDICINE
- An Entropy-Based Architecture for Detection of Sepsis in Newborn Cry Diagnostic Systems
- (2022) Zahra Khalilzad et al. Entropy
- Classification of asphyxia infant cry using hybrid speech features and deep learning models
- (2022) Hua-Nong Ting et al. EXPERT SYSTEMS WITH APPLICATIONS
- Characterization of infant healthy and pathological cry signals in cepstrum domain based on approximate entropy and correlation dimension
- (2021) Salim Lahmiri et al. CHAOS SOLITONS & FRACTALS
- A review of infant cry analysis and classification
- (2021) Chunyan Ji et al. EURASIP Journal on Audio Speech and Music Processing
- Heuristic hyperparameter optimization of deep learning models for genomic prediction
- (2021) Junjie Han et al. G3-Genes Genomes Genetics
- How to tune the RBF SVM hyperparameters? An empirical evaluation of 18 search algorithms
- (2021) Jacques Wainer et al. ARTIFICIAL INTELLIGENCE REVIEW
- Deep Learning Assisted Neonatal Cry Classification via Support Vector Machine Models
- (2021) Ashwini K et al. Frontiers in Public Health
- Automated newborn cry diagnostic system using machine learning approach
- (2021) Fatemeh Salehian Matikolaie et al. Biomedical Signal Processing and Control
- On the use of long-term features in a newborn cry diagnostic system
- (2020) Fatemeh Salehian Matikolaie et al. Biomedical Signal Processing and Control
- Identification of diseases in newborns using advanced acoustic features of cry signals
- (2019) Yasmina Kheddache et al. Biomedical Signal Processing and Control
- Enhanced Automatic Speech Recognition System Based on Enhancing Power-Normalized Cepstral Coefficients
- (2019) Mohamed Tamazin et al. Applied Sciences-Basel
- Improved binary dragonfly optimization algorithm and wavelet packet based non-linear features for infant cry classification
- (2018) M. Hariharan et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Automated depression analysis using convolutional neural networks from speech
- (2018) Lang He et al. JOURNAL OF BIOMEDICAL INFORMATICS
- Cry-based infant pathology classification using GMMs
- (2016) Hesam Farsaie Alaie et al. SPEECH COMMUNICATION
- Resonance Frequencies Behavior in Pathologic Cries of Newborns
- (2015) Yasmina Kheddache et al. JOURNAL OF VOICE
- Normal and hypoacoustic infant cry signal classification using time–frequency analysis and general regression neural network
- (2012) M. Hariharan et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Gammatone Cepstral Coefficients: Biologically Inspired Features for Non-Speech Audio Classification
- (2012) X. Valero et al. IEEE TRANSACTIONS ON MULTIMEDIA
- Respiratory Distress of the Term Newborn Infant
- (2012) Martin O. Edwards et al. Paediatric Respiratory Reviews
- Pathophysiology and Treatment of Septic Shock in Neonates
- (2010) James L. Wynn et al. CLINICS IN PERINATOLOGY
- PP-293. Full term neonatal admissions
- (2010) Bahiyeh Qandalji EARLY HUMAN DEVELOPMENT
- Optimized Approximation Algorithm in Neural Networks Without Overfitting
- (2008) Yinyin Liu et al. IEEE TRANSACTIONS ON NEURAL NETWORKS
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More