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PubMed Publications| Keyword search (4,163 papers available) |  |
"Neural networks" Keyword-tagged Publications:
| Title | Authors | PubMed ID | |
|---|---|---|---|
| 1 | Tuning Deep Learning for Predicting Aluminum Prices Under Different Sampling: Bayesian Optimization Versus Random Search | Alicia Estefania Antonio Figueroa | 41751647 CONCORDIA |
| 2 | Distinguishing Between Healthy and Unhealthy Newborns Based on Acoustic Features and Deep Learning Neural Networks Tuned by Bayesian Optimization and Random Search Algorithm | Lahmiri S; Tadj C; Gargour C; | 41294952 ENCS |
| 3 | Efficient neural encoding as revealed by bilingualism | Moore C; Donhauser PW; Klein D; Byers-Heinlein K; | 40828024 PSYCHOLOGY |
| 4 | Personalizing brain stimulation: continual learning for sleep spindle detection | Sobral M; Jourde HR; Marjani Bajestani SE; Coffey EBJ; Beltrame G; | 40609549 PSYCHOLOGY |
| 5 | Parallel boosting neural network with mutual information for day-ahead solar irradiance forecasting | Ahmed U; Mahmood A; Khan AR; Kuhlmann L; Alimgeer KS; Razzaq S; Aziz I; Hammad A; | 40185800 PHYSICS |
| 6 | Large language models deconstruct the clinical intuition behind diagnosing autism | Stanley J; Rabot E; Reddy S; Belilovsky E; Mottron L; Bzdok D; | 40147442 ENCS |
| 7 | MuscleMap: An Open-Source, Community-Supported Consortium for Whole-Body Quantitative MRI of Muscle | McKay MJ; Weber KA; Wesselink EO; Smith ZA; Abbott R; Anderson DB; Ashton-James CE; Atyeo J; Beach AJ; Burns J; Clarke S; Collins NJ; Coppieters MW; Cornwall J; Crawford RJ; De Martino E; Dunn AG; Eyles JP; Feng HJ; Fortin M; Franettovich Smith MM; Galloway G; Gandomkar Z; Glastras S; Henderson LA; Hides JA; Hiller CE; Hilmer SN; Hoggarth MA; Kim B; Lal N; LaPorta L; Magnussen JS; Maloney S; March L; Nackley AG; O' Leary SP; Peolsson A; Perraton Z; Pool-Goudzwaard AL; Schnitzler M; Seitz AL; Semciw AI; Sheard PW; Smith AC; Snodgrass SJ; Sullivan J; Tran V; Valentin S; Walton DM; Wishart LR; Elliott JM; | 39590726 HKAP |
| 8 | A protocol for trustworthy EEG decoding with neural networks | Borra D; Magosso E; Ravanelli M; | 39549492 ENCS |
| 9 | Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks | Adcock B; Brugiapaglia S; Dexter N; Moraga S; | 39454372 MATHSTATS |
| 10 | Deep neural network-based robotic visual servoing for satellite target tracking | Ghiasvand S; Xie WF; Mohebbi A; | 39440297 ENCS |
| 11 | Generalization limits of Graph Neural Networks in identity effects learning | D' Inverno GA; Brugiapaglia S; Ravanelli M; | 39426036 ENCS |
| 12 | The immunomodulatory effect of oral NaHCO3 is mediated by the splenic nerve: multivariate impact revealed by artificial neural networks | Alvarez MR; Alkaissi H; Rieger AM; Esber GR; Acosta ME; Stephenson SI; Maurice AV; Valencia LMR; Roman CA; Alarcon JM; | 38549144 CSBN |
| 13 | Reinforcement learning for automatic quadrilateral mesh generation: A soft actor-critic approach | Pan J; Huang J; Cheng G; Zeng Y; | 36375347 ENCS |
| 14 | Comparative Evaluation of Artificial Neural Networks and Data Analysis in Predicting Liposome Size in a Periodic Disturbance Micromixer | Ocampo I; López RR; Camacho-León S; Nerguizian V; Stiharu I; | 34683215 ENCS |
| 15 | X-Vectors: New Quantitative Biomarkers for Early Parkinson's Disease Detection From Speech | Jeancolas L; Petrovska-Delacrétaz D; Mangone G; Benkelfat BE; Corvol JC; Vidailhet M; Lehéricy S; Benali H; | 33679361 PERFORM |
| Title: | Distinguishing Between Healthy and Unhealthy Newborns Based on Acoustic Features and Deep Learning Neural Networks Tuned by Bayesian Optimization and Random Search Algorithm | ||||
| Authors: | Lahmiri S, Tadj C, Gargour C | ||||
| Link: | https://pubmed.ncbi.nlm.nih.gov/41294952/ | ||||
| DOI: | 10.3390/e27111109 | ||||
| Publication: | Entropy (Basel, Switzerland) | ||||
| Keywords: | Bayesian optimization; Mel-frequency cepstral coefficients; auditory-inspired amplitude modulation; deep feedforward neural networks; newborn cry; prosody; random search optimization; | ||||
| PMID: | 41294952 | Category: | Date Added: | 2025-11-26 | |
| Dept Affiliation: |
ENCS
1 Department of Supply Chain and Business Technology Management, John Molson School of Business, Concordia University, Montreal, QC H3G 1M8, Canada. 2 Department of Electrical Engineering, École de Technologie Supérieure, Montreal, QC H3C 1K3, Canada. |
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Description: |
Voice analysis and classification for biomedical diagnosis purpose is receiving a growing attention to assist physicians in the decision-making process in clinical milieu. In this study, we develop and test deep feedforward neural networks (DFFNN) to distinguish between healthy and unhealthy newborns. The DFFNN are trained with acoustic features measured from newborn cries, including auditory-inspired amplitude modulation (AAM), Mel Frequency Cepstral Coefficients (MFCC), and prosody. The configuration of the DFFNN is optimized by using Bayesian optimization (BO) and random search (RS) algorithm. Under both optimization techniques, the experimental results show that the DFFNN yielded to the highest classification rate when trained with all acoustic features. Specifically, the DFFNN-BO and DFFNN-RS achieved 87.80% ± 0.23 and 86.12% ± 0.33 accuracy, respectively, under ten-fold cross-validation protocol. Both DFFNN-BO and DFFNN-RS outperformed existing approaches tested on the same database. |
