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Enhanced heart sound classification using Mel frequency cepstral coefficients and comparative analysis of single vs. ensemble classifier strategies.
PLoS One
December 2024
Future Technology Research Center, National Yunlin University of Science and Technology, Yunlin, Taiwan.
This paper seeks to enhance the performance of Mel Frequency Cepstral Coefficients (MFCCs) for detecting abnormal heart sounds. Heart sounds are first pre-processed to remove noise and then segmented into S1, systole, S2, and diastole intervals, with thirteen MFCCs estimated from each segment, yielding 52 MFCCs per beat. Finally, MFCCs are used for heart sound classification.
View Article and Find Full Text PDFNovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.
J Proteome Res
December 2024
Department of Artificial Intelligence, Hanyang University, Seoul 04763, Republic of Korea.
peptide sequencing is a valuable technique in mass-spectrometry-based proteomics, as it deduces peptide sequences directly from tandem mass spectra without relying on sequence databases. This database-independent method, however, relies solely on imperfect scoring functions that often lead to erroneous peptide identifications. To boost correct identification, we present NovoRank, a postprocessing tool that employs spectral clustering and machine learning to assign more plausible peptide sequences to spectra.
View Article and Find Full Text PDFIdentification of novel therapeutic targets for head and neck squamous cell carcinoma through bioinformatics analysis.
Sci Rep
December 2024
Department of Otorhinolaryngology-Head and Neck Surgery, Korea University College of Medicine, 35365, Seoul, Korea.
Head and neck squamous cell carcinoma (HNSCC) is a heterogeneous cancer with limited therapeutic options. Using publicly available datasets, we identified the WD repeat domain 54 (WDR54) gene as a potential therapeutic target in HNSCC. Gene expression profiling interactive analysis version 2 (GEPIA2) was used to identify genes differentially overexpressed in HNSCC.
View Article and Find Full Text PDFFostering children's creativity through LLM-driven storytelling with a social robot.
Front Robot AI
December 2024
Embodied Social Agents Lab (ESAL), Department of Electrical Engineering and Computer Science (EECS), KTH Royal Institute of Technology, Stockholm, Sweden.
Creativity is an important skill that is known to plummet in children when they start school education that limits their freedom of expression and their imagination. On the other hand, research has shown that integrating social robots into educational settings has the potential to maximize children's learning outcomes. Therefore, our aim in this work was to investigate stimulating children's creativity through child-robot interactions.
View Article and Find Full Text PDFCrop yield prediction in agriculture: A comprehensive review of machine learning and deep learning approaches, with insights for future research and sustainability.
Heliyon
December 2024
Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Selangor, Malaysia.
The agriculture sector is confronted with numerous challenges in the quest for accurate crop yield estimation, which is essential for efficient resource management and mitigating food scarcity in a rapidly growing global population. This research paper delves into the application of advanced Artificial Intelligence (AI) techniques to enhance crop yield estimation in the context of diverse agricultural challenges. Through a systematic literature review and analysis of relevant studies, this paper explores the role of AI methods, such as Machine Learning (ML) and Deep Learning (DL), in addressing the complexities posed by geographical variations, crop diversity, and cultivation areas.
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