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Explainable e-sports win prediction through Machine Learning classification in streaming

• Authors : García-Méndez, Silvia; de Arriba-Pérez, Francisco

Subjects: Artificial Intelligence

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Pipeline for FlowCam data processing with modular open-source software and optional machine learning classification

• Authors : Katerina Symiakaki; Tim J. W. Walles; Cassidy Park

Subjects: FlowCam; Plankton; Machine learning classification

• Source: PeerJ, Vol 14, p e20754 (2026)

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Identifying Children with Clinical Language Disorder: An Application of Machine-Learning Classification

• Authors : Justice, Laura M.; Ahn, Woo-Young; Logan, Jessica A. R.

Subjects: Language Impairments; Disability Identification; Clinical DiagnosisSocial Skills Rating System

• Source: Journal of Learning Disabilities. Sep-Oct 2019 52(5):351-365.15

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Evaluation of six machine learning classification algorithms in pig breed identification using SNPs array data.

• Authors : Liu R; National Engineering Research Center for Breeding Swine Industry, Guangdong Provincial Key Lab of Agro-Animal Genomics and Molecular Breeding, Guangdong Laboratory of Lingnan Modern Agriculture, College of Animal Science, South China Agricultural University, Guangzhou, China.; Xu Z

Subjects: Artificial Intelligence* ; Polymorphism, Single Nucleotide*; Animals

• Source: Animal genetics [Anim Genet] 2023 Apr; Vol. 54 (2), pp. 113-122. Date of Electronic Publication: 2022 Dec 02.Publisher: Wiley-Blackwell Country of Publication: England NLM ID: 8605704 Publication Model: Print-Electronic Cited Medium: Internet ISSN:

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Optimizing NFL Draft Selections with Machine Learning Classification.

• Authors : Enaganti, Akshaj¹ (AUTHOR); Pappas, George¹ (AUTHOR)

• Source: AI. Sep2025, Vol. 6 Issue 9, p221. 18p.

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Comparing Machine Learning Classification Approaches for Predicting Expository Text Difficulty

• Authors : Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S.

Subjects: Artificial Intelligence; Classification; Comparative AnalysisFlesch Kincaid Grade Level Formula

• Source: Grantee Submission. 2018Paper presented at the International Florida Artificial Intelligence Research Society Conference (31st, Melbourne, FL, May 6

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Latent Supervision: A Method for Improved Performance and Calibration of Machine Learning Classification Models in Ophthalmology

• Authors : Hady Yazbeck, MD; Jad Assaf, MD; Tom M. Lietman, MD

Subjects: Latent class analysis; Artificial intelligence; Trachoma

• Source: Ophthalmology Science, Vol 6, Iss 5, Pp 101151- (2026)

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Weight optimization of steel lattice transmission towers based on Differential Evolution and machine learning classification technique

• Authors : Tran-Hieu Nguyen; Anh-Tuan Vu

Subjects: Artificial intelligence; Tower; TA630-695

• Source: Fracture and Structural Integrity, Vol 16, Iss 59, Pp 172-187 (2022)Fracture and Structural Integrity, Vol 16, Iss 59 (2021)Frattura ed Integrità Strutturale; Vol. 16 No. 59 (2022):

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An Explainable AI Exploration of the Machine Learning Classification of Neoplastic Intracerebral Hemorrhage from Non-Contrast CT.

• Authors : Schulze-Weddige, Sophia¹ (AUTHOR) ; Baumgärtner, Georg Lukas^1,2 (AUTHOR); Orth, Tobias^1,3 (AUTHOR)

• Source: Cancers. Aug2025, Vol. 17 Issue 15, p2502. 13p.

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Vowel segmentation impact on machine learning classification for chronic obstructive pulmonary disease

• Authors : Idrisoglu, Alper; Moraes, Ana Luiza Dallora; Cheddad, Abbas

Subjects: Male; Support Vector Machine; Respiratory Medicine and Allergy

• Source: Sci RepScientific Reports, Vol 15, Iss 1, Pp 1-14 (2025)

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