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HELP: A computational framework for labelling and predicting human common and context-specific essential genes.

• Authors : Granata I; Institute for High-Performance Computing and Networking, National Research Council, Naples, Italy.; Maddalena L

Subjects: Computational Biology*/Computational Biology*/Computational Biology*/methods ; Genes, Essential*/Genes, Essential*/Genes, Essential*/genetics ; Machine Learning*

• Source: PLoS computational biology [PLoS Comput Biol] 2024 Sep 27; Vol. 20 (9), pp. e1012076. Date of Electronic Publication: 2024 Sep 27 (Print Publication: 2024).Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet

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AI-Assisted Cotton Grading: Active and Semi-Supervised Learning to Reduce the Image-Labelling Burden.

• Authors : Fisher OJ; Food, Water, Waste Research Group, Faculty of Engineering, University of Nottingham, Nottingham NG7 2RD, UK.; School of Chemistry and Chemical Engineering, University of Surrey, Guildford GU2 7XH, UK.

Subjects: Supervised Machine Learning* ; Machine Learning*; Random Forest

• Source: Sensors (Basel, Switzerland) [Sensors (Basel)] 2023 Oct 24; Vol. 23 (21). Date of Electronic Publication: 2023 Oct 24.Publisher: MDPI Country of Publication: Switzerland NLM ID: 101204366 Publication Model: Electronic Cited Medium: Internet ISSN: 1424-8220

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Manifold Explorer: Satellite Image Labelling and Clustering Tool with Using Deep Convolutional Autoencoders.

• Authors : Patel, Tulsi¹ (AUTHOR) ; Jones, Mark W.¹ (AUTHOR) ; Redfern, Thomas² (AUTHOR)

• Source: Algorithms. Oct2023, Vol. 16 Issue 10, p469. 17p.

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Using multi-label ensemble CNN classifiers to mitigate labelling inconsistencies in patch-level Gleason grading.

• Authors : Butt, Muhammad Asim¹ (AUTHOR) ; Kaleem, Muhammad Farhat² (AUTHOR); Bilal, Muhammad^3,4 (AUTHOR)

Subjects: *DEEP learning; *PROSTATE cancer prognosis; *NAIVE Bayes classification

• Source: PLoS ONE. 7/5/2024, Vol. 19 Issue 7, p1-24. 24p.

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Auto-Classification of Parkinson's Disease with Different Motor Subtypes Using Arterial Spin Labelling MRI Based on Machine Learning.

• Authors : Xiong, Jinhua¹ (AUTHOR) ; Zhu, Haiyan² (AUTHOR); Li, Xuhang³ (AUTHOR)

• Source: Brain Sciences (2076-3425). Nov2023, Vol. 13 Issue 11, p1524. 11p.

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Automated labelling of radiology reports using natural language processing: Comparison of traditional and newer methods

• Authors : Seo Yi Chng; Paul J. W. Tern; Matthew R. X. Kan

Subjects: automated labelling; machine learning; natural language processing

• Source: Health Care Science, Vol 2, Iss 2, Pp 120-128 (2023)

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Pattern Labelling of Business Communication Data.

• Authors : Kaya, Muhammed-Fatih (AUTHOR)

Subjects: BUSINESS communication; DATA transmission systems; DISCOVERY (Law)

• Source: Group Decision & Negotiation. Dec2022, Vol. 31 Issue 6, p1203-1234. 32p.

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Self-labelling of tugboat operation using unsupervised machine learning and intensity indicator

• Authors : Januwar Hadi; Dimitrios Konovessis; Zhi Yung Tay

Subjects: Machine learning; Self-labelling; Intensity indicators

• Source: Maritime Transport Research, Vol 4, Iss , Pp 100082- (2023)

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A Machine-Learning-Based Labelling Diversity Model for Predictive Analysis: Using 16QAM as a Case Study

• Authors : Shaheen Solwa; Mohamed K. Elmezughi; Omran Salih

Subjects: Labelling diversity; machine learning; mean square error

• Source: IEEE Access, Vol 10, Pp 91840-91854 (2022)

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Evaluation of single-cell RNAseq labelling algorithms using cancer datasets.

• Authors : Christensen, Erik^1,2 (AUTHOR); Luo, Ping³ (AUTHOR); Turinsky, Andrei⁴ (AUTHOR)

• Source: Briefings in Bioinformatics. Jan2023, Vol. 24 Issue 1, p1-16. 16p.

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