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Addressing Threats to Validity in Supervised Machine Learning: A Framework and Best Practices for Education Researchers. EdWorkingPaper No. 25-1117

• Authors : Kylie L. Anglin; Annenberg Institute for School Reform at Brown University

Subjects: Validity; Artificial Intelligence; Models

• Source: Annenberg Institute for School Reform at Brown University. 2025.62

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GRB Redshift Classifier to Follow up High-redshift GRBs Using Supervised Machine Learning

• Authors : Dainotti, Maria Giovanna; Bhardwaj, Shubham; Cook, Christopher ...

Subjects: Natural Sciences; Physical Sciences; Astronomy

• Source: Astrophysical Journal, Supplement Series. 277(1)

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Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome.

• Authors : Pons-Suñer P; ITI, Universitat Politècnica de València, Valencia, Spain. .; Signol F

Subjects: Leukemia, Myeloid, Acute*/Leukemia, Myeloid, Acute*/Leukemia, Myeloid, Acute*/therapy ; Leukemia, Myeloid, Acute*/Leukemia, Myeloid, Acute*/Leukemia, Myeloid, Acute*/diagnosis ; Leukemia, Myeloid, Acute*/Leukemia, Myeloid, Acute*/Leukemia, Myeloid, Acute*/complications

• Source: BMC medical informatics and decision making [BMC Med Inform Decis Mak] 2025 May 01; Vol. 25 (1), pp. 179. Date of Electronic Publication: 2025 May 01.Publisher: BioMed Central Country of Publication: England NLM ID: 101088682 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6947

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Supervised Machine Learning and Physics Machine Learning approach for prediction of peak temperature distribution in Additive Friction Stir Deposition of Aluminium Alloy.

• Authors : Mishra A; School of Industrial and Information Engineering, Politecnico Di Milano, Milan, Italy.; Jatt V

Subjects: Alloys*/Alloys*/Alloys*/chemistry ; Aluminum*/Aluminum*/Aluminum*/chemistry ; Supervised Machine Learning*

• Source: PloS one [PLoS One] 2025 Apr 04; Vol. 20 (4), pp. e0309751. Date of Electronic Publication: 2025 Apr 04 (Print Publication: 2025).Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet

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Multiple, Single Trait GWAS and Supervised Machine Learning Reveal the Genetic Architecture of Fraxinus excelsior Tolerance to Ash Dieback in Europe

• Authors : Cleary, Michelle; Sveriges lantbruksuniversitet, Originator

Subjects: Botany; Botanik; Forest Science

• Source: Plant, Cell and Environment. 48:3793-3809

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A Supervised Machine Learning Model for Dental Crowns Material Design for Manufacturing.

• Authors : Osama, Adel¹ ; Fouda, Noha²; Eraky, Mohamed T.²

• Source: Egyptian International Journal of Engineering Sciences & Technology (EIJEST). Jun2025, Vol. 50 Issue 2, p30-47. 18p.

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Addressing Threats to Validity in Supervised Machine Learning: A Framework and Best Practices for Education Researchers

• Authors : Kylie Anglin (ORCID 0000-0001-7661-3370)

Subjects: Validity; Artificial Intelligence; Models

• Source: AERA Open. 2024 10(1).21

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Analysis of Two Neuroanatomical Subtypes of Parkinson's Disease and Their Motor Progression Based on Semi-Supervised Machine Learning.

• Authors : Zhou H; Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China.; Wu Y

Subjects: Parkinson Disease*/Parkinson Disease*/Parkinson Disease*/diagnostic imaging ; Parkinson Disease*/Parkinson Disease*/Parkinson Disease*/classification ; Parkinson Disease*/Parkinson Disease*/Parkinson Disease*/physiopathology

• Source: CNS neuroscience & therapeutics [CNS Neurosci Ther] 2025 Feb; Vol. 31 (2), pp. e70277.Publisher: Wiley-Blackwell Country of Publication: England NLM ID: 101473265 Publication Model: Print Cited Medium: Internet ISSN: 1755-5949

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Identification of patient demographic, clinical, and SARS-CoV-2 genomic factors associated with severe COVID-19 using supervised machine learning: a retrospective multicenter study.

• Authors : Nirmalarajah K; Sunnybrook Research Institute, Toronto, ON, Canada.; Public Health Ontario, 661 University Avenue, Toronto, ON, Canada.

Subjects: COVID-19*/COVID-19*/COVID-19*/virology ; COVID-19*/COVID-19*/COVID-19*/epidemiology ; COVID-19*/COVID-19*/COVID-19*/pathology

• Source: BMC infectious diseases [BMC Infect Dis] 2025 Jan 28; Vol. 25 (1), pp. 132. Date of Electronic Publication: 2025 Jan 28.Publisher: BioMed Central Country of Publication: England NLM ID: 100968551 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2334

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Predicting macular hole surgery outcomes: Integrating preoperative OCT features with supervised machine learning statistical models.

• Authors : Venkatesh R; Department of Retina and Vitreous, Narayana Nethralaya, Rajaji Nagar, Bengaluru, Karnataka, India.; Gandhi P

Subjects: Tomography, Optical Coherence*/Tomography, Optical Coherence*/Tomography, Optical Coherence*/methods ; Retinal Perforations*/Retinal Perforations*/Retinal Perforations*/surgery ; Retinal Perforations*/Retinal Perforations*/Retinal Perforations*/diagnosis

• Source: Indian journal of ophthalmology [Indian J Ophthalmol] 2025 Jan 01; Vol. 73 (Suppl 1), pp. S66-S71. Date of Electronic Publication: 2024 Dec 24.Publisher: Medknow Publications Country of Publication: India NLM ID: 0405376 Publication Model: Print-Electronic Cited Medium: Internet ISSN:

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