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Predicting Surgical Site Infection after Lumbar Laminectomy and Discectomy: A Cutting-edge Algorithmic Approach by Incorporating Ensembled Stacking into the Current State-of-the-art for Automated Machine Learning.
Bangash, Ali Haider ; Mani, Kyle ; Goldman, Samuel N. ; et al.
Neurosurgical Review; 9/18/2025, Vol. 48 Issue 1, p1-12, 12p

SURGICAL site infections MACHINE learning BOOSTING algorithms ENSEMBLE learning DISCECTOMY SPINAL surgery …
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Bias Begins with Data: The FairGround Corpus for Robust and Reproducible Research on Algorithmic Fairness
Simson, Jan ; Fabris, Alessandro ; Fröhner, Cosima ; et al.

Machine Learning Computers and Society
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Application on Information Island with Information Visualization and Software Engineering
Lv, Jiahui ; Shen, Kaimin ; Johnson, Shardrom ; et al.
2018 5th International Conference on Systems and Informatics (ICSAI) Systems and Informatics (ICSAI), 2018 5th International Conference on. :598-603 Nov, 2018

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6

Research on the Integration and Innovation of Artificial Intelligence and Big Data in the Digital Transformation of the Economy.
Ju, Yun ; Su, Xiao ; Tian, Ze
International Journal of High Speed Electronics & Systems. Jul2025, p1. 18p.

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Identifying resource-rational heuristics for risky choice.
Krueger, Paul M. ; Callaway, Frederick ; Gul, Sayan ; et al.
Psychol Rev

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8

Working with the Digraph3 Python Resources
Bisdorff, Raymond
International Series in Operations Research & Management Science ; Algorithmic Decision Making with Python Resources ; page 3-12 ; ISSN 0884-8289 2214-7934 ; ISBN 9783030909277 9783030909284

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Heuristics from bounded meta-learned inference.
Binz, Marcel ; Gershman, Samuel J. ; Schulz, Eric ; et al.
Psychol Rev

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Consumer decisions in virtual commerce: Predict good help-timing based on cognitive load.
Weiß, Tobias ; Pfeiffer, Jella
J Neurosci Psychol Econ

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11

Bayesian inference for evidence accumulation models with regressors.
Dao, Viet Hung ; Gunawan, David ; Kohn, Robert ; et al.
Psychol Methods

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12

Using algorithmic game theory to improve supervised machine learning: A novel applicability approach in flood susceptibility mapping.
Nasiri Khiavi A ; Vafakhah M
Publisher: Springer Country of Publication: Germany NLM ID: 9441769 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1614-7499 (Electronic) Linking ISSN: 09441344 NLM ISO Abbreviation: Environ Sci Pollut Res Int Subsets: MEDLINE

Iran Machine Learning Floods Algorithms Support Vector Machine Supervised Machine Learn... …
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13

The Data Journalism Handbook : Towards A Critical Data Practice
Bounegru, Liliana ; Gray, Jonathan ; Bounegru, Liliana ; et al.

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14

Process and content in decisions from memory.
Zhao, Wenjia Joyce ; Richie, Russell ; Bhatia, Sudeep
Psychol Rev

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15

Computational signatures of inequity aversion in children across seven societies.
Amir, Dorsa ; Melnikoff, David ; Warneken, Felix ; et al.
Journal of Experimental Psychology

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16

Rating-by-Ranking with Learned Performance Quantile Norms
Bisdorff, Raymond
International Series in Operations Research & Management Science ; Algorithmic Decision Making with Python Resources ; page 125-136 ; ISSN 0884-8289 2214-7934 ; ISBN 9783030909277 9783030909284

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17

Working with Bipolar-Valued Digraphs
Bisdorff, Raymond
International Series in Operations Research & Management Science ; Algorithmic Decision Making with Python Resources ; page 13-27 ; ISSN 0884-8289 2214-7934 ; ISBN 9783030909277 9783030909284

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18

Building a Best Choice Recommendation
Bisdorff, Raymond
International Series in Operations Research & Management Science ; Algorithmic Decision Making with Python Resources ; page 41-54 ; ISSN 0884-8289 2214-7934 ; ISBN 9783030909277 9783030909284

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19

Rating by Sorting into Relative Performance Quantiles
Bisdorff, Raymond
International Series in Operations Research & Management Science ; Algorithmic Decision Making with Python Resources ; page 115-124 ; ISSN 0884-8289 2214-7934 ; ISBN 9783030909277 9783030909284

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20

Working with Outranking Digraphs
Bisdorff, Raymond
International Series in Operations Research & Management Science ; Algorithmic Decision Making with Python Resources ; page 29-38 ; ISSN 0884-8289 2214-7934 ; ISBN 9783030909277 9783030909284

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