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Features selected by the Chi <t> 2 feature </t> ranking for each dataset and for methods used in exudate segmentation.
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Features selected by the Chi <t> 2 feature </t> ranking for each dataset and for methods used in exudate segmentation.
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Performance of the various machine learning approaches employed for identifying unsafe food products
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Features selected by the Chi 2 feature ranking for each dataset and for methods used in exudate segmentation.

Journal: Scientific Reports

Article Title: Diabetic retinopathy detection via exudates and hemorrhages segmentation using iterative NICK thresholding, watershed, and Chi 2 feature ranking

doi: 10.1038/s41598-025-90048-6

Figure Lengend Snippet: Features selected by the Chi 2 feature ranking for each dataset and for methods used in exudate segmentation.

Article Snippet: To further improve our results in different applications, we incorporated the watershed separation algorithm (WS) and the Chi 2 feature selection method (Chi 2 ) on expanded feature sets.

Techniques: Standard Deviation

General Characteristics of Included Studies

Journal: JAMA Otolaryngology-- Head & Neck Surgery

Article Title: Comparison of Postmarketing Findings vs the Initial Clinical Validation Findings of a Thyroid Nodule Gene Expression Classifier

doi: 10.1001/jamaoto.2019.1449

Figure Lengend Snippet: General Characteristics of Included Studies

Article Snippet: Baca et al, 2017 , January 2012-July 2016 , Brigham & Women's Hospital , No , Academic , No , Yes/Yes d , COI with Veracyte , A/FLUS (selective use; >1 cm, without oncocytic features; 36% were A/FLUS in 2 FNA biopsies).

Techniques: Biomarker Discovery

Performance of the various machine learning approaches employed for identifying unsafe food products

Journal: JAMIA Open

Article Title: Detecting reports of unsafe foods in consumer product reviews

doi: 10.1093/jamiaopen/ooz030

Figure Lengend Snippet: Performance of the various machine learning approaches employed for identifying unsafe food products

Article Snippet: Multinomial Naive Bayes (Feature selection using Chi 2 , k = 500) , 0.66 , 0.66 , 0.66.

Techniques: Selection, Sequencing