Line plots of performance metrics across TFIDF conditions.

Line plots of performance metrics across TFIDF conditions.

<p>Mean (y-axis) of recall, precision, and F1-score (as labelled) of all testers, for each clinicopathologic finding (key), across the four TFIDF conditions (x-axis) tested in a pilot test of the application, DEE, designed for extraction of necropsy data from the Wildbase Pathology Register.&l...

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Номзүйн дэлгэрэнгүй
Үндсэн зохиолч:	Stefan Saverimuttu (20882325) (author)
Бусад зохиолчид:	Kate McInnes (7520158) (author), Kristin Warren (3339657) (author), Lian Yeap (21221659) (author), Stuart Hunter (2498485) (author), Brett Gartrell (6325817) (author), An Pas (12001965) (author), James Chatterton (20347204) (author), Bethany Jackson (3339660) (author)
Хэвлэсэн:	2025
Нөхцлүүд:	Ecology Information Systems not elsewhere classified wildlife necropsy data wildbase pathology register study evaluates part score &# 8212 pilot study highlights one health objectives limited terminological variance examine ), designed driven misclassification patterns consuming process poses analysed alongside tester 63 &# 8211 terminological variance may efficiently derive insights text clinical data search term selection efficient data retrieval four clinicopathologic findings highest performance scores scores across knowledge retrieval extracting insights efficient utilisation clinicopathologic finding tested findings findings reveal findings characterized xlink "> valuable resources results highlight relatively simple rapid analysis principals underlying mining approaches mining application may describe manual review external oiling diphtheritic stomatitis broader implementation bespoke text based text automatically capture application testers advancing conservation
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!

Ижил төстэй зүйлс

Statistics of search terms and stems. Mean, standard deviation, and range of the number of selected search terms and number of 3 letter word stems derived from these search terms, across testers and clinicopathologic findings in the pilot test of an application for extraction of necropsy data from the Wildbase Pathology Register, DEE.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Metrics of application performance. Mean, standard deviation, and range of recall, precision, and calculated F1-score of all four tested clinicopathologic findings across all testers of the application for extraction of necropsy data from the Wildbase Pathology Register, DEE.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Quantification of misclassification categorisation. Misclassification categories quantified across all testers and clinicopathologic findings for false positives and false negatives in a pilot test of the text-mining application; DEE, designed for the rapid retrieval of necropsy data from free-text reports within the Wildbase Pathology Register of Aotearoa New Zealand.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Table of misclassification coding structure. Codes in the left-hand column were given to individual records misclassified by the application according to the false positive and false negative code definitions and examples described.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Clinicopathologic finding descriptions given for each dataset, and reference name of each finding in this study.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Violin plots of performance metrics across all testers.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Bar charts of false positive misclassifications for tested clinicopathologic findings across all testers.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Bar charts of false negative misclassifications for tested clinicopathologic findings across all testers.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Summarised workflow of the ‘Examine’ section of DEE.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Violin plot of all application test performance metrics.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

All tester data.
-н: Stefan Saverimuttu (20882325)
Хэвлэсэн: (2025)

Image 1_The relationship between social emotions and intuitive eating behaviors: an exploration based on text analysis.pdf
-н: Jing Wu (54032)
Хэвлэсэн: (2025)

اقتضاء النص عند الأصوليين وتطبيقاته في القانون المدني الأردني
-н: Al-Saleh, Abdullah
Хэвлэсэн: (2021)

التعارض بين النصوص: أسبابه ودفعه
-н: Almujahed, Muhammad Said
Хэвлэсэн: (2020)

Multilevel logistic regression models with each negative emotions as a predictor.
-н: Chan-Young Ahn (22683343)
Хэвлэсэн: (2025)

Confusion Matrix for Binary Classification.
-н: Chan-Young Ahn (22683343)
Хэвлэсэн: (2025)

Associations between pre-assessment self-report measures and EMA (14-day) ratings.
-н: Chan-Young Ahn (22683343)
Хэвлэсэн: (2025)

Descriptive statistics of demographic and clinical characteristics.
-н: Chan-Young Ahn (22683343)
Хэвлэсэн: (2025)

Feature importance scores of the predictors.
-н: Chan-Young Ahn (22683343)
Хэвлэсэн: (2025)

Supplementary material JImaging-3990735
-н: Adrien Deliege (22675676)
Хэвлэсэн: (2025)

Maximum clade credibility (MCC) trees of phylodynamic models for transmission in farm A.
-н: Marina Meester (11765542)
Хэвлэсэн: (2025)

Output of phylodynamic (BD) and SEIR model to estimate the effective reproduction number of between-pen transmission (between-pen R<sub>e</sub>) for farm B, compartment 2 during weeks 7 to 16 of batch B.
-н: Marina Meester (11765542)
Хэвлэсэн: (2025)

Infection dynamics and phylogenetics of HEV in two farms.
-н: Marina Meester (11765542)
Хэвлэсэн: (2025)

Schematic overview of a pig farm and the three hypothesized environmental transmission routes (indicated by pink arrows) of hepatitis E virus in farms.
-н: Marina Meester (11765542)
Хэвлэсэн: (2025)

تجديد الاصطلاح الفقهي عند الشيخ مصطفى الزرقا
-н: Alajmi, Muhammad Mahdi Muhammad
Хэвлэсэн: (2022)

Synthetic event log with control-flow deviations and known ground-truth causal factors from a loan application process
-н: Deanna Coralage (20557091)
Хэвлэсэн: (2025)

Data Sheet 1_Enhancing preoperative HER2 status classification of invasive breast cancers using machine learning models based on clinicopathological and MRI features: a multicenter study.docx
-н: Suhong Zhao (10057478)
Хэвлэсэн: (2025)

Medication-inclusive multivariable logistic regression for MAFLD.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Multivariable logistic regression models for MAFLD predictors.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Liver Fibrosis Characteristics by CKD Stage in MAFLD Patients (n = 64).
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Liver Stiffness and Fibrosis Grading by MAFLD Status.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Comparison of Non-invasive Liver Fibrosis Scores.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Demographic and Clinical Characteristics of Study Participants.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Proposed pathophysiological crosstalk between MAFLD and CKD.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Receiver operating characteristic (ROC) curve analysis comparing the performance of non-invasive fibrosis scores in MAFLD patients.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Stratification of Liver Stiffness according to eGFR in the MAFLD group.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

A. Violin plots showing eGFR distribution in MAFLD (red) vs. non-MAFLD (blue) groups.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

Grades of liver fibrosis in MAFLD group (grey) and non-MAFLD group (black).
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

eGFR in the study participants.
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

2D–shear-wave elastography example: MAFLD + CKD case (female, 57 years).
-н: Zienab M. Saad (22676502)
Хэвлэсэн: (2025)

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