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Carole Koechli

Showing results (1-10 of 9) with videos related to

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European Journal of Radiology|May 19, 2023
Radiomics and machine learning for predicting the consistency of benign tumors of the central nervous system: A systematic reviewCarole Koechli, Daniel R Zwahlen, Philippe Schucht, et al.
Cancers|June 10, 2022
Machine Learning for the Detection and Segmentation of Benign Tumors of the Central Nervous System: A Systematic ReviewPaul Windisch, Carole Koechli, Susanne Rogers, et al.
Oncology|June 15, 2025
A Pipeline for the Automatic Identification of Randomized Controlled Oncology Trials and Assignment of Tumor Entities Using Natural Language ProcessingPaul Windisch, Fabio Dennstädt, Carole Koechli, et al.
JMIR Cancer|January 21, 2026
Large Language Models for Supporting Clear Writing and Detecting Spin in Randomized Controlled Trials in Oncology: Comparative Analysis of GPT Models and PromptsCarole Koechli, Fabio Dennstädt, Christina Schröder, et al.
Journal of the American Medical Informatics Association : JAMIA|March 30, 2026
Is one run enough? Reproducibility of flagship large language models across temperature and reasoning settings in biomedical text processingPaul Windisch, Carole Koechli, Fabio Dennstädt, et al.
JCO Clinical Cancer Informatics|November 27, 2024
Metastatic Versus Localized Disease as Inclusion Criteria That Can Be Automatically Extracted From Randomized Controlled Trials Using Natural Language ProcessingPaul Windisch, Fabio Dennstädt, Carole Koechli, et al.
Cureus|January 15, 2025
The Impact of Temperature on Extracting Information From Clinical Trial Publications Using Large Language ModelsPaul Windisch, Fabio Dennstädt, Carole Koechli, et al.
JAMIA Open|October 28, 2024
Predicting the sample size of randomized controlled trials using natural language processingPaul Windisch, Fabio Dennstädt, Carole Koechli, et al.
Cancers|May 14, 2022
Convolutional Neural Networks to Detect Vestibular Schwannomas on Single MRI Slices: A Feasibility StudyCarole Koechli, Erwin Vu, Philipp Sager, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
European Journal of Radiology|May 19, 2023
Radiomics and machine learning for predicting the consistency of benign tumors of the central nervous system: A systematic reviewCarole Koechli, Daniel R Zwahlen, Philippe Schucht, et al.
Cancers|June 10, 2022
Machine Learning for the Detection and Segmentation of Benign Tumors of the Central Nervous System: A Systematic ReviewPaul Windisch, Carole Koechli, Susanne Rogers, et al.
Oncology|June 15, 2025
A Pipeline for the Automatic Identification of Randomized Controlled Oncology Trials and Assignment of Tumor Entities Using Natural Language ProcessingPaul Windisch, Fabio Dennstädt, Carole Koechli, et al.
JMIR Cancer|January 21, 2026
Large Language Models for Supporting Clear Writing and Detecting Spin in Randomized Controlled Trials in Oncology: Comparative Analysis of GPT Models and PromptsCarole Koechli, Fabio Dennstädt, Christina Schröder, et al.
Journal of the American Medical Informatics Association : JAMIA|March 30, 2026
Is one run enough? Reproducibility of flagship large language models across temperature and reasoning settings in biomedical text processingPaul Windisch, Carole Koechli, Fabio Dennstädt, et al.
JCO Clinical Cancer Informatics|November 27, 2024
Metastatic Versus Localized Disease as Inclusion Criteria That Can Be Automatically Extracted From Randomized Controlled Trials Using Natural Language ProcessingPaul Windisch, Fabio Dennstädt, Carole Koechli, et al.
Cureus|January 15, 2025
The Impact of Temperature on Extracting Information From Clinical Trial Publications Using Large Language ModelsPaul Windisch, Fabio Dennstädt, Carole Koechli, et al.
JAMIA Open|October 28, 2024
Predicting the sample size of randomized controlled trials using natural language processingPaul Windisch, Fabio Dennstädt, Carole Koechli, et al.
Cancers|May 14, 2022
Convolutional Neural Networks to Detect Vestibular Schwannomas on Single MRI Slices: A Feasibility StudyCarole Koechli, Erwin Vu, Philipp Sager, et al.
Pageof 1