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Showing results (291-300 of 321) with videos related to

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Neuro-Oncology|August 30, 2024
Multimodal deep learning improves recurrence risk prediction in pediatric low-grade gliomasMaryamalsadat Mahootiha, Divyanshu Tak, Zezhong Ye, et al.
Medrxiv : the Preprint Server for Health Sciences|November 28, 2024
Leveraging Deep Learning of Chest Radiograph Images to Identify Individuals at High Risk for Chronic Obstructive Pulmonary DiseaseSaman Doroodgar Jorshery, Jay Chandra, Anika S Walia, et al.
Nature|March 19, 2026
Thymic health and immunotherapy outcomes in patients with cancerSimon Bernatz, Vasco Prudente, Suraj Pai, et al.
The Lancet. Digital Health|April 22, 2023
Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trialBenjamin H Kann, Jirapat Likitlersuang, Dennis Bontempi, et al.
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology|December 23, 2025
Automated Lymph Node and Extranodal Extension Assessment Improves Risk Stratification in Oropharyngeal CarcinomaZezhong Ye, Reza Mojahed-Yazdi, Anna Zapaishchykova, et al.
Nature Communications|November 9, 2023
Automated temporalis muscle quantification and growth charts for children through adulthoodAnna Zapaishchykova, Kevin X Liu, Anurag Saraf, et al.
Proceedings of the National Academy of Sciences of the United States of America|March 4, 2015
Horizontal gene transfer and gene dosage drives adaptation to wood colonization in a tree pathogenBraham Dhillon, Nicolas Feau, Andrea L Aerts, et al.
The Lancet. Oncology|October 31, 2024
Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practiceSpyridon Bakas, Philipp Vollmuth, Norbert Galldiks, et al.
The Lancet. Oncology|October 31, 2024
Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancementsJavier E Villanueva-Meyer, Spyridon Bakas, Pallavi Tiwari, et al.
The Lancet. Rheumatology|May 9, 2026
Prevalence and determinants of sacroiliac joint bone marrow oedema in the general population in Germany: a population-based cross-sectional studyKeno Bressem, Murat Torgutalp, Torsten Diekhoff, et al.
Pageof 33

Showing results (291-300 of 321) with videos related to

Sort By:
Pageof 33
Neuro-Oncology|August 30, 2024
Multimodal deep learning improves recurrence risk prediction in pediatric low-grade gliomasMaryamalsadat Mahootiha, Divyanshu Tak, Zezhong Ye, et al.
Medrxiv : the Preprint Server for Health Sciences|November 28, 2024
Leveraging Deep Learning of Chest Radiograph Images to Identify Individuals at High Risk for Chronic Obstructive Pulmonary DiseaseSaman Doroodgar Jorshery, Jay Chandra, Anika S Walia, et al.
Nature|March 19, 2026
Thymic health and immunotherapy outcomes in patients with cancerSimon Bernatz, Vasco Prudente, Suraj Pai, et al.
The Lancet. Digital Health|April 22, 2023
Screening for extranodal extension in HPV-associated oropharyngeal carcinoma: evaluation of a CT-based deep learning algorithm in patient data from a multicentre, randomised de-escalation trialBenjamin H Kann, Jirapat Likitlersuang, Dennis Bontempi, et al.
Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology|December 23, 2025
Automated Lymph Node and Extranodal Extension Assessment Improves Risk Stratification in Oropharyngeal CarcinomaZezhong Ye, Reza Mojahed-Yazdi, Anna Zapaishchykova, et al.
Nature Communications|November 9, 2023
Automated temporalis muscle quantification and growth charts for children through adulthoodAnna Zapaishchykova, Kevin X Liu, Anurag Saraf, et al.
Proceedings of the National Academy of Sciences of the United States of America|March 4, 2015
Horizontal gene transfer and gene dosage drives adaptation to wood colonization in a tree pathogenBraham Dhillon, Nicolas Feau, Andrea L Aerts, et al.
The Lancet. Oncology|October 31, 2024
Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 2: recommendations for standardisation, validation, and good clinical practiceSpyridon Bakas, Philipp Vollmuth, Norbert Galldiks, et al.
The Lancet. Oncology|October 31, 2024
Artificial Intelligence for Response Assessment in Neuro Oncology (AI-RANO), part 1: review of current advancementsJavier E Villanueva-Meyer, Spyridon Bakas, Pallavi Tiwari, et al.
The Lancet. Rheumatology|May 9, 2026
Prevalence and determinants of sacroiliac joint bone marrow oedema in the general population in Germany: a population-based cross-sectional studyKeno Bressem, Murat Torgutalp, Torsten Diekhoff, et al.
Pageof 33