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Alexander S Baras

Showing results (1-10 of 62) with videos related to

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Scientific Reports|July 13, 2021
Deep learning identifies antigenic determinants of severe SARS-CoV-2 infection within T-cell repertoiresJohn-William Sidhom, Alexander S Baras
Cancer Research Communications|June 17, 2024
Characterization of Non-Monotonic Relationships between Tumor Mutational Burden and Clinical OutcomesJordan Anaya, Julia Kung, Alexander S Baras
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|October 25, 2024
Evaluation of a Task-Specific Self-Supervised Learning Framework in Digital Pathology Relative to Transfer Learning Approaches and Existing Foundation ModelsTawsifur Rahman, Alexander S Baras, Rama Chellappa
BMC Bioinformatics|August 30, 2018
miRge 2.0 for comprehensive analysis of microRNA sequencing dataYin Lu, Alexander S Baras, Marc K Halushka
International Journal of Gynecological Pathology : Official Journal of the International Society of Gynecological Pathologists|February 4, 2014
Ki-67 index as an ancillary tool in the differential diagnosis of proliferative endometrial lesions with secretory changeGrzegorz T Gurda, Alexander S Baras, Robert J Kurman
Laboratory Investigation; a Journal of Technical Methods and Pathology|April 27, 2011
Loss of VOPP1 overexpression in squamous carcinoma cells induces apoptosis through oxidative cellular injuryAlexander S Baras, Alex Solomon, Robert Davidson, et al.
Nature Biomedical Engineering|November 3, 2023
Multiple-instance learning of somatic mutations for the classification of tumour type and the prediction of microsatellite statusJordan Anaya, John-William Sidhom, Faisal Mahmood, et al.
BJU International|February 16, 2026
Digital pathology-based artificial intelligence algorithms in prostate cancer: inside the 'black box'Claire M de la Calle, Alexander S Baras, Tamara L Lotan
Cancer Research|February 18, 2010
The COXEN principle: translating signatures of in vitro chemosensitivity into tools for clinical outcome prediction and drug discovery in cancerSteven C Smith, Alexander S Baras, Jae K Lee, et al.
Cancer Research Communications|March 31, 2023
Probabilistic Mixture Models Improve Calibration of Panel-derived Tumor Mutational Burden in the Context of both Tumor-normal and Tumor-only SequencingJordan Anaya, John-William Sidhom, Craig A Cummings, et al.
Pageof 7

Showing results (1-10 of 62) with videos related to

Sort By:
Pageof 7
Scientific Reports|July 13, 2021
Deep learning identifies antigenic determinants of severe SARS-CoV-2 infection within T-cell repertoiresJohn-William Sidhom, Alexander S Baras
Cancer Research Communications|June 17, 2024
Characterization of Non-Monotonic Relationships between Tumor Mutational Burden and Clinical OutcomesJordan Anaya, Julia Kung, Alexander S Baras
Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc|October 25, 2024
Evaluation of a Task-Specific Self-Supervised Learning Framework in Digital Pathology Relative to Transfer Learning Approaches and Existing Foundation ModelsTawsifur Rahman, Alexander S Baras, Rama Chellappa
BMC Bioinformatics|August 30, 2018
miRge 2.0 for comprehensive analysis of microRNA sequencing dataYin Lu, Alexander S Baras, Marc K Halushka
International Journal of Gynecological Pathology : Official Journal of the International Society of Gynecological Pathologists|February 4, 2014
Ki-67 index as an ancillary tool in the differential diagnosis of proliferative endometrial lesions with secretory changeGrzegorz T Gurda, Alexander S Baras, Robert J Kurman
Laboratory Investigation; a Journal of Technical Methods and Pathology|April 27, 2011
Loss of VOPP1 overexpression in squamous carcinoma cells induces apoptosis through oxidative cellular injuryAlexander S Baras, Alex Solomon, Robert Davidson, et al.
Nature Biomedical Engineering|November 3, 2023
Multiple-instance learning of somatic mutations for the classification of tumour type and the prediction of microsatellite statusJordan Anaya, John-William Sidhom, Faisal Mahmood, et al.
BJU International|February 16, 2026
Digital pathology-based artificial intelligence algorithms in prostate cancer: inside the 'black box'Claire M de la Calle, Alexander S Baras, Tamara L Lotan
Cancer Research|February 18, 2010
The COXEN principle: translating signatures of in vitro chemosensitivity into tools for clinical outcome prediction and drug discovery in cancerSteven C Smith, Alexander S Baras, Jae K Lee, et al.
Cancer Research Communications|March 31, 2023
Probabilistic Mixture Models Improve Calibration of Panel-derived Tumor Mutational Burden in the Context of both Tumor-normal and Tumor-only SequencingJordan Anaya, John-William Sidhom, Craig A Cummings, et al.
Pageof 7