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Leukemia & Lymphoma
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October 6, 2021
Artificial intelligence models in chronic lymphocytic leukemia - recommendations toward state-of-the-art
Rudi Agius, Mehdi Parviz, Carsten Utoft Niemann
Bioinformatics (Oxford, England)
|
September 10, 2011
Protein-protein binding affinity prediction on a diverse set of structures
Iain H Moal, Rudi Agius, Paul A Bates
Blood Advances
|
April 25, 2022
Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data
Mehdi Parviz, Christian Brieghel, Rudi Agius, et al.
Briefings in Functional Genomics
|
July 20, 2012
Understanding cancer mechanisms through network dynamics
Tammy M K Cheng, Sakshi Gulati, Rudi Agius, et al.
Hemasphere
|
April 16, 2026
Machine learning enhances risk stratification and treatment failure prediction in diffuse large B-cell lymphoma
Mikkel Werling, Alexander D Fuglkjær, Peter Brown, et al.
Plos Computational Biology
|
September 17, 2013
Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization
Rudi Agius, Mieczyslaw Torchala, Iain H Moal, et al.
Leukemia & Lymphoma
|
January 5, 2024
Identifying CLL patients at high risk of atrial fibrillation on treatment using machine learning
Mehdi Parviz, Rudi Agius, Emelie Curovic Rotbain, et al.
Proteins
|
August 1, 2013
A Markov-chain model description of binding funnels to enhance the ranking of docked solutions
Mieczyslaw Torchala, Iain H Moal, Raphael A G Chaleil, et al.
Acta Oncologica (Stockholm, Sweden)
|
February 19, 2026
Post-treatment infection prediction in CLL using domain adaptation of lymphoma electronic health records
Mehdi Parviz, Christian Brieghel, Mikkel Werling, et al.
Scientific Reports
|
August 16, 2022
Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning
Adrian G Zucco, Rudi Agius, Rebecka Svanberg, et al.
Page
of 2
Search research articles
Search
Showing results (1-10 of 17) with videos related to
Sort By:
Page
of 2
Leukemia & Lymphoma
|
October 6, 2021
Artificial intelligence models in chronic lymphocytic leukemia - recommendations toward state-of-the-art
Rudi Agius, Mehdi Parviz, Carsten Utoft Niemann
Bioinformatics (Oxford, England)
|
September 10, 2011
Protein-protein binding affinity prediction on a diverse set of structures
Iain H Moal, Rudi Agius, Paul A Bates
Blood Advances
|
April 25, 2022
Prediction of clinical outcome in CLL based on recurrent gene mutations, CLL-IPI variables, and (para)clinical data
Mehdi Parviz, Christian Brieghel, Rudi Agius, et al.
Briefings in Functional Genomics
|
July 20, 2012
Understanding cancer mechanisms through network dynamics
Tammy M K Cheng, Sakshi Gulati, Rudi Agius, et al.
Hemasphere
|
April 16, 2026
Machine learning enhances risk stratification and treatment failure prediction in diffuse large B-cell lymphoma
Mikkel Werling, Alexander D Fuglkjær, Peter Brown, et al.
Plos Computational Biology
|
September 17, 2013
Characterizing changes in the rate of protein-protein dissociation upon interface mutation using hotspot energy and organization
Rudi Agius, Mieczyslaw Torchala, Iain H Moal, et al.
Leukemia & Lymphoma
|
January 5, 2024
Identifying CLL patients at high risk of atrial fibrillation on treatment using machine learning
Mehdi Parviz, Rudi Agius, Emelie Curovic Rotbain, et al.
Proteins
|
August 1, 2013
A Markov-chain model description of binding funnels to enhance the ranking of docked solutions
Mieczyslaw Torchala, Iain H Moal, Raphael A G Chaleil, et al.
Acta Oncologica (Stockholm, Sweden)
|
February 19, 2026
Post-treatment infection prediction in CLL using domain adaptation of lymphoma electronic health records
Mehdi Parviz, Christian Brieghel, Mikkel Werling, et al.
Scientific Reports
|
August 16, 2022
Personalized survival probabilities for SARS-CoV-2 positive patients by explainable machine learning
Adrian G Zucco, Rudi Agius, Rebecka Svanberg, et al.
Page
of 2