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author Patkar, Nikhil
Shaikh, Anam Fatima
Kakirde, Chinmayee
Nathany, Shrinidhi
Ramesh, Hridya
Bhanshe, Prasanna
Joshi, Swapnali
Chaudhary, Shruti
Kannan, Sadhana
Khizer, Syed Hasan
Chatterjee, Gaurav
Tembhare, Prashant
Shetty, Dhanalaxmi
Gokarn, Anant
Punatkar, Sachin
Bonda, Avinash
Nayak, Lingaraj
Jain, Hasmukh
Khattry, Navin
Bagal, Bhausaheb
Sengar, Manju
Gujral, Sumeet
Subramanian, Papagudi
author_facet Patkar, Nikhil
Shaikh, Anam Fatima
Kakirde, Chinmayee
Nathany, Shrinidhi
Ramesh, Hridya
Bhanshe, Prasanna
Joshi, Swapnali
Chaudhary, Shruti
Kannan, Sadhana
Khizer, Syed Hasan
Chatterjee, Gaurav
Tembhare, Prashant
Shetty, Dhanalaxmi
Gokarn, Anant
Punatkar, Sachin
Bonda, Avinash
Nayak, Lingaraj
Jain, Hasmukh
Khattry, Navin
Bagal, Bhausaheb
Sengar, Manju
Gujral, Sumeet
Subramanian, Papagudi
author_sort Patkar, Nikhil
collection PubMed
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spelling pubmed-67737772019-10-03 A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1 Patkar, Nikhil Shaikh, Anam Fatima Kakirde, Chinmayee Nathany, Shrinidhi Ramesh, Hridya Bhanshe, Prasanna Joshi, Swapnali Chaudhary, Shruti Kannan, Sadhana Khizer, Syed Hasan Chatterjee, Gaurav Tembhare, Prashant Shetty, Dhanalaxmi Gokarn, Anant Punatkar, Sachin Bonda, Avinash Nayak, Lingaraj Jain, Hasmukh Khattry, Navin Bagal, Bhausaheb Sengar, Manju Gujral, Sumeet Subramanian, Papagudi Blood Cancer J Correspondence Nature Publishing Group UK 2019-10-01 /pmc/articles/PMC6773777/ /pubmed/31575857 http://dx.doi.org/10.1038/s41408-019-0244-2 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Correspondence
Patkar, Nikhil
Shaikh, Anam Fatima
Kakirde, Chinmayee
Nathany, Shrinidhi
Ramesh, Hridya
Bhanshe, Prasanna
Joshi, Swapnali
Chaudhary, Shruti
Kannan, Sadhana
Khizer, Syed Hasan
Chatterjee, Gaurav
Tembhare, Prashant
Shetty, Dhanalaxmi
Gokarn, Anant
Punatkar, Sachin
Bonda, Avinash
Nayak, Lingaraj
Jain, Hasmukh
Khattry, Navin
Bagal, Bhausaheb
Sengar, Manju
Gujral, Sumeet
Subramanian, Papagudi
A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1
title A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1
title_full A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1
title_fullStr A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1
title_full_unstemmed A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1
title_short A novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated NPM1
title_sort novel machine-learning-derived genetic score correlates with measurable residual disease and is highly predictive of outcome in acute myeloid leukemia with mutated npm1
topic Correspondence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6773777/
https://www.ncbi.nlm.nih.gov/pubmed/31575857
http://dx.doi.org/10.1038/s41408-019-0244-2
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