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Journal Articles

Combining Gene Expression Profiling and Artificial Intelligence to Diagnose B-Cell Non-Hodgkin Lymphoma

Victor Bobée, PharmD, Fanny Drieux, MD, Vinciane Marchand, Vincent Sater, Liana Veresezan, MD, Jean-Michel Picquenot, MD, Pierre-Julien Viailly, Marie-delphine Lanic, Mathieu Viennot, Elodie Bohers, PhD, Lucie Oberic, MD, Christiane Copie-Bergman, MD PhD, Thierry Jo Molina, MD PhD, Philippe Gaulard, MD PhD, Corinne Haioun, MD PhD, Gilles A. Salles, MD PhD, Herve Tilly, MD PhD, Fabrice Jardin, Philippe Ruminy, PhD

Blood (2019) 134 (Supplement_1): 1476.

https://doi.org/10.1182/blood-2019-122405

Published: 2019

Journal Articles

Reinforcement Learning to Optimize the Treatment of Multiple Myeloma

Kenneth H. Shain, MD PhD, Daniel Hart, Ariosto Siqueira Silva, PhD, Raghunandanreddy Alugubelli, MS, Gabriel De Avila, BS, Praneeth Reddy Sudalagunta, PhD, Alexandre Tungesvik, MD, Amit Kulkarni, PhD, Carmelo Blancuicett, PhD MD, Hongyue Dai, PhD, Taiga Nishihori, MD, Jason B. Brayer, PhDMD, Brandon Blue, MD, Melissa Alsina, MD, Rachid Baz, MD, William S. Dalton, PhDMD

Blood (2019) 134 (Supplement_1): 5511.

https://doi.org/10.1182/blood-2019-132234

Published: 2019

Journal Articles

The Impact of Treatment Recommendation By Leukemia Artificial Intelligence Program (LEAP) on Survival in Patients with Chronic Myeloid Leukemia in Chronic Phase (CML-CP)

Blood (2019) 134 (Supplement_1): 1642.

https://doi.org/10.1182/blood-2019-130148

Published: 2019

Journal Articles

A Personalized Prediction Model to Risk Stratify Patients with Acute Myeloid Leukemia (AML) Using Artificial Intelligence

Blood (2019) 134 (Supplement_1): 2091.

https://doi.org/10.1182/blood-2019-128066

Published: 2019

Journal Articles

Knowledge Transfer between Artificial Neural Networks for Different Multicolor Flow Cytometry Protocols Improves Classification Performance for Rare B-Cell Neoplasm Subtypes

Nanditha Mallesh, Max Zhao, Franz Elsner, PhD, Hannes Lueling, PhD, Richard Schabath, PhD, Claudia Haferlach, MD, Torsten Haferlach, MD, Peter Krawitz, MD, Wolfgang Kern, MD

Blood (2019) 134 (Supplement_1): 2094.

https://doi.org/10.1182/blood-2019-130483

Published: 2019

Journal Articles

Predicting Response to Hypomethylating Agents in Patients with Myelodysplastic Syndromes (MDS) Using Artificial Intelligence (AI)

Nathan Radakovich, BA, Mikkael A. Sekeres, MD MS, Cameron Beau Hilton, BA, Sudipto Mukherjee, MD PhD MPH, Jacob Shreve, MD MS, Yazan Rouphail, Rachel Shirley, Vera Adema, PhD, Hassan Awada, MD, Anjali S. Advani, MD, Cassandra M Kerr, MS, Yasunobu Nagata, MD PhD, Yihong Guan, PhD, Teodora Kuzmanovic, BA, Metis Hasipek, PhD, Babal K. Jha, PhD, Jaroslaw P. Maciejewski, MD PhD, Aziz Nazha, MD

Blood (2019) 134 (Supplement_1): 2089.

https://doi.org/10.1182/blood-2019-126275

Published: 2019

Journal Articles

Voice of Cancer Patients: Patient Experience Regarding Use of Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia

Sangeeta Aggarwal, MD, Singh Manish, B.Tech, Guroosh Chaudhary, Alok Aggarwal, PhD, Himanshu Punetha, M. Tech, Juhi Jha, Rahul Kumar Gond

Blood (2019) 134 (Supplement_1): 5843.

https://doi.org/10.1182/blood-2019-125195

Published: 2019

Journal Articles

Diagnostic Predictive Model for Diagnosis of Heart Failure after Hematopoietic Cell Transplantation (HCT): Comparison of Traditional Statistical with Machine Learning Modeling

Benjamin Djulbegovic, MD, Jennifer Berano Teh, Lennie Wong, PhD, Iztok Hozo, PhD, Saro H. Armenian, DO, MPH

Blood (2019) 134 (Supplement_1): 5799.

https://doi.org/10.1182/blood-2019-130764

Published: 2019

Journal Articles

Artificial Intelligence Guided Precision Medicine Approach to Hematological Disease

Tomomi Takei, MD, Kazuaki Yokoyama, MD PhD, Nozomi Yusa, Sousuke Nakamura, MD, Miho Ogawa, MD, Kanya Kondoh, MD, Masayuki Kobayashi, MD, Asako Kobayashi, Mika Ito, Eigo Shimizu, Mako Yamamoto, Rika Kasajima, PhD, Koichiro Yuji, MD PhD, Rui Yamaguchi, PhD, Yoichi Furukawa, MD PhD, Seiya Imoto, PhD, Satoru Miyano, PhD, Arinobu Tojo, MD PhD

Blood (2018) 132 (Supplement 1): 2254.

https://doi.org/10.1182/blood-2018-99-117941

Published: 2018

Journal Articles

Relapse and Mortality Prediction of Acute Myeloid Leukemia Patients Using Deep Bidirectional Long Short-Term Memory-Deep Neural Network Architecture

Bor-Sheng Ko, MD PhD, Yu-Fen Wang, MS, Chih-Chuan Lu, B.S., Jeng-Lin Li, BS, Chi-Chun Lee, PhD, Jih-Luh Tang, MD, Hwei-Fang Tien, MD, PhD

Blood (2018) 132 (Supplement 1): 2811.

https://doi.org/10.1182/blood-2018-99-115778

Published: 2018

Journal Articles

An Artificial Intelligence (AI) Approach for Automated Flow Cytometric Diagnosis of B-Cell Lymphoma

Alexander Höllein, MD, Max Zhao, Richard Schabath, MD, Torsten Haferlach, MD, Claudia Haferlach, MD, Peter Krawitz, MD, Wolfgang Kern, MD

Blood (2018) 132 (Supplement 1): 2856.

https://doi.org/10.1182/blood-2018-99-113797

Published: 2018

Journal Articles

An Artificial Intelligence Approach for Predicting Allogeneic Hematopoietic Stem Cell Transplantation Outcome By Detecting Pre-Transplant Minimal Residual Disease in Acute Myeloid Leukemia Using Flow Cytometry Data

Chi-Cheng Li, MD, Bor-Sheng Ko, MD, PhD, Yu-Fen Wang, MS, Jeng-Lin Li, BS, Pei-Fang Weng, BS, Hsin-An Hou, MD, PhD, Xiu-Wen Liao, MS, Chien-Ting Lin, MD, Jia-Hou Liu, MD, Hsun-I Sun, Hwei-Fang Tien, MD, PhD, Chi-Chun Lee, PhD, Jih-Luh Tang, MD,PhD

Blood (2017) 130 (Supplement 1): 2042.

https://doi.org/10.1182/blood.V130.Suppl_1.2042.2042

Published: 2017

Journal Articles

Patient-Based Prediction Algorithm of Relapse after Allo-HSCT for Acute Leukemia Using Machine Learning Approach

Kyoko Fuse, MD, Shun Uemura, MD, Tatsuya Suwabe, MD, Takayuki Katagiri, MD, Tomoyuki Tanaka, MD, Takashi Ushiki, MD PhD, Yasuhiko Shibasaki, MD PhD, Naoko Sato, MD PhD, Toshio Yano, MD PhD, Takashi Kuroha, MD PhD, Shigeo Hashimoto, MD PhD, Tastuo Furukawa, MD PhD, Miwako Narita, MD PhD, Hirohito Sone, MD PhD, Masayoshi Masuko, MD PhD

Blood (2017) 130 (Supplement 1): 2044.

https://doi.org/10.1182/blood.V130.Suppl_1.2044.2044

Published: 2017

Journal Articles

An Artificial Intelligence Approach for B Lymphoblastic Leukemia Minimal Residual Disease Detection and Clinical Prognosis Prediction Using Flow Cytometry Data

Yu-Fen Wang, MS, Bor-Sheng Ko, MD, PhD, Chi-Cheng Li, MD, Jeng-Lin Li, BS, Pei-Fang Weng, BS, Huai-Hsuan Huang, MD, Hsin-An Hou, MD, PhD, Hwei-Fang Tien, MD, PhD, Chi-Chun Lee, PhD, Jih-Luh Tang, MD,PhD

Blood (2017) 130 (Supplement 1): 3980.

https://doi.org/10.1182/blood.V130.Suppl_1.3980.3980

Published: 2017

Journal Articles

Deep Learning Algorithms Depict New Subgroups of AML and MDS Based on Genetics Only and Allow Distinction of Both Entities with High Accuracy of 90%

Manja Meggendorfer, PhD, Wencke Walter, PhD, Claudia Haferlach, MD, Wolfgang Kern, MD, Torsten Haferlach, MD

Blood (2017) 130 (Supplement 1): 2957.

https://doi.org/10.1182/blood.V130.Suppl_1.2957.2957

Published: 2017

Journal Articles

Age Is Not a Predictive Marker in Molecularly Annotated Elderly Patients with Myelofibrosis Treated with Ruxolitinib: a Multicenter Study on 277 Patients.

Blood (2017) 130 (Supplement 1): 1642.

https://doi.org/10.1182/blood.V130.Suppl_1.1642.1642

Published: 2017

Journal Articles

An Artificial Intelligence Approach in Classifying Acute Myeloid Leukemia and Myelodysplastic Syndrome for Minimal Residual Disease Detection with Post Induction Prognosis Analysis Using Flow Cytometry

Bor-Sheng Ko, MD, PhD, Chi-Cheng Li, MD, Yu-Fen Wang, MS, Jeng-Lin Li, BS, Hsin-An Hou, MD, PhD, Pei-Fang Weng, BS, Hwei-Fang Tien, MD, PhD, Chi-Chun Lee, PhD, Jih-Luh Tang, MD,PhD

Blood (2017) 130 (Supplement 1): 1403.

https://doi.org/10.1182/blood.V130.Suppl_1.1403.1403

Published: 2017

Journal Articles

Clinical Application of Artificial Intelligence in Patients with Chronic Myeloid Leukemia in Chronic Phase

Koji Sasaki, MD, Hagop M. Kantarjian, MD, Elias J. Jabbour, MD, Susan O'Brien, MD, Farhad Ravandi, MD, Marina Konopleva, MDPhD, Gautam Borthakur, MD, William G. Wierda, MD PhD, Naval Daver, MD, Koichi Takahashi, MD, Preetesh Jain, MBBS,MDDM,PhD, Jeffrey Skinner, Mary Beth Rios, RN, Sherry Pierce, BSN, BA, Guillermo Garcia-Manero, MD, Jorge E. Cortes, MD

Blood (2016) 128 (22): 940.

https://doi.org/10.1182/blood.V128.22.940.940

Published: 2016

Journal Articles

Using Machine Intelligence Algorithms to Develop a Geno-Clinical Model to Predict Responses to Hypomethylating Agents in Myelodysplastic Syndromes

Aziz Nazha, MD, Mikkael A. Sekeres, MD MS, Rafael Bejar, MD PhD, John Barnard, PhD, Karam Al-Issa, MD, Bartlomiej P Przychodzen, MSc, Matt Kalaycio, MD, Michael J. Clemente, M.S., Cassandra M. Hirsch, BSc, Benjamin L Ebert, MD PhD, Jaroslaw P. Maciejewski

Blood (2016) 128 (22): 3193.

https://doi.org/10.1182/blood.V128.22.3193.3193

Published: 2016

Journal Articles

A Machine Learning Based Model to Predict Two-Year Leukemia Free Survival in Cord Blood Transplantation for Acute Leukemia - a Data Mining Study, on Behalf of Eurocord, Cord Blood Committee and the Acute Leukemia Working Party of the EBMT

Blood (2015) 126 (23): 3211.

https://doi.org/10.1182/blood.V126.23.3211.3211

Published: 2015

NARROW

Combining Gene Expression Profiling and Artificial Intelligence to Diagnose B-Cell Non-Hodgkin Lymphoma

Reinforcement Learning to Optimize the Treatment of Multiple Myeloma

The Impact of Treatment Recommendation By Leukemia Artificial Intelligence Program (LEAP) on Survival in Patients with Chronic Myeloid Leukemia in Chronic Phase (CML-CP)

A Personalized Prediction Model to Risk Stratify Patients with Acute Myeloid Leukemia (AML) Using Artificial Intelligence

Knowledge Transfer between Artificial Neural Networks for Different Multicolor Flow Cytometry Protocols Improves Classification Performance for Rare B-Cell Neoplasm Subtypes

Predicting Response to Hypomethylating Agents in Patients with Myelodysplastic Syndromes (MDS) Using Artificial Intelligence (AI)

Voice of Cancer Patients: Patient Experience Regarding Use of Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia

Diagnostic Predictive Model for Diagnosis of Heart Failure after Hematopoietic Cell Transplantation (HCT): Comparison of Traditional Statistical with Machine Learning Modeling

Artificial Intelligence Guided Precision Medicine Approach to Hematological Disease

Relapse and Mortality Prediction of Acute Myeloid Leukemia Patients Using Deep Bidirectional Long Short-Term Memory-Deep Neural Network Architecture

An Artificial Intelligence (AI) Approach for Automated Flow Cytometric Diagnosis of B-Cell Lymphoma

An Artificial Intelligence Approach for Predicting Allogeneic Hematopoietic Stem Cell Transplantation Outcome By Detecting Pre-Transplant Minimal Residual Disease in Acute Myeloid Leukemia Using Flow Cytometry Data

Patient-Based Prediction Algorithm of Relapse after Allo-HSCT for Acute Leukemia Using Machine Learning Approach

An Artificial Intelligence Approach for B Lymphoblastic Leukemia Minimal Residual Disease Detection and Clinical Prognosis Prediction Using Flow Cytometry Data

Deep Learning Algorithms Depict New Subgroups of AML and MDS Based on Genetics Only and Allow Distinction of Both Entities with High Accuracy of 90%

Age Is Not a Predictive Marker in Molecularly Annotated Elderly Patients with Myelofibrosis Treated with Ruxolitinib: a Multicenter Study on 277 Patients.

An Artificial Intelligence Approach in Classifying Acute Myeloid Leukemia and Myelodysplastic Syndrome for Minimal Residual Disease Detection with Post Induction Prognosis Analysis Using Flow Cytometry

Clinical Application of Artificial Intelligence in Patients with Chronic Myeloid Leukemia in Chronic Phase

Using Machine Intelligence Algorithms to Develop a Geno-Clinical Model to Predict Responses to Hypomethylating Agents in Myelodysplastic Syndromes

A Machine Learning Based Model to Predict Two-Year Leukemia Free Survival in Cord Blood Transplantation for Acute Leukemia - a Data Mining Study, on Behalf of Eurocord, Cord Blood Committee and the Acute Leukemia Working Party of the EBMT

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American Society of Hematology

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ASH Publications

American Society of Hematology

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