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Primeur weekly 2017-02-13

Focus

Funding agencies and academia need to rethink reward structure for computational tool developers to tackle big scientific challenges ...

OpenAire to support more technical e-Infrastructures with Open Research Data guidelines, publication and training ...

Exascale supercomputing

ISC High Performance keynote forecasts future role of HPC in weather and climage prediction ...

Crowd computing

Towards equal access to digital coins ...

Quantum computing

Large groups of photons on demand - an equivalent of photonic 'integrated circuit' ...

Protecting quantum computing networks against hacking threats ...

Sorting machine for atoms ...

Focus on Europe

HPC-Europa3 provides access to European HPC systems ...

Peter the Great Saint Petersburg Polytechnic University is first university to introduce computational computer code for Airbus ...

Middleware

Introducing Hazelcast Jet: a new lightweight, distributed data processing engine ...

Bright Computing announces strategic alliance with Curtiss-Wright ...

Hardware

NVIDIA powers new class of supercomputing workstations with breakthrough capabilities for design and engineering ...

Van Andel research institute optimises HPC pipeline to drive research discoveries and new drug therapies with end-to-end DDN solution ...

CoolIT Systems issued U.S. patent for modular heat-transfer solutions ...

ORNL researchers break data transfer efficiency record ...

Cray reports 2016 full year and fourth quarter financial results ...

Supermicro deploys 30,000+ MicroBlade servers to enable one of the world's highest Efficiency (1.06 PUE) data centres ...

Mellanox ships more than 100,000 cables for next generation 100 Gb/s networks ...

UMass Amherst boosts deep learning research with powerful new GPU cluster ...

Oak Ridge National Laboratory enhances data integrity and accessibility with Active Archive Solutions ...

Applications

ANSYS spurs pervasive engineering simulation with release 18 ...

Computing sciences students: Get your team together for the SC17 Student Cluster Competition in Denver ...

Latest Allinea update advances code optimization across platforms ...

Con Edison selects C3 IoT for Big Data and predictive analytics platform and applications ...

New algorithms may revolutionize drug discoveries - and our understanding of life ...

When data's deep, dark places need to be illuminated ...

Computer trained to predict which AML patients will go into remission and which will relapse ...

The Cloud

Cycle Computing collaborates with ANSYS on its Enterprise Cloud HPC offering ...

IBM launches "Digital - Nation Africa" and invests $70 million to bring digital skills to Africa with free, Watson-powered skills platform for 25 million people ...

Computer trained to predict which AML patients will go into remission and which will relapse

Murat Dundar, PhD is an associate professor of computer science in the School of Science at Indiana University-Purdue University Indianapolis. He is an internationally respected machine-learning scientist who specializes in teaching computers to understand biomedical data. Credit: School of Science at Indiana University-Purdue University Indianapolis.9 Feb 2017 Indianapolis - Researchers have developed the first computer machine-learning model to accurately predict which patients diagnosed with acute myelogenous leukemia, or AML, will go into remission following treatment for their disease and which will relapse.

"It's pretty straightforward to teach a computer to recognize AML, once you develop a robust algorithm, and in previous work we did it with almost 100 percent accuracy", stated Murat Dundar, senior author of the disease-progression study and associate professor of computer science in the School of Science at Indiana University-Purdue University Indianapolis. "What was challenging was to go beyond that work and teach the computer to accurately predict the direction of change in disease progression in AML patients, interpreting new data to predict the unknown: which new AML patients will go into remission and which will relapse."

The computer was trained using bone marrow data and medical histories of AML patients, as well as blood data from healthy individuals. Cases about which the computer had no information were evaluated by the algorithm by applying knowledge about similar cases in the database. The computer was then able to predict remission with 100 percent accuracy. Relapse was correctly predicted in 90 percent of relevant cases.

"As the input, our computational system employs data from flow cytometry, a widely utilized technology that can rapidly provide detailed characteristics of single cells in samples such as blood or bone marrow", explained Bartek Rajwa, first author of the study and research assistant professor of computational biology in the Bindley Bioscience Center at Purdue University. "Traditionally, the results of flow cytometry analyses are evaluated by highly trained human experts rather than by machine-learning algorithms. But computers are often better at extracting knowledge from complex data than humans are."

Automated measurement and monitoring of response to treatment of AML are critical not only for objective evaluation of disease-status prognosis but also for timely assessment of treatment strategies, the study's authors noted. Their work creates and underlies a clinical decision support system that recognizes the presence of minute residual amounts of malignant cells of any AML type in bone marrow samples, enabling early identification of change in direction of disease progression.

"Machine learning is not about modelling data. It's about extracting knowledge from the data you have so you can build a powerful, intuitive tool that can make predictions about future data that the computer has not previously seen - the machine is learning, not memorizing - and that's what we did", stated Murat Dundar, an internationally respected machine-learning scientist who specializes in teaching computers to understand biomedical data.

The National Cancer Institute anticipated that 19,950 individuals would be diagnosed with AML in 2016 and forecast that approximately 10,430 deaths from AML would occur last year.

The study was a collaboration of IUPUI's Murat Dundar and Purdue's Bartek Rajwa with Roswell Park Cancer Institute's Paul K. Wallace, a flow cytometry expert, and Elizabeth A. Griffiths, a physician who treats patients with AML.

This research, which has potential application to other hematological neoplasms in addition to AML, was supported by National Science Foundation grant IIS-1252648 (CAREER), by National Institute of Biomedical Imaging and Bioengineering grant 5R21EB015707 and in part by National Cancer Institute grant 5P30 CA01605.

The paper titled "Automated Assessment of Disease Progression in Acute Myeloid Leukemia by Probabilistic Analysis of Flow Cytometry Data" is published online ahead of print inIEEE Transactions on Biomedical Engineering.

Source: Indiana University-Purdue University Indianapolis School of Science

Back to Table of contents

Primeur weekly 2017-02-13

Focus

Funding agencies and academia need to rethink reward structure for computational tool developers to tackle big scientific challenges ...

OpenAire to support more technical e-Infrastructures with Open Research Data guidelines, publication and training ...

Exascale supercomputing

ISC High Performance keynote forecasts future role of HPC in weather and climage prediction ...

Crowd computing

Towards equal access to digital coins ...

Quantum computing

Large groups of photons on demand - an equivalent of photonic 'integrated circuit' ...

Protecting quantum computing networks against hacking threats ...

Sorting machine for atoms ...

Focus on Europe

HPC-Europa3 provides access to European HPC systems ...

Peter the Great Saint Petersburg Polytechnic University is first university to introduce computational computer code for Airbus ...

Middleware

Introducing Hazelcast Jet: a new lightweight, distributed data processing engine ...

Bright Computing announces strategic alliance with Curtiss-Wright ...

Hardware

NVIDIA powers new class of supercomputing workstations with breakthrough capabilities for design and engineering ...

Van Andel research institute optimises HPC pipeline to drive research discoveries and new drug therapies with end-to-end DDN solution ...

CoolIT Systems issued U.S. patent for modular heat-transfer solutions ...

ORNL researchers break data transfer efficiency record ...

Cray reports 2016 full year and fourth quarter financial results ...

Supermicro deploys 30,000+ MicroBlade servers to enable one of the world's highest Efficiency (1.06 PUE) data centres ...

Mellanox ships more than 100,000 cables for next generation 100 Gb/s networks ...

UMass Amherst boosts deep learning research with powerful new GPU cluster ...

Oak Ridge National Laboratory enhances data integrity and accessibility with Active Archive Solutions ...

Applications

ANSYS spurs pervasive engineering simulation with release 18 ...

Computing sciences students: Get your team together for the SC17 Student Cluster Competition in Denver ...

Latest Allinea update advances code optimization across platforms ...

Con Edison selects C3 IoT for Big Data and predictive analytics platform and applications ...

New algorithms may revolutionize drug discoveries - and our understanding of life ...

When data's deep, dark places need to be illuminated ...

Computer trained to predict which AML patients will go into remission and which will relapse ...

The Cloud

Cycle Computing collaborates with ANSYS on its Enterprise Cloud HPC offering ...

IBM launches "Digital - Nation Africa" and invests $70 million to bring digital skills to Africa with free, Watson-powered skills platform for 25 million people ...