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Large scale data mining using genetics-based machine learning
2012
Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference companion - GECCO Companion '12
Preserved Fulltext
within NVIDIA s Graphic Processor Units
• CUDA runs thousands of threads at the same time à
Single Program, Multiple Data paradigm
• In the last few years GPUs have been extensively used in
the ...
If we
have the parallel hardware, this is a trivial way of gaining
efficiency
-32 million pairs of amino-acids (instances in the training set) with less than 2% of real contacts -Each instance is ...
doi:10.1145/2330784.2330936
dblp:conf/gecco/BacarditL12
fatcat:7qpgc572efg5zk3zkz4px3pky4
Large scale data mining using genetics-based machine learning
2013
Proceeding of the fifteenth annual conference companion on Genetic and evolutionary computation conference companion - GECCO '13 Companion
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
within NVIDIA s Graphic Processor Units
• CUDA runs thousands of threads at the same time à
Single Program, Multiple Data paradigm
• In the last few years GPUs have been extensively used in
the ...
If we
have the parallel hardware, this is a trivial way of gaining
efficiency
-32 million pairs of amino-acids (instances in the training set) with less than 2% of real contacts -Each instance is ...
doi:10.1145/2464576.2480807
dblp:conf/gecco/BacarditL13
fatcat:g7weaaxqsrdytcnalrucleoz4u
Large scale data mining using genetics-based machine learning
2009
Proceedings of the 11th annual conference companion on Genetic and evolutionary computation conference - GECCO '09
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
within NVIDIA s Graphic Processor Units
• CUDA runs thousands of threads at the same time à
Single Program, Multiple Data paradigm
• In the last few years GPUs have been extensively used in
the ...
If we
have the parallel hardware, this is a trivial way of gaining
efficiency
-32 million pairs of amino-acids (instances in the training set) with less than 2% of real contacts -Each instance is ...
doi:10.1145/1570256.1570424
dblp:conf/gecco/BacarditL09
fatcat:gnpp6egslzf7fjnyxkt2naqwam
Large scale data mining using genetics-based machine learning
2011
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation - GECCO '11
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
within NVIDIA s Graphic Processor Units
• CUDA runs thousands of threads at the same time à
Single Program, Multiple Data paradigm
• In the last few years GPUs have been extensively used in
the ...
If we
have the parallel hardware, this is a trivial way of gaining
efficiency
-32 million pairs of amino-acids (instances in the training set) with less than 2% of real contacts -Each instance is ...
doi:10.1145/2001858.2002137
dblp:conf/gecco/BacarditL11
fatcat:bgbkp6youfauxnc7jetrpjwj4q
Application and Exploration of Big Data Mining in Clinical Medicine
2016
Chinese Medical Journal
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Zhang et al. proposed a new system that analyzed the medical data stream and made predictions in real-time. ...
important insights for the early diagnosis of breast cancer. ...
doi:10.4103/0366-6999.178019
pmid:26960378
pmcid:PMC4804421
fatcat:5esbnukxvzdo3fajojwz4s2ry4
Application of AI and IoT in Clinical Medicine: Summary and Challenges
2021
Current Medical Science
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recognition, behavior recognition, anomaly detection, assistant decision-making system, to describe the scenario-based applications of remote diagnosis and treatment collaboration, neonatal intensive ...
In addition, the in-depth integration of AI and IoT technology enables the gradual improvement of medical diagnosis and treatment capabilities so as to provide services to the public in a more effective ...
An ANN is a parallel nonlinear dynamic system model, which is a mathematical model for information processing similar to the structure of synaptic connections in the brain. ...
doi:10.1007/s11596-021-2486-z
pmid:34939144
pmcid:PMC8693843
fatcat:3g3qpksktjhv5koqs3i7ylco7y
Deep learning for healthcare applications based on physiological signals: A review
2018
Computer Methods and Programs in Biomedicine
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Conclusions: This review paper depicts the application of various deep learning algorithms used till recently, but in future it will be used for more healthcare areas to improve the quality of diagnosis ...
and Objective: We have cast the net into the ocean of knowledge to retrieve the latest scientific research on deep learning methods for physiological signals. ...
Acknowledgements Funding: No external funding sources supported this review. ...
doi:10.1016/j.cmpb.2018.04.005
pmid:29852952
fatcat:3tn4ookjyjgafgnbb2tyzznhz4
Current Applications and Future Impact of Machine Learning in Radiology
2018
Radiology
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Machine learning has the potential to improve different steps of the radiology workflow including order scheduling and triage, clinical decision support systems, detection and interpretation of findings ...
In this article, the authors review examples of current applications of machine learning and artificial intelligence techniques in diagnostic radiology. ...
Convergence of Computing Power and Data Major advances in processing units based on massive concurrent parallel processing chip architectures for graphics radiology.rsna.org n Radiology: Volume 288: Number ...
doi:10.1148/radiol.2018171820
pmid:29944078
pmcid:PMC6542626
fatcat:vrf37sksivfkph47qdicwzeqge
An accelerated framework for the classification of biological targets from solid-state micropore data
2016
Computer Methods and Programs in Biomedicine
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The parallel implementation of the algorithm on graphics processing unit (GPU) demonstrates a speedup of three to four folds as compared to a serial implementation on an Intel Core i7 processor. ...
, such as cancerous/noncancerous cells based on the training data. ...
Originally aimed for gaming, graphics processing units (GPUs) have evolved as accelerators into a gamut of compute-intensive scientific applications including bioinformatics and biomedical signal processing ...
doi:10.1016/j.cmpb.2016.06.001
pmid:27480732
fatcat:3skfpew2ibgffmpjn6xxblunoy
Towards the Interpretability of Machine Learning Predictions for Medical Applications Targeting Personalised Therapies: A Cancer Case Survey
2021
International Journal of Molecular Sciences
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In addition, convolutional neural networks (CNNs), supported by the rapid development of graphic processing units (GPUs) and high-performance computing (HPC) infrastructures, are gaining importance when ...
However, the interpretability of machine learning predictions so that doctors can understand them, trust them and gain useful insights for the clinical practice is still rarely considered, which is a factor ...
In parallel, new frameworks (e.g., TensorFlow, PyTorch) have been developed to exploit all the computing power of graphical processing units (GPUs) and accelerate image analysis. ...
doi:10.3390/ijms22094394
pmid:33922356
fatcat:z3mxbx7fajge7pkyrp2odlauz4
EGFR Microdeletion Mutations Analysis System Model Using Parameters Combinations Generator for Design of RADBAS Neural Network Knowledge Based Identifier
2018
International Journal of Computational Intelligence Systems
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20th; and the second mode is intended for application in real time using sample patients' data with microdeletion mutations extracted online from EGFR mutation database. ...
We propose computing system/model based on two modules: The first module includes training of knowledge based radial basis (RADBAS) neural network using training set generated with combinatorial microdeletion ...
Acknowledgments We thank BiH Federal Ministry of Education and Science for the financial support in 2012/2013 for the research project "Computer Aided Lung Cancer Classification of Mutated EGFR Exons Using ...
doi:10.2991/ijcis.11.1.93
fatcat:xiri3p3myraxng5n7bgzvaa4dm
Implementation and Use of Disease Diagnosis Systems for Electronic Medical Records Based on Machine Learning: A Complete Review
2020
IEEE Access
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A fully automated diagnosis system of prostate cancer can be built in future. ...
MANB has been outperformed others based on these performance metrics with training time 16s and 0.72 of AUC to predict LOAD patients.
3) Decision Tree Methods A decision tree is one of the commonly used ...
doi:10.1109/access.2020.3016782
fatcat:j76bwlyrj5dv5mhhsvs4apynje
Artificial intelligence (AI) to enhance breast cancer screening: protocol for population-based cohort study of cancer detection
2022
BMJ Open
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We aim to address these limitations by comparing the accuracy of AI and radiologists in a cohort of consecutive of women attending a real-world population breast cancer screening programme.Methods and ...
AI accuracy will be compared with that of radiologist single-reading based on the difference in the area under the receiver operating characteristic curve. ...
A laptop with the AI algorithm installed and a graphics processing unit supporting its evaluation will be located at BSWA. ...
doi:10.1136/bmjopen-2021-054005
pmid:34980622
pmcid:PMC8724814
fatcat:6cjaxdylxjbsfmvf3drnr5gumy
NOVEL TRENDS OF ARTIFICIAL INTELLIGENCE
2018
Zenodo
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Hence, a need for introducing AI techniques arises in order to develop both diagnosis and intervention processes. ...
(for recognition of special types of disease patterns), patient monitoring, as control units for prosthetic devices, automatic diagnostic systems and the dynamic solution of complex allocation and routine ...
AI used in biomedical applications diagnosis of various diseases like lung cancer, also used in the diagnosis of acute leukemia and pancreatic cancer. ...
doi:10.5281/zenodo.2530516
fatcat:ebk4pq2czfhzbotmabe2x4ruwe
Regional implementation of a national cancer policy: taking forward multiprofessional, collaborative cancer care
1998
European Journal of Cancer Care
Preserved Fulltext
The Internet Archive has digitized a microfilm copy of this work. It may be possible to borrow a copy for reading.
INTRODUCTION services for common and rare cancers. ...
This paper outlines the process adopted in one region towards implementing the vision of Calman-Hine. ...
doi:10.1046/j.1365-2354.1998.00077.x
pmid:9793007
fatcat:zsa2emenu5fqne25i6w4r4tugq
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