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Academic Articles & Research Papers
Showing 20 of 938 academic articles
Ioannis Kavakiotis, O. Tsave, Athanasios Salifoglou, Nicos Maglaveras et al. • Computational and Structural Biotechnology Journal
(2017)
The remarkable advances in biotechnology and health sciences have led to a significant production of data, such as high throughput genetic data and clinical information, generated from large Electronic Health Records (EHRs). To this end, ap...
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DOI: https://doi.org/10.1016/j.csbj.2016.12.005
PMC: 5257026
Qingyang Ling • Applied and Computational Engineering
(2023)
Machine learning is a field of study where the computer can learn for itself without a human explicitly hardcoding the knowledge for it. These algorithms make up the backbone of machine learning. This paper aims to study the field of machin...
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DOI: https://doi.org/10.54254/2755-2721/4/20230355
Guy S. Handelman, Hong Kuan Kok, Ronil Vikesh Chandra, Amir H. Razavi et al. • Journal of Internal Medicine
(2018)
Machine learning (ML) is a burgeoning field of medicine with huge resources being applied to fuse computer science and statistics to medical problems. Proponents of ML extol its ability to deal with large, complex and disparate data, often ...
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Open Access
DOI: https://doi.org/10.1111/joim.12822
Iason Batzianoulis, Fumiaki Iwane, Shupeng Wei, Carolina Gaspar Pinto Ramos Correia et al. • Communications Biology
(2021)
Teaching an assistive robotic manipulator to move objects in a cluttered table requires demonstrations from expert operators, but what if the experts are individuals with motor disabilities? Batzianoulis et al. propose a learning approach w...
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Open Access (DOAJ)
DOI: 10.1038/s42003-021-02891-8
Ral Garreta, Guillermo Moncecchi • International Linear Collider
(2013)
The book adopts a tutorial-based approach to introduce the user to Scikit-learn.If you are a programmer who wants to explore machine learning and data-based methods to build intelligent applications and enhance your programming skills, this...
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Simon Willcock, Javier Martínez‐López, Danny A. P. Hooftman, Kenneth J. Bagstad et al. • Ecosystem Services
(2018)
Recent developments in machine learning have expanded data-driven modelling (DDM) capabilities, allowing artificial intelligence to infer the behaviour of a system by computing and exploiting correlations between observed variables within i...
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DOI: https://doi.org/10.1016/j.ecoser.2018.04.004
Het Patel, Aditya Kansara, Boppuru Rudra Prathap, Kukatlapalli Pradeep Kumar • Measurement: Sensors
(2023)
The exponential rise in the use of social media has resulted in a massive increase in the volume of unstructured text created. This content is presented through messages, conversations, postings, and blogs. Microblogging has become a popula...
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Open Access (DOAJ)
DOI: 10.1016/j.measen.2023.100768
Marco Fiorucci, Marina Khoroshiltseva, Massimiliano Pontil, Arianna Traviglia et al. • Pattern Recognition Letters
(2020)
The application of Machine Learning (ML) to Cultural Heritage (CH) has evolved since basic statistical approaches such as Linear Regression to complex Deep Learning models. The question remains how much of this actively improves on the unde...
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DOI: https://doi.org/10.1016/j.patrec.2020.02.017
Sarah M. Alghamdi, Paul N. Schofield, Robert Hoehndorf • Disease Models & Mechanisms
(2022)
Computing phenotypic similarity helps identify new disease genes and diagnose rare diseases. Genotype–phenotype data from orthologous genes in model organisms can compensate for lack of human data and increase genome coverage. In the past d...
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Open Access (DOAJ)
DOI: 10.1242/dmm.049441
Jörn Lötsch, Alfred Ultsch • Pain
(2017)
1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...
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DOI: https://doi.org/10.1097/j.pain.0000000000001118
PMC: 5895117
James L. Melville, Edmund K. Burke, Jonathan D. Hirst • Combinatorial Chemistry & High Throughput Screening
(2009)
In this review, we highlight recent applications of machine learning to virtual screening, focusing on the use of supervised techniques to train statistical learning algorithms to prioritize databases of molecules as active against a partic...
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DOI: https://doi.org/10.2174/138620709788167980
Pariwat Ongsulee • International Conference on ICT and Knowledge Engineering
(2017)
It is increasingly recognized that artificial intelligence has been touted as a new mobile. Because of the high volume of data that being generated by devices, sensors and social media users, the machine can learn to distinguish the pattern...
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DOI: https://doi.org/10.1109/ictke.2017.8259629
Simon Rogers, Mark Girolami • Chapman & Hall/CRC eBooks
(2016)
"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations ...
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DOI: https://doi.org/10.1201/9781315382159
Dominic Dwyer, Peter Falkai, Nikolaos Koutsouleris • Annual Review of Clinical Psychology
(2018)
Machine learning approaches for clinical psychology and psychiatry explicitly focus on learning statistical functions from multidimensional data sets to make generalizable predictions about individuals. The goal of this review is to provide...
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DOI: https://doi.org/10.1146/annurev-clinpsy-032816-045037
Rodrigo D. Escobar, Alekya R. Angula, Mark Corsi • Ingenierías USBMed
(2012)
Compile-time optimization of code can result in significant performance gains. The amount of these gains varies widely depending upon the code being optimized, the hardware being compiled for, the specific performance increase attempted (e....
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Open Access (DOAJ)
Zetao Yan • Egyptian Informatics Journal
(2025)
Portfolio optimization is a process that involves distribution of capital with the purpose of maximizing returns and at the same time minimizing risks. The current paper discusses the use of Transformer networks in supervised learning for p...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.eij.2025.100839
Neusa R. Adão Martins, Neusa R. Adão Martins, Simon Annaheim, Christina M. Spengler et al. • Frontiers in Physiology
(2021)
The objective measurement of fatigue is of critical relevance in areas such as occupational health and safety as fatigue impairs cognitive and motor performance, thus reducing productivity and increasing the risk of injury. Wearable systems...
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Open Access (DOAJ)
DOI: 10.3389/fphys.2021.790292
Tan Yan Lin, Pang Ying Han, Ooi Shih Yin, Khoh Wee How et al. • Journal of Engineering Technology and Applied Physics
(2023)
In the telecom industry, predicting customer churn is crucial for improving customer retention. In literature, the use of single classifiers is predominantly focused. Customer data is complex data due to class imbalance and contain multiple...
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Open Access (DOAJ)
DOI: 10.33093/jetap.2023.5.2.12
(2007)
This volume contains the papers accepted to the 24th International Conference on Machine Learning (ICML 2007), which was held at Oregon State University in Corvalis, Oregon, from June 20th to 24th, 2007. ICML is the annual conference of the...
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DOI: https://doi.org/10.1145/1273496
Eleftheria Polychronidou, Ilias Kalamaras, Andreas Agathangelidis, Lesley-Ann Sutton et al. • BMC Bioinformatics
(2018)
Abstract Background Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D stru...
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Open Access (DOAJ)
DOI: 10.1186/s12859-018-2381-1