Home »
Academic Articles & Research Papers
Showing 20 of 85 academic articles
Adi Laurentiu Tarca, Vincent J. Carey, Xuewen Chen, Roberto J. Romero et al. • PLoS Computational Biology
(2007)
The term machine learning refers to a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. Two facets of mechan...
OPENALEX
public-domain
DOI: https://doi.org/10.1371/journal.pcbi.0030116
PMC: 1904382
Joshua I. Glaser, Ari S. Benjamin, Raeed H. Chowdhury, Matthew G. Perich et al. • eNeuro
(2020)
Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern machine learning tools, which are versatile and easy to use, have the potential to significantly improve deco...
OPENALEX
cc-by
DOI: https://doi.org/10.1523/eneuro.0506-19.2020
PMC: 7470933
Noémie Letellier, Caitlin G. Jones-Ngo, Michael W. Cheung, Rosana Aguilera et al. • Environment International
(2025)
Background: As the health burden attributable to wildfire activity increases under climate change, it is crucial to determine which subgroups face heightened vulnerability to wildfire smoke. Marginalized communities may experience dispropor...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.envint.2025.109955
Zhixin Lu, Brian R. Hunt, Edward Ott • Chaos An Interdisciplinary Journal of Nonlinear Science
(2018)
A machine-learning approach called "reservoir computing" has been used successfully for short-term prediction and attractor reconstruction of chaotic dynamical systems from time series data. We present a theoretical framework that describes...
OPENALEX
Open Access
DOI: https://doi.org/10.1063/1.5039508
Fanny Monori, Alin Tisan • Sensors
(2026)
Odour recognition with low-cost gas sensors is challenging in open-air settings due to the non-specificity of the sensors and environmental variability. This can be mitigated by incorporating additional information into the classification p...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s26082493
Nathan A. Brooks, Ankur Puri, Sanya Garg, Swapnika Nag et al. • Scientific Reports
(2021)
Abstract Population-level data have suggested that bacille Calmette-Guerin (BCG) vaccination may lessen the severity of Coronavirus Disease-19 (COVID-19) prompting clinical trials in this area. Some reports have demonstrated conflicting res...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-020-80787-z
Alexandre Abraham, Fabián Pedregosa, Michael Eickenberg, Philippe Gervais et al. • Frontiers in Neuroinformatics
(2014)
Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series....
OPENALEX
cc-by
DOI: https://doi.org/10.3389/fninf.2014.00014
PMC: 3930868
David Barber • Cambridge University Press eBooks
(2012)
Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot ...
OPENALEX
DOI: https://doi.org/10.1017/cbo9780511804779
John B. O. Mitchell • Wiley Interdisciplinary Reviews Computational Molecular Science
(2014)
Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics ...
OPENALEX
cc-by
DOI: https://doi.org/10.1002/wcms.1183
PMC: 4180928
Harry Surden • Colorado Law Scholarly Commons (University of Colorado Colorado Springs)
(2014)
This Article explores the application of machine learning techniques within the practice of law. Broadly speaking “machine learning” refers to computer algorithms that have the ability to “learn” or improve in performance over time on some ...
OPENALEX
Open Access
Marc Claesen, Bart De Moor • arXiv (Cornell University)
(2015)
We introduce the hyperparameter search problem in the field of machine learning and discuss its main challenges from an optimization perspective. Machine learning methods attempt to build models that capture some element of interest based o...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.1502.02127
Brad Boehmke, Brandon Greenwell • Chapman & Hall/CRC eBooks
(2019)
Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today’s most popular machine learning methods. This book serves as a practitioner’s guide to the machine learning process a...
OPENALEX
DOI: https://doi.org/10.1201/9780367816377
G. Baaklini, G. Baaklini, R. El Hourany, M. Fakhri et al. • Ocean Science
(2022)
The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping t...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/os-18-1491-2022
Bradley James Erickson, Panagiotis D. Korfiatis, Zeynettin Akkus, Timothy Lee Kline • Radiographics
(2017)
Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the ma...
OPENALEX
Open Access
DOI: https://doi.org/10.1148/rg.2017160130
PMC: 5375621
Yalın Baştanlar, Mustafa Özuysal • Methods in molecular biology
(2013)
The machine learning field, which can be briefly defined as enabling computers make successful predictions using past experiences, has exhibited an impressive development recently with the help of the rapid increase in the storage capacity ...
OPENALEX
Open Access
DOI: https://doi.org/10.1007/978-1-62703-748-8_7
Pedro Larrañaga, Borja Calvo, Roberto Santana, Concha Bielza et al. • Briefings in Bioinformatics
(2006)
This article reviews machine learning methods for bioinformatics. It presents modelling methods, such as supervised classification, clustering and probabilistic graphical models for knowledge discovery, as well as deterministic and stochast...
OPENALEX
Open Access
DOI: https://doi.org/10.1093/bib/bbk007
• Series in machine perception and artificial intelligence
(2019)
The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict ...
OPENALEX
DOI: https://doi.org/10.1142/9789811201967_0001
Ł. Wilk, Ł. Wilk, D. Mielczarek, W. Ostrowski et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
(2022)
The use of deep machine learning methods for semantic classification of city mesh models is one of the current trends in geoscience development. Thanks to the thriving development of Convolutional Neural Networks (CNNs) it is now achievable...
DOAJ
Open Access (DOAJ)
DOI: 10.5194/isprs-archives-XLIII-B2-2022-485-2022
Sarkar Siddique, James C. L. Chow • Reports of Practical Oncology & Radiotherapy
(2020)
Artificial intelligence (AI) has already been implemented widely in the medical field in the recent years. This paper first reviews the background of AI and radiotherapy. Then it explores the basic concepts of different AI algorithms and ma...
OPENALEX
cc-by-nc-nd
DOI: https://doi.org/10.1016/j.rpor.2020.03.015
PMC: 7321818
Nina Schwalbe, Brian Wahl • The Lancet
(2020)
Concurrent advances in information technology infrastructure and mobile computing power in many low and middle-income countries (LMICs) have raised hopes that artificial intelligence (AI) might help to address challenges unique to the field...
OPENALEX
other-oa
DOI: https://doi.org/10.1016/s0140-6736(20)30226-9
PMC: 7255280