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Machine learning applications in epilepsy

Bardia Abbasi, Daniel M. Goldenholz • Epilepsia (2019)

Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recogn...

OPENALEX Open Access DOI: https://doi.org/10.1111/epi.16333 PMC: 9897263

Understanding Machine Learning

Shai Shalev‐Shwartz, Shai Ben-David • Cambridge University Press eBooks (2014)

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book prov...

OPENALEX DOI: https://doi.org/10.1017/cbo9781107298019

Bayesian Reasoning and Machine Learning

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

Machine learning methods in chemoinformatics

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

Machine learning for precision medicine

Sarah J. MacEachern, Nils D. Forkert • Genome (2020)

Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multi-modal or multi-omics data from an individual to make patient-tailored decisions. With t...

OPENALEX Open Access DOI: https://doi.org/10.1139/gen-2020-0131

A flexible analytic wavelet transform and ensemble bagged tree model for electroencephalogram-based meditative mind-wandering detection

Ajay Dadhich, Jaideep Patel, Rovin Tiwari, Richa Verma et al. • Healthcare Analytics (2024)

Mind-wandering (MW) is when an individual’s concentration drifts away from the task or activity. Researchers found a greater variability in electroencephalogram (EEG) signals due to MW. Collecting more nuanced information from raw EEG data ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.health.2023.100286

Machine Learning for Sociology

Mario D. Molina, Filiz Garip • Annual Review of Sociology (2019)

Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and soci...

OPENALEX Open Access DOI: https://doi.org/10.1146/annurev-soc-073117-041106

Improved railway track faults detection using Mel-frequency cepstral coefficient and constant-Q transform features

Rahman Shafique, Khadija Kanwal, Venkata Chunduri, Gyu Sang Choi et al. • Scientific Reports (2025)

Abstract Regular inspection of the health of railway tracks is crucial to maintaining reliable and safe train operations. Some factors including cracks, rail discontinuity, ballast issues, burn wheels, super-elevation, loose nuts and bolts,...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-14763-w

PCPAm - A dataset of histopathological images of penile cancer for classification tasksZenodo

Marcos Gabriel Mendes Lauande, Geraldo Braz Júnior, João Dallyson Sousa de Almeida, Vandecia Rejane Monteiro Fernandes et al. • Data in Brief (2025)

Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underdeveloped countries like Brazil, where it represents approximately 2% of cancers affecting men. This dataset was created to address the scarc...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2025.111823

Predicting Urban Quality of Life Using Machine Learning on Street Images and Personal Information with Statistical Feature Selection: A Comparative Study of Bangkok and London

Ployrada Suvarnakuta, Intouch Prakaisak, Pittipol Kantavat, Boonserm Kijsirikul et al. • Engineered Science (2025)

This study proposes a machine learning framework for predicting perceived urban quality of life (QoL) by integrating visual features from street-level imagery with personal attributes, including demographic, socioeconomic, and travel behavi...

DOAJ Open Access (DOAJ) DOI: 10.30919/es1972

Surface circulation properties in the eastern Mediterranean emphasized using machine learning methods

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

Context Aware Evapotranspiration (ETs) for Saline Soils Reclamation

Arfat Ahmad Khan, Muhammad Asif Nauman, Rab Nawaz Bashir, Rashid Jahangir et al. • IEEE Access (2022)

Accurate Evapotranspiration for saline soils (ETs) is important as well as challenging for the reclamation of saline soils through an effective leaching process. Evapotranspiration (ET) by FAO-56 Penman-Monteith standard method is complex, ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2022.3206009

Machine Learning

Stephen Marsland • Chapman & Hall/CRC eBooks (2014)

A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing wo...

OPENALEX DOI: https://doi.org/10.1201/b17476

Optimization for Machine Learning

S. Sra, S. Nowozin, Stephen J. Wright • The MIT Press eBooks (2011)

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments ...

OPENALEX DOI: https://doi.org/10.7551/mitpress/8996.001.0001

Exploring the Impact of Alternatives of Object-Oriented Cohesion Measures on Machine Learning-Based Predictions of Inheritance Reusability

Jehad Al Dallal, Bader Alkhazi • IEEE Access (2024)

The cohesion of an object-oriented class refers to the relatedness of its methods and attributes. Constructors, destructors, and access methods are special types of methods featuring unique characteristics that can artificially affect class...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3484007