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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 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

Machine Learning and Law

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

Machine learning in automated text categorization

Fabrizio Sebastiani • ACM Computing Surveys (2002)

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing need to organize them...

OPENALEX Open Access DOI: https://doi.org/10.1145/505282.505283

Comparing Clinical Metadata Fusion Strategies for Diabetic and Hypertensive Retinopathy Classification

Vinicius de Carvalho Rispoli, Alan Müller, Weverson Garcia Medeiros, Marília Miranda Forte Gomes et al. • Machine Learning and Knowledge Extraction (2026)

Structured clinical variables may complement fundus photographs, but the most appropriate point at which to integrate them into a retinal foundation model remains uncertain. This study compares an image-only baseline with three strategies f...

DOAJ Open Access (DOAJ) DOI: 10.3390/make8100299

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

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

Design and Pilot Feasibility of a Low-Cost Wearable for Mexican Sign Language in Inclusive Higher Education

Juan Carlos Ramírez-Vázquez, Guadalupe Esmeralda Rivera-García, Marco Antonio Gómez-Guzmán, Marco Antonio Díaz-Martínez et al. • Technologies (2026)

A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype el...

DOAJ Open Access (DOAJ) DOI: 10.3390/technologies14030189

Multi-Resolution and Multi-Temporal Satellite Remote Sensing Analysis to Understand Human-Induced Changes in the Landscape for the Protection of Cultural Heritage: The Case Study of the MapDam Project, Syria

Nicodemo Abate, Diego Ronchi, Sara Elettra Zaia, Gabriele Ciccone et al. • Land (2025)

This study presents a multi-resolution and multi-temporal remote sensing approach to assess human-induced changes in cultural landscapes, with a focus on the archaeological site of Amrit (Syria) within the MapDam project. By integrating sat...

DOAJ Open Access (DOAJ) DOI: 10.3390/land14112233

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

Deep Learning for Automatic Vision-Based Recognition of Industrial Surface Defects: A Survey

Michela Prunella, Roberto Maria Scardigno, Domenico Buongiorno, Antonio Brunetti et al. • IEEE Access (2023)

Automatic vision-based inspection systems have played a key role in product quality assessment for decades through the segmentation, detection, and classification of defects. Historically, machine learning frameworks, based on hand-crafted ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3271748

Python Machine Learning

Sebastian Raschka (2015)

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This BookLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effect...

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Machine learning in bioinformatics

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

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

Introduction to Machine Learning

• 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

Machine Learning

Ethem Alpaydın • The MIT Press eBooks (2021)

A concise overview of machine learning—computer programs that learn from data—the basis of such applications as voice recognition and driverless cars. Today, machine learning underlies a range of applications we use every day, from product ...

OPENALEX Open Access DOI: https://doi.org/10.7551/mitpress/13811.001.0001

Machine Learning

Peter A. Flach • Cambridge University Press eBooks (2012)

As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511973000

Investigating the Role of Artificial Intelligence in Management of Diabetes in Iran: A Systematic Review

Fatemeh Bahador, Azam Sabahi, Samaneh Jalali, Fatemeh Ameri • پیاورد سلامت (2023)

Background and Aim: Diabetes is one of the most common metabolic diseases in Iran and the fifth leading cause of death all over the world. Its spread around the world has created new methods in biomedical research, including artificial inte...

DOAJ Open Access (DOAJ)