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Identification of arachidonic acid metabolism-related diagnostic markers in heart failure based on bioinformatics analysis and machine learning

Saiqing Chen, Chunxia Zhang, Yueting Yu • Frontiers in Cardiovascular Medicine (2025)

BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modul...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcvm.2025.1625064

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...

OPENALEX

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 and deep learning

Christian Janiesch, Patrick Zschech, Kai Heinrich • Electronic Markets (2021)

Abstract Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of a...

OPENALEX cc-by DOI: https://doi.org/10.1007/s12525-021-00475-2

Global patterns of gully occurrence and their sensitivity to environmental changes

Yixian Chen, Sofie De Geeter, Jean Poesen, Francis Matthews et al. • International Soil and Water Conservation Research (2026)

Gully formation is a significant driver of soil erosion and land degradation worldwide and often leads to important downstream impacts. Nonetheless, our understanding of the global patterns and the factors controlling this process remains l...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.iswcr.2025.09.004

Strategy in the Age of Artificial Intelligence

Kareem Ayoub, Kenneth Payne • Journal of Strategic Studies (2015)

We argue that Artificial Intelligence (AI) will, in the very near future, have a profound impact on the conduct of strategy and will be disruptive of existing power balances. To do so, we review the psychological foundations of strategy and...

OPENALEX DOI: https://doi.org/10.1080/01402390.2015.1088838

Defining artificial intelligence for librarians

Andrew Martin Cox, Suvodeep Mazumdar A • Journal of Librarianship and Information Science (2022)

The aim of the paper is to define Artificial Intelligence (AI) for librarians by examining general definitions of AI, analysing the umbrella of technologies that make up AI, defining types of use case by area of library operation, and then ...

OPENALEX cc-by DOI: https://doi.org/10.1177/09610006221142029

The Myth of Artificial Intelligence

Erik J. Larson • Harvard University Press eBooks (2021)

Futurists are certain that humanlike AI is on the horizon, but in fact engineers have no idea how to program human reasoning. AI reasons from statistical correlations across data sets, while common sense is based heavily on conjecture. Erik...

OPENALEX DOI: https://doi.org/10.2307/j.ctv322v43j

Artificial intelligence

S. Pradeesh Hosea, V. Harikrishnan, K. Rajkumar • International Conference on Electronics Computer Technology (2011)

Artificial intelligence research has foundered on the issue of representation. When intelligence is approached in an incremental manner, with strict reliance on interfacing to the real world through perception and action, reliance on repres...

OPENALEX DOI: https://doi.org/10.1109/icectech.2011.5941871

Resistance to Medical Artificial Intelligence

Chiara Longoni, Andrea Bonezzi, Carey K. Morewedge • Journal of Consumer Research (2019)

Abstract Artificial intelligence (AI) is revolutionizing healthcare, but little is known about consumer receptivity to AI in medicine. Consumers are reluctant to utilize healthcare provided by AI in real and hypothetical choices, separate a...

OPENALEX Open Access DOI: https://doi.org/10.1093/jcr/ucz013

Artificial Intelligence in Logistics

László Kota • Advanced Logistic Systems - Theory and Practice (2018)

The artificial intelligence undergoes an enormous development since its appearance in the fifties. The computing power has grown exponentially since then, enabling the use of artificial intelligence applications in different areas. Since th...

OPENALEX DOI: https://doi.org/10.32971/als.2019.004

Neurosurgery and artificial intelligence

Mohammad Mofatteh • AIMS neuroscience (2021)

Neurosurgeons receive extensive and lengthy training to equip themselves with various technical skills, and neurosurgery require a great deal of pre-, intra- and postoperative clinical data collection, decision making, care and recovery. Th...

OPENALEX cc-by DOI: https://doi.org/10.3934/neuroscience.2021025 PMC: 8611194