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Machine learning and the physical sciences

Giuseppe Carleo, J. I. Cirac, Kyle Stuart Cranmer, Laurent Daudet et al. • Reviews of Modern Physics (2019)

In October 2018 an APS Physics Next Workshop on Machine Learning was held in Riverhead, NY. This article reviews and summarizes the proceedings of this very broad, emerging field.This needs to be a placard in the left-hand column, with a cu...

OPENALEX Open Access DOI: https://doi.org/10.1103/revmodphys.91.045002

Readings in Machine Learning

JUDE W. SHAVLIK, Thomas E. Deitterich, Thomas G. Dietterich (1991)

From the Publisher: The ability to learn is a fundamental characteristic of intelligent behavior. Consequently, machine learning has been a focus of artificial intelligence since the beginnings of AI in the 1950s. The 1980s saw tremendous ...

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Causality for Machine Learning

Bernhard Schölkopf • ACM eBooks (2022)

Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning. This article discusses where links have been and should ...

OPENALEX Open Access DOI: https://doi.org/10.1145/3501714.3501755

Machine Learning in Action

Peter de B. Harrington (2012)

SummaryMachine Learning in Action is unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. You'll use the flexible Python programming language to bui...

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An Introduction to Machine Learning

Solveig Badillo, Balázs Bánfai, Fabian Birzele, Iakov I. Davydov et al. • Clinical Pharmacology & Therapeutics (2020)

In the last few years, machine learning (ML) and artificial intelligence have seen a new wave of publicity fueled by the huge and ever-increasing amount of data and computational power as well as the discovery of improved learning algorithm...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1002/cpt.1796 PMC: 7189875

Machine Learning for Medical Imaging

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

A Transformer-Based Approach for Efficient Geometric Feature Extraction from Vector Shape Data

Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang et al. • Applied Sciences (2025)

The extraction of shape features from vector elements is essential in cartography and geographic information science, supporting a range of intelligent processing tasks. Traditional methods rely on different machine learning algorithms tail...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15052383

Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection

Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja • BioData Mining (2021)

Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13040-021-00271-w

On-board Clutch Slippage Detection and Diagnosis in Heavy Duty Machine

Elisabeth Källström, Tomas Olsson, John Lindström, Lars Hakansson et al. • International Journal of Prognostics and Health Management (2018)

In order to reduce unnecessary stops and expensive downtime originating from clutch failure of construction equipment machines; adequate real time sensor data measured on the machine in combination with feature extraction and classification...

DOAJ Open Access (DOAJ) DOI: doi:10.36001/ijphm.2018.v9i1.2693

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

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

Inferring Markovian quantum master equations of few-body observables in interacting spin chains

Francesco Carnazza, Federico Carollo, Dominik Zietlow, Sabine Andergassen et al. • New Journal of Physics (2022)

Full information about a many-body quantum system is usually out-of-reach due to the exponential growth—with the size of the system—of the number of parameters needed to encode its state. Nonetheless, in order to understand the complex phen...

DOAJ Open Access (DOAJ) DOI: 10.1088/1367-2630/ac7df6