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Machine Learning for Electrocatalyst and Photocatalyst Design and Discovery

Haoxin Mai, Tu C. Le, Dehong Chen, David Alan Winkler et al. • Chemical Reviews (2022)

Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels, reducing the impact of global warming, and providing solutions to environmental pollution. Improved processes for catalyst design and a better unde...

OPENALEX DOI: https://doi.org/10.1021/acs.chemrev.2c00061

Deciphering Exhaled Aerosol Fingerprints for Early Diagnosis and Personalized Therapeutics of Obstructive Respiratory Diseases in Small Airways

Xiuhua April Si, Jinxiang Xi • Journal of Nanotheranostics (2021)

Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challengin...

DOAJ Open Access (DOAJ) DOI: 10.3390/jnt2030007

Machine learning in pain research

Jörn Lötsch, Alfred Ultsch • Pain (2017)

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1097/j.pain.0000000000001118 PMC: 5895117

Virtual CT Myelography: A Patch-Based Machine Learning Model to Improve Intraspinal Soft Tissue Visualization on Unenhanced Dual-Energy Lumbar Spine CT

Xuan V. Nguyen, Devi D. Nelakurti, Engin Dikici, Sema Candemir et al. • Information (2022)

Background: Distinguishing between the spinal cord and cerebrospinal fluid (CSF) non-invasively on CT is challenging due to their similar mass densities. We hypothesize that patch-based machine learning applied to dual-energy CT can accurat...

DOAJ Open Access (DOAJ) DOI: 10.3390/info13090412

Machine Learning and the Future of Cardiovascular Care

Giorgio Quer, Ramy Arnaout, Michael Henne, Rima Arnaout • Journal of the American College of Cardiology (2021)

The role of physicians has always been to synthesize the data available to them to identify diagnostic patterns that guide treatment and follow response. Today, increasingly sophisticated machine learning algorithms may grow to support clin...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.jacc.2020.11.030 PMC: 7839163

Information disclosure and funding success of green crowdfunding campaigns: a study on GoFundMe

Ziyi Yin, Guowei Huang, Rui Zhao, Sen Wang et al. • Financial Innovation (2024)

Abstract Crowdfunding has become important in increasing financial support for the development of green technologies. Self-disclosed information significantly affects supporters’ decisions and is important for the success of green project f...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40854-024-00666-8

A Deep Dive into a Groundbreaking Approach to Machine Learning-Powered E-Learning

Subhabrata Sengupta, Rupayan Das, Satyajit Chakrabarti • Emitter: International Journal of Engineering Technology (2024)

Information retrieval aims to find the most important data for specific queries. The challenge is retrieving relevant data efficiently due to the large search area. Existing solutions lead to unnecessary processing costs. Additionally, iden...

DOAJ Open Access (DOAJ) DOI: 10.24003/emitter.v12i2.855

Advancing Biosensors with Machine Learning

Feiyun Cui, Yun Yue, Yi Zhang, Ziming Zhang et al. • ACS Sensors (2020)

Chemometrics play a critical role in biosensors-based detection, analysis, and diagnosis. Nowadays, as a branch of artificial intelligence (AI), machine learning (ML) have achieved impressive advances. However, novel advanced ML methods, es...

OPENALEX DOI: https://doi.org/10.1021/acssensors.0c01424

Spatial analysis of smart tourism contrasts A comparison between tourist attractions in Cairo and Dubai

Walaa Mohamed Najeb • Al-Mağallah Al-ʿilmiyyaẗ Li Kulliyyaẗ Al-Adāb - Ǧāmiʿaẗ Asyūṭ (2026)

Technology has undergone rapid advancements, significantly impacting various sectors, with the tourism industry emerging as one of the most benefited. This research examines several key aspects, including: An overview of Cairo and Dubai as ...

DOAJ Open Access (DOAJ) DOI: 10.21608/aakj.2025.429364.2248

Development of a Data-Based Machine Learning Model for Classifying and Predicting Property Damage Caused by Fire

Jongho Lee, Jiuk Shin, Jaewook Lee, Chorong Park et al. • Applied Sciences (2023)

Large fires in factories cause severe human casualties and property damage. Thus, preparing more economical and efficient management strategies for fire prevention can significantly improve fire safety. This study deals with property damage...

DOAJ Open Access (DOAJ) DOI: 10.3390/app132111866

A Prediction Model for Spot LNG Prices Based on Machine Learning Algorithms to Reduce Fluctuation Risks in Purchasing Prices

Sun-Feel Yang, So-Won Choi, Eul-Bum Lee • Energies (2023)

The ongoing Russia–Ukraine conflict has exacerbated the global crisis of natural gas supply, particularly in Europe. During the winter season, major importers of liquefied natural gas (LNG), such as South Korea and Japan, were directly affe...

DOAJ Open Access (DOAJ) DOI: 10.3390/en16114271

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

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

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

The voice of depression: speech features as biomarkers for major depressive disorder

Felix Menne, Felix Dörr, Julia Schräder, Johannes Tröger et al. • BMC Psychiatry (2024)

Abstract Background Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patient...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12888-024-06253-6

Virtual reality in skill development through user experience and technology advancements

Mochammad Hannats Hanafi Ichsan, Cecilia Sik-Lanyi, Tibor Guzsvinecz • Discover Computing (2025)

Abstract New technologies, such as Virtual Reality (VR) / Virtual Environment (VE), which focus on User Experience (UX) to provide more engaging and immersive experiences, can help people grow their skills. Technology advancement is also an...

DOAJ Open Access (DOAJ) DOI: 10.1007/s10791-025-09703-1

Artificial Intelligence Adoption and Employee Productivity in Vietnam’s Technology Sector: Evidence From Telecommunications and IT Firms

Nguyen Trung Kien, Quang Hung Do, Nguyen Tung Duong • SAGE Open (2026)

This study investigates the impact of artificial intelligence (AI) adoption on employee productivity within Vietnam’s technology sector, with a particular focus on telecommunications and information technology firms. Using survey data colle...

DOAJ Open Access (DOAJ) DOI: 10.1177/21582440261488067