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Accuracy of machine learning for differentiation between optic neuropathies and pseudopapilledema

Jin Mo Ahn, Sangsoo Kim, Kwang-Sung Ahn, Sung-Hoon Cho et al. • BMC Ophthalmology (2019)

Abstract Background This study is to evaluate the accuracy of machine learning for differentiation between optic neuropathies, pseudopapilledema (PPE) and normals. Methods Two hundred and ninety-five images of optic neuropathies, 295 images...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12886-019-1184-0

Condensing AI-Based Attitude Control Using Kolmogorov–Arnold Networks for Memory Efficiency

Kirill Djebko, Patrick Schurk, Tom Baumann, Frank Puppe et al. • Aerospace (2025)

Artificial Intelligence (AI) is rapidly transforming engineering fields, from robotics to aerospace, with applications in control systems for UAVs and satellites. This work builds on a previously developed AI attitude controller for the Inn...

DOAJ Open Access (DOAJ) DOI: 10.3390/aerospace12121039

Deep-learning–based non-contrast CT for detecting acute ischemic stroke: a systematic review and HSROC meta-analysis of patient-level diagnostic accuracy

Kalab Yigermal Gete, Asnakew Achaw Ayele • BMC Neurology (2025)

Abstract Background Non-contrast CT (NCCT) is first-line imaging for suspected acute ischemic stroke (AIS) but has limited early sensitivity; deep learning (DL) may improve patient-level detection. Objectives To estimate the diagnostic accu...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12883-025-04528-3

Ethical and legal concerns in artificial intelligence applications for the diagnosis and treatment of lung cancer: a scoping review

Ghenwa Chamouni, Filippo Lococo, Carolina Sassorossi, Nkunzi Atuhaire et al. • Frontiers in Public Health (2025)

IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpubh.2025.1663298

Scalable and accurate deep learning with electronic health records

Alvin Rajkomar, Eyal Oren, Kai Chen, Andrew M. Dai et al. • npj Digital Medicine (2018)

Predictive modeling with electronic health record (EHR) data is anticipated to drive personalized medicine and improve healthcare quality. Constructing predictive statistical models typically requires extraction of curated predictor variabl...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41746-018-0029-1 PMC: 6550175

ASAVACT: Arabic sentiment analysis for vaccine-related COVID-19 tweets using deep learning

Sarah Alhumoud, Asma Al Wazrah, Laila Alhussain, Lama Alrushud et al. • PeerJ Computer Science (2023)

COVID-19 has become a global pandemic that has affected not only the health sector but also economic, social, and psychological well-being. Individuals are using social media platforms to communicate their feelings and sentiments about the ...

DOAJ Open Access (DOAJ) DOI: 10.7717/peerj-cs.1507

A feasibility study of deep learning-based segmentation of the inferior alveolar nerve on magnetic resonance neurography

Yoon Joo Choi, Sujeong Han, Chena Lee, Kug Jin Jeon et al. • Scientific Reports (2026)

Abstract The inferior alveolar nerve (IAN) is the major sensory nerve innervating the mandibular region, and its automatic segmentation is crucial. It has been indirectly identified on the mandibular canal, which surrounds the IAN, using co...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-45392-6

Credit card fraud detection in the era of disruptive technologies: A systematic review

Asma Cherif, Arwa Badhib, Heyfa Ammar, Suhair Alshehri et al. • Journal of King Saud University: Computer and Information Sciences (2023)

Credit card fraud is becoming a serious and growing problem as a result of the emergence of innovative technologies and communication methods, such as contactless payment. In this article, we present an in-depth review of cutting-edge resea...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jksuci.2022.11.008

Review of deep learning for photoacoustic imaging

Changchun Yang, Hengrong Lan, Feng Gao, Fei Gao • Photoacoustics (2020)

Machine learning has been developed dramatically and witnessed a lot of applications in various fields over the past few years. This boom originated in 2009, when a new model emerged, that is, the deep artificial neural network, which began...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.pacs.2020.100215 PMC: 7779783

Analysis of Customer Churn Classification for Sinarmas Syariah Lhokseumawe Insurance Services Using Deep Learning Tabnet and Explainable AI

Syarifah Muliana, Taufiq Taufiq, Munirul Ula • Journal of Applied Informatics and Computing (2026)

Customer churn is a major challenge in the insurance industry because it directly affects customer retention, business sustainability, and company profitability. Early identification of customers at risk of churn is therefore essential for ...

DOAJ Open Access (DOAJ) DOI: 10.30871/jaic.v10i3.12864

Communicative management in present-day university

Petryshyna Olga, Boyko Mariya • SHS Web of Conferences (2021)

In modern academic community not only communication management plays a great role. Monitoring of expectations, awareness of communicative needs, the course and results of communicative interaction, barriers hindering rational managerial dec...

DOAJ Open Access (DOAJ) DOI: 10.1051/shsconf/202110402012

HRCTCov19-a high-resolution chest CT scan image dataset for COVID-19 diagnosis and differentiation

Iraj Abedi, Mahsa Vali, Bentolhoda Otroshi, Maryam Zamanian et al. • BMC Research Notes (2024)

Abstract Introduction Computed tomography (CT) was a widely used diagnostic technique for COVID-19 during the pandemic. High-Resolution Computed Tomography (HRCT), is a type of computed tomography that enhances image resolution through the ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13104-024-06693-z

Behavioral Motivation and Influencing Factors of Graduate Students Using AIGC Tool: An Empirical Analysis Based on Questionnaire Survey

Yijia WAN, Liping GU • Nongye tushu qingbao xuebao (2024)

[Purpose/Significance] To explore in depth the acceptance and usage habits of AIGC tools by graduate students in the process of academic research, and to promote the positive attention and application of emerging technologies by graduate st...

DOAJ Open Access (DOAJ) DOI: 10.13998/j.cnki.issn1002-1248.24-0716

Comparison of Deep Learning Models for LAI Simulation and Interpretable Hydrothermal Coupling in the Loess Plateau

Junpo Yu, Yajun Si, Wen Zhao, Zeyu Zhou et al. • Plants (2025)

As the world’s largest loess deposit region, the Loess Plateau’s vegetation dynamics are crucial for its regional water–heat balance and ecosystem functioning. Leaf Area Index (LAI) serves as a key indicator bridging canopy architecture and...

DOAJ Open Access (DOAJ) DOI: 10.3390/plants14152391