Reset
Showing 20 of 3,336 academic articles

APRICOIN: An Adaptive Approach for Prioritizing High-Risk Containers Inspections

Mohamed Yassine Samiri, Mehdi Najib, Abdelaziz Elfazziki, Mohamed Nezar Abourraja et al. • IEEE Access (2017)

Risk evaluation of the containers remains a difficult task, often due to incomplete or ambiguous information on containers. In addition, the evaluation process needs to be adapted on an ongoing basis to cope with emerging risk factors. Furt...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2017.2746838

A machine learning approach predicts future risk to suicidal ideation from social media data

Arunima Roy, Katerina Nikolitch, Rachel McGinn, Safiya Jinah et al. • npj Digital Medicine (2020)

Abstract Machine learning analysis of social media data represents a promising way to capture longitudinal environmental influences contributing to individual risk for suicidal thoughts and behaviors. Our objective was to generate an algori...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-020-0287-6

A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis

Muhammad Irfan, Zohaib Mushtaq, Nabeel Ahmed Khan, Salim Nasar Faraj Mursal et al. • IEEE Access (2023)

Machine learning (ML) based bearing fault detection is an emerging application of Artificial Intelligence (AI) that has proven its utility in effectively classifying various faults for timely measures. There are myriad studies dedicated to ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3332243

Artificial Intelligence for Clinical Trial Design

Stefan Harrer, Pratik P. Shah, Bhavna Josephine Antony, Jianying Hu • Trends in Pharmacological Sciences (2019)

Clinical trials consume the latter half of the 10 to 15 year, 1.5-2.0 billion USD, development cycle for bringing a single new drug to market. Hence, a failed trial sinks not only the investment into the trial itself but also the preclinica...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.tips.2019.05.005

Artificial Intelligence Review

Amal Kilani, Ahmed Ben Hamida, Habib Hamam • IGI Global eBooks (2017)

In this paper, we present a profound literature review of the Artificial Intelligence (AI). After defining it, we briefly cover its history and enumerate its principal fields of application. We name for example information system, commerce,...

OPENALEX DOI: https://doi.org/10.4018/978-1-5225-2255-3.ch010

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Heather Marriott, Renata Kabiljo, Guy P Hunt, Ahmad Al Khleifat et al. • Acta Neuropathologica Communications (2023)

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40478-023-01686-8

An automated deep learning framework for brain tumor classification using MRI imagery

Muhammad Aamir, Ziaur Rahman, Uzair Aslam Bhatti, Waheed Ahmed Abro et al. • Scientific Reports (2025)

Abstract The precise and timely diagnosis of brain tumors is essential for accelerating patient recovery and preserving lives. Brain tumors exhibit a variety of sizes, shapes, and visual characteristics, requiring individualized treatment s...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-02209-2

IEEE Access Special Section Editorial: 5G and Beyond Mobile Wireless Communications Enabling Intelligent Mobility

Ke Guan, Markus Rupp, Thomas Kurner, Cesar Briso et al. • IEEE Access (2020)

Increasing urbanization is one major trend that shapes tomorrow’s society; by 2050, more than 85% of the developed world’s population will live in a comparatively small number of ever-growing cities. Within such cities ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3037635

Radiomics and radiogenomics: extracting more information from medical images for the diagnosis and prognostic prediction of ovarian cancer

Song Zeng, Xin-Lu Wang, Hua Yang • Military Medical Research (2024)

Abstract Ovarian cancer (OC) remains one of the most lethal gynecological malignancies globally. Despite the implementation of various medical imaging approaches for OC screening, achieving accurate differential diagnosis of ovarian tumors ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40779-024-00580-1

Can artificial intelligence transform higher education?

Tony Bates, Cristóbal Cobo, Olga Mariño, Steve Wheeler • International Journal of Educational Technology in Higher Education (2020)

Many have argued that the development of artificial intelligence has more potential to change higher education than any other technological advance.For instance, Klutka et al. ( 2018) has listed the following goals for AI in higher educatio...

OPENALEX cc-by DOI: https://doi.org/10.1186/s41239-020-00218-x

Artificial intelligence and employment

Alexandre Georgieff, Raphaela Hyee • OECD social employment and migration working papers (2021)

Recent years have seen impressive advances in artificial intelligence (AI) and this has stoked renewed concern about the impact of technological progress on the labour market, including on worker displacement. This paper looks at the possib...

OPENALEX DOI: https://doi.org/10.1787/c2c1d276-en

Application of artificial intelligence to the electrocardiogram

Zachi Itzhak Attia, David Harmon, Elijah Raphael Behr, Paul A. Friedman • European Heart Journal (2021)

Artificial intelligence (AI) has given the electrocardiogram (ECG) and clinicians reading them super-human diagnostic abilities. Trained without hard-coded rules by finding often subclinical patterns in huge datasets, AI transforms the ECG,...

OPENALEX Open Access DOI: https://doi.org/10.1093/eurheartj/ehab649 PMC: 8500024

A review of optimization strategies for deep and machine learning in diabetic macular edema

A. M. Mutawa, Khalid Sabti, Bibin Shalini Sundaram Thankaleela, Seemant Raizada • Frontiers in Artificial Intelligence (2026)

Diabetic macular edema (DME) is a primary contributor to visual impairment in diabetic patients, necessitating precise and prompt analysis for optimal treatment. Recent breakthroughs in deep learning (DL) and machine learning (ML) have yiel...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1684752

A bibliometric analysis of industry 4.0 digital manufacturing and smart technologies for sustainable development

Ferhat Yilmaz, Zeynep Ozguner • Discover Sustainability (2026)

Abstract This study provides a broad bibliometric analysis of Industry 4.0 as well as technology-based production systems within the appropriate scientific literature to target the description of the dynamic structure, intellectual foundati...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-026-03275-w

Prediction of homologous recombination deficiency from routine histology with attention-based multiple instance learning in nine different tumor types

Chiara Maria Lavinia Loeffler, Omar S. M. El Nahhas, Hannah Sophie Muti, Zunamys I. Carrero et al. • BMC Biology (2024)

Abstract Background Homologous recombination deficiency (HRD) is recognized as a pan-cancer predictive biomarker that potentially indicates who could benefit from treatment with PARP inhibitors (PARPi). Despite its clinical significance, HR...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12915-024-02022-9