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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 satellite-derived, ground-measurement-independent monthly PM2.5 mass concentration dataset over China during 2000 - 2015

Ying Zhang, Zhengqiang Li, Yuanyuan Wei, Zongren Peng • Big Earth Data (2021)

Following the accelerated development of urbanization and industrialization, atmospheric particulate matter has become a significant threat to public health globally. Environmental health studies usually use the mass concentration of fine p...

DOAJ Open Access (DOAJ) DOI: 10.1080/20964471.2021.1918908

Artificial intelligence, systemic risks, and sustainability

Victor Galaz, Miguel Ángel Centeno, Peter W. Callahan, Amar Causevic et al. • Technology in Society (2021)

Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as sensor technology and robotics are likely to change the way individuals, communities, governments...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.techsoc.2021.101741

Study on the impact of meteorological factors on influenza in different periods and prediction based on artificial intelligence RF-Bi-LSTM algorithm: to compare the COVID-19 period with the non-COVID-19 period

Hansong Zhu, Si Chen, Weixia Qin, Joldosh Aynur et al. • BMC Infectious Diseases (2024)

Abstract Objective At different times, public health faces various challenges and the degree of intervention measures varies. The research on the impact and prediction of meteorology factors on influenza is increasing gradually, however, th...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12879-024-09750-x

Integrative Approaches to Soybean Resilience, Productivity, and Utility: A Review of Genomics, Computational Modeling, and Economic Viability

Yuhong Gai, Shuhao Liu, Zhidan Zhang, Jian Wei et al. • Plants (2025)

Soybean is a vital crop globally and a key source of food, feed, and biofuel. With advancements in high-throughput technologies, soybeans have become a key target for genetic improvement. This comprehensive review explores advances in multi...

DOAJ Open Access (DOAJ) DOI: 10.3390/plants14050671

Explainable and perturbation-resilient model for cyber-threat detection in industrial control systems Networks

Urslla Uchechi Izuazu, Cosmas Ifeanyi Nwakanma, Dong-Seong Kim, Jae Min Lee • Discover Internet of Things (2025)

Abstract Deep learning-based intrusion detection systems (DL-IDS) have proven effective in detecting cyber threats. However, their vulnerability to adversarial attacks and environmental noise, particularly in industrial settings, limits pra...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43926-025-00100-0

Molecular biology and integrated strategies for activating cryptic biosynthetic gene clusters toward next-generation antibiotic discovery

Veilumuthu Pattapulavar, Sathiyabama Ramanujam, Avanthi Yellampalli, Henu Sree Badiginchala et al. • Frontiers in Bioinformatics (2026)

Antimicrobial resistance (AMR) has been identified as one of the 21st century’s severest global public health crises. AMR led to an estimated 4.95 million deaths in 2019 and will claim 10 million lives a year by 2050 in the absence of targe...

DOAJ Open Access (DOAJ) DOI: 10.3389/fbinf.2026.1893206

Association between myosteatosis and impaired glucose metabolism: A deep learning whole‐body magnetic resonance imaging population phenotyping approach

Matthias Jung, Hanna Rieder, Marco Reisert, Susanne Rospleszcz et al. • Journal of Cachexia, Sarcopenia and Muscle (2024)

Abstract Background There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with th...

DOAJ Open Access (DOAJ) DOI: 10.1002/jcsm.13527

REVIEW OF THEORETICAL APPROACHES TO USING OF ARTIFICIAL INTELLIGENCE FOR PLANNING PROBLEMS IN ECONOMICS

Gocha Ugulava • ეკონომიკური პროფილი (2022)

Artificial intelligence methods and technologies are increasingly included in human's everyday life. Managing actors in the context of their activities, from the planning stage to the decision-making stage, are faced with the need to operat...

DOAJ Open Access (DOAJ) DOI: 10.52244/ep.2021.22.11

Analysis of Water Pollution Using Different Physicochemical Parameters: A Study of Yamuna River

Rohit Sharma, Raghvendra Kumar, Suresh Chandra Satapathy, Nadhir Al-Ansari et al. • Frontiers in Environmental Science (2020)

The Yamuna river has become one of the most polluted rivers in India as well as in the world because of the high-density population growth and speedy industrialization. The Yamuna river is severely polluted and needs urgent revival. The Yam...

DOAJ Open Access (DOAJ) DOI: 10.3389/fenvs.2020.581591

A Risk Identification Method for Ensuring AI-Integrated System Safety for Remotely Controlled Ships with Onboard Seafarers

Changui Lee, Seojeong Lee • Journal of Marine Science and Engineering (2024)

The maritime sector is increasingly integrating Information and Communication Technology (ICT) and Artificial Intelligence (AI) technologies to enhance safety, environmental protection, and operational efficiency. With the introduction of t...

DOAJ Open Access (DOAJ) DOI: 10.3390/jmse12101778