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Proposing New Data Whitening Method through Application of LSTM Method for Fault Condition Prediction in Bearing Data

Nasrin Rezaei, Andreas Rehkopf • Advances in Engineering and Intelligence Systems (2026)

In the context of big data, data preprocessing, especially data whitening, plays a pivotal role in improving the effectiveness of AI models. While traditional whitening methods suffer from severe computational bottlenecks, arising from the ...

DOAJ Open Access (DOAJ) DOI: 10.22034/aeis.2026.575941.1510

Computer vision and machine‐learning techniques for quantification and predictive modeling of intracellular anticancer drug delivery by nanocarriers

Sanjay Goswami, Kshama D. Dhobale, Ravindra D. Wavhale, Barnali Goswami et al. • Applied AI Letters (2022)

Abstract The field of cancer nanomedicine has made significant progress, but its clinical translation is impeded by many challenges, such as the difficulty in analyzing intracellular anticancer drug release by the nanocarriers due to the la...

DOAJ Open Access (DOAJ) DOI: 10.1002/ail2.50

Deep Learning

Dulani Meedeniya • Chapman & Hall/CRC eBooks (2023)

This book focuses on deep learning (DL), which is an important aspect of data science, that includes predictive modeling. DL applications are widely used in domains such as finance, transport, healthcare, automanufacturing, and advertising....

OPENALEX public-domain DOI: https://doi.org/10.1201/9781003390824

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

Comprehensive framework of machine learning and deep learning architectures with metaheuristic optimization for high-fidelity prediction of nanofluid specific heat capacity

Priya Mathur, Dheeraj Kumar, Farhan Sheth, Hammad Shaikh et al. • Scientific Reports (2025)

Abstract Accurately predicting the specific heat capacity of nanofluids is critical for optimizing their performance in engineering and industrial applications. This study explores twelve machine learning and deep learning models using conv...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-28268-z

RDDA: Rectified Discriminatory Delta-Adjust

Ziad F. Doughan, Sari S. Itani • IEEE Access (2025)

This paper introduces Rectified Discriminatory Delta-Adjust (RDDA), a novel methodology that enhances interpolation-based predictive modeling through adaptive sensitivity parameters. Building upon the foundational Delta-Adjust algorithm, RD...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3641537

Integrating BIM, Machine Learning, and PMBOK for Green Project Management in Saudi Arabia: A Framework for Energy Efficiency and Environmental Impact Reduction

Maher Abuhussain, Ali Hussain Alhamami, Khaled Almazam, Omar Humaidan et al. • Buildings (2025)

This study introduces a comprehensive framework combining building information modeling (BIM), project management body of knowledge (PMBOK), and machine learning (ML) to optimize energy efficiency and reduce environmental impacts in Riyadh’...

DOAJ Open Access (DOAJ) DOI: 10.3390/buildings15173031

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling

Mafalda Reis Pereira, Mafalda Reis Pereira, Filipe Neves dos Santos, Fernando Tavares et al. • Frontiers in Plant Science (2023)

Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpls.2023.1242201

Precision Microalgae: A New Conceptual Framework for Bioengineering Applications

Darissa Alves Dutra, Richard Luan Silva Machado, Mariany Costa Deprá, Adriane Terezinha Schneider et al. • Bioengineering (2026)

Microalgae are promising platforms for biomass production, carbon capture, biofuels, and high-value bioproducts. However, despite significant advances in cultivation technologies, reactor engineering, and metabolic engineering, industrial i...

DOAJ Open Access (DOAJ) DOI: 10.3390/bioengineering13091011

Artificial Intelligence for Enhancing Resilience

Nitin Rane, Mallikarjuna Paramesha, Saurabh Choudhary, Jayesh Rane • Journal of Applied Artificial Intelligence (2024)

In an increasingly complex and unpredictable world, resilience-the ability to withstand and recover from adverse conditions is essential across various sectors. This research paper investigates the transformative potential of artificial int...

OPENALEX cc-by DOI: https://doi.org/10.2139/ssrn.4831911

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

Artificial Intelligence in Cardiology

Kipp W. Johnson, Jessica Torres Soto, Benjamin Scott Glicksberg, Khader Shameer et al. • Journal of the American College of Cardiology (2018)

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial ...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.jacc.2018.03.521