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Academic Articles & Research Papers
Showing 20 of 107 academic articles
Felipe Oviedo, Juan Lavista Ferres, Tonio Buonassisi, Keith T. Butler • Accounts of Materials Research
(2022)
High Resolution Image Download MS PowerPoint Slide Conspectus Machine learning has become a common and powerful tool in materials research. As more data become available, with the use of high-performance computing and high-throughput experi...
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DOI: https://doi.org/10.1021/accountsmr.1c00244
Gaith Rjoub, Jamal Bentahar, Omar Abdel Wahab, Rabeb Mizouni et al. • IEEE Transactions on Network and Service Management
(2023)
The “black-box” nature of artificial intelligence (AI) models has been the source of many concerns in their use for critical applications. Explainable Artificial Intelligence (XAI) is a rapidly growing research field that aims to create mac...
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Open Access
DOI: https://doi.org/10.1109/tnsm.2023.3282740
Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi et al. • Communications Materials
(2022)
Machine learning plays an increasingly important role in many areas of chemistry and materials science, being used to predict materials properties, accelerate simulations, design new structures, and predict synthesis routes of new materials...
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DOI: https://doi.org/10.1038/s43246-022-00315-6
PMC: 9702700
Yiwen Shi, Ping Ren, Yi Zhang, Xiajing Gong et al. • Frontiers in Research Metrics and Analytics
(2021)
Towards the objectives of the UnitedStates Food and Drug Administration (FDA) generic drug science and research program, it is of vital importance in developing product-specific guidances (PSGs) with recommendations that can facilitate and ...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/frma.2021.670006
Julia El Zini, Mariette Awad • ACM Computing Surveys
(2022)
Despite their success, deep networks are used as black-box models with outputs that are not easily explainable during the learning and the prediction phases. This lack of interpretability is significantly limiting the adoption of such model...
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Open Access
DOI: https://doi.org/10.1145/3529755
Gaurav Mohindru, Koushik Mondal, Haider Banka • CAAI Transactions on Intelligence Technology
(2021)
Abstract In the era of automatic task processing or designing complex algorithms, to analyse data, it is always pertinent to find real‐life solutions using cutting‐edge tools and techniques to generate insights into the data. The data‐drive...
DOAJ
Open Access (DOAJ)
DOI: 10.1049/cit2.12032
Zexian Zeng, Yu Deng, Xiaoyu Li, Tristan Naumann et al. • IEEE Transactions on Computational Biology and Bioinformatics
(2018)
This article reviews recent advances in applying natural language processing (NLP) to Electronic Health Records (EHRs) for computational phenotyping. NLP-based computational phenotyping has numerous applications including diagnosis categori...
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Open Access
DOI: https://doi.org/10.1109/tcbb.2018.2849968
PMC: 6388621
Sumaya Mustafa, Mariwan Hama Saeed • Journal of Electrical Systems and Information Technology
(2025)
Abstract Artificial intelligence (AI) models have demonstrated significant success in classifying various types of text. However, the complex nature of these models often complicates the interpretability of their classifications. To address...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s43067-025-00273-2
Muhammad Shoaib Farooq, Syed Muhammad Asadullah Gilani, Muhammad Faraz Manzoor, Momina Shaheen • Information
(2025)
Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding ...
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Open Access (DOAJ)
DOI: 10.3390/info16070595
Yao L, Chen Y, Shen J, Zhang J et al. • Advances in Medical Education and Practice
(2026)
Lifeng Yao, Yijun Chen, Jing Shen, Junge Zhang, Yiwei Zhang, Guojin Liang, Yiqin Ji Department of Anesthesiology, The First Affiliated Hospital of Ningbo University, Ningbo, Zhejiang, People’s Republic of ChinaCorrespondence: Yijun Chen, De...
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Open Access (DOAJ)
Lei Zhang, Yiru Huang, Leiming Yan, Jinghao Ge et al. • Advanced Intelligent Systems
(2024)
Making computers automatically extract latent scientific knowledge from literature is highly desired for future materials and chemical research in the artificial intelligence era. Herein, the natural language processing (NLP)‐based machine ...
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Open Access (DOAJ)
DOI: 10.1002/aisy.202300678
Aditi S. Krishnapriyan, Joseph Montoya, Maciej Haranczyk, Jens Hummelshøj et al. • Scientific Reports
(2021)
Abstract Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an ...
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Open Access (DOAJ)
DOI: 10.1038/s41598-021-88027-8
Rittik Chandra Das Turjy, Fahmid Al Farid, Fahmid Al Farid, Md. Hasan Imam Bijoy et al. • Frontiers in Artificial Intelligence
(2026)
Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...
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Open Access (DOAJ)
DOI: 10.3389/frai.2026.1884567
Liaqat Ali, Ce Zhu, Noorbakhsh Amiri Golilarz, Ashir Javeed et al. • IEEE Access
(2019)
Parkinson's disease (PD) is the second most common neurodegenerative disease of central nervous system (CNS). Till now, there is no definitive clinical examination that can diagnose a PD patient. However, it has been reported that PD patien...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2932037
Om Khare, Sunil Mane, Harshmohan Kulkarni, Ninad Barve • Discover Artificial Intelligence
(2024)
Abstract Plant diseases significantly threaten global agriculture, impacting crop yield and food security. Nearly 30% of the crop yield is lost due to plant diseases. Efficient identification and classification of plant diseases through com...
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Open Access (DOAJ)
DOI: 10.1007/s44163-024-00150-3
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...
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DOI: https://doi.org/10.1016/j.pacs.2020.100215
PMC: 7779783
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...
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Open Access (DOAJ)
DOI: 10.1038/s41598-025-28268-z
Alexander Selvikvåg Lundervold, Arvid Lundervold • Zeitschrift für Medizinische Physik
(2018)
What has happened in machine learning lately, and what does it mean for the future of medical image analysis? Machine learning has witnessed a tremendous amount of attention over the last few years. The current boom started around 2009 when...
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DOI: https://doi.org/10.1016/j.zemedi.2018.11.002
Justin M. Johnson, Taghi M. Khoshgoftaar • Journal Of Big Data
(2019)
The purpose of this study is to examine existing deep learning techniques for addressing class imbalanced data. Effective classification with imbalanced data is an important area of research, as high class imbalance is naturally inherent in...
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DOI: https://doi.org/10.1186/s40537-019-0192-5
Jason Bell • Wiley eBooks
(2014)
Emotion recognition is an important research topic.Physiological signals seem to be an appropriate way for emotion recognition and specific sensors are required to collect these data.Therefore, laboratory sensors are commonly used while the...
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DOI: https://doi.org/10.1002/9781119183464