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Academic Articles & Research Papers
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Qingxia Chen • Discover Artificial Intelligence
(2025)
Abstract This study explores the application of artificial intelligence (AI) in improving the trial efficiency of criminal cases. Using a dataset consisting of 500 criminal case records, including minor, ordinary, and complex cases, we appl...
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Open Access (DOAJ)
DOI: 10.1007/s44163-025-00353-2
Cristian Cosentino, Simone Gatto, Pietro Liò, Fabrizio Marozzo • Future Internet
(2026)
Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...
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Open Access (DOAJ)
DOI: 10.3390/fi18030174
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)
Abdullah Ayub Khan, Asif Ali Laghari, Shafique Ahmad Awan • ICST Transactions on Scalable Information Systems
(2018)
INTRODUCTION: Due to the advancement in the field of Artificial Intelligence (AI), the ability to tackle entire problems of machine intelligence. Nowadays, Machine learning (ML) is becoming a hot topic due to the direct training of machines...
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DOI: https://doi.org/10.4108/eai.21-4-2021.169418
Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera et al. • IEEE Access
(2020)
Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning (DL) is already present in many applications ranging from computer vision for medicine to autonomous driving of modern cars as well as other sectors in ...
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Open Access (DOAJ)
DOI: 10.1109/ACCESS.2020.3039858
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...
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Open Access (DOAJ)
DOI: 10.1002/ail2.50
Ji Su Hwang, Seok Gi Kim, Tae Hwan Shin, Yong Eun Jang et al. • Pharmaceutics
(2022)
Cancer is a group of diseases causing abnormal cell growth, altering the genome, and invading or spreading to other parts of the body. Among therapeutic peptide drugs, anticancer peptides (ACPs) have been considered to target and kill cance...
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Open Access (DOAJ)
DOI: 10.3390/pharmaceutics14050997
Mohammad Mustafa Taye • Computers
(2023)
In recent years, deep learning (DL) has been the most popular computational approach in the field of machine learning (ML), achieving exceptional results on a variety of complex cognitive tasks, matching or even surpassing human performance...
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DOI: https://doi.org/10.3390/computers12050091
Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan et al. • BMC Psychiatry
(2025)
Abstract Background Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional s...
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Open Access (DOAJ)
DOI: 10.1186/s12888-025-07196-2
Dimitrios Georgiou, Sotiris Kotsiantis, Fotini Sereti • Mathematics
(2026)
Topological data analysis (TDA) has evolved into a flexible and robust paradigm for obtaining qualitative, geometry-inspired insights from high-dimensional, noisy, and complex data. Grounded in algebraic topology, geometry, statistics, and ...
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Open Access (DOAJ)
DOI: 10.3390/math14122205
Chayakrit Krittanawong, Kipp W. Johnson, Robert S. Rosenson, Zhen Wang et al. • European Heart Journal
(2019)
Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via...
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Open Access
DOI: https://doi.org/10.1093/eurheartj/ehz056
PMC: 6600129
Boris Pyakillya, Н. Я. Казаченко, N Mikhailovsky • Journal of Physics Conference Series
(2017)
The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG d...
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DOI: https://doi.org/10.1088/1742-6596/913/1/012004
Mingyu Kim, Jihye Yun, Yongwon Cho, Keewon Shin et al. • Neurospine
(2019)
The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learn...
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DOI: https://doi.org/10.14245/ns.1938396.198
PMC: 6945006
Rocio Vargas, Amir Hosein Mosavi, Ramon Ruiz • Preprints.org
(2018)
Deep learning is an emerging area of machine learning (ML) research. It comprises multiple hidden layers of artificial neural networks. The deep learn- ing methodology applies nonlinear transformations and model abstractions of high level i...
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DOI: https://doi.org/10.20944/preprints201810.0218.v1
Daniel Kirk, E.J. Kok, Michele Tufano, Bedir Teki̇nerdoğan et al. • Advances in Nutrition
(2022)
Data currently generated in the field of nutrition are becoming increasingly complex and high-dimensional, bringing with them new methods of data analysis. The characteristics of machine learning (ML) make it suitable for such analysis and ...
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DOI: https://doi.org/10.1093/advances/nmac103
PMC: 9776646
Vishal Kumar Goar, Nagendra Singh Yadav • Advances in business information systems and analytics book series
(2024)
This chapter focuses on providing a complete grasp of the foundations of machine learning (ML). Machine learning is a rapidly evolving domain with wide-ranging applications, from natural language processing to autonomous vehicles. This chap...
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DOI: https://doi.org/10.4018/979-8-3693-1598-9.ch002
Ahmed E. Radwan, David A. Wood, Ahmed A. Radwan • Journal of Rock Mechanics and Geotechnical Engineering
(2022)
Pore pressure is an essential parameter for establishing reservoir conditions, geological interpretation and drilling programs. Pore pressure prediction depends on information from various geophysical logs, seismic, and direct down-hole pre...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrmge.2022.01.012
Xin Qian, Yu Li, Xianghui Zhang, Heng Guo et al. • Frontiers in Cardiovascular Medicine
(2022)
BackgroundCardiovascular diseases (CVD) are currently the leading cause of premature death worldwide. Model-based early detection of high-risk populations for CVD is the key to CVD prevention. Thus, this research aimed to use machine learni...
DOAJ
Open Access (DOAJ)
DOI: 10.3389/fcvm.2022.854287
Jichao Li, Xiaosong Du, Joaquim R. R. A. Martins • Progress in Aerospace Sciences
(2022)
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep learning. We review the applications of ML in ASO to date and pr...
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DOI: https://doi.org/10.1016/j.paerosci.2022.100849
Artur M. Schweidtmann, Erik Esche, Asja Fischer, Marius Kloft et al. • Chemie Ingenieur Technik
(2021)
Abstract The transformation of the chemical industry to renewable energy and feedstock supply requires new paradigms for the design of flexible plants, (bio‐)catalysts, and functional materials. Recent breakthroughs in machine learning (ML)...
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DOI: https://doi.org/10.1002/cite.202100083