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Academic Articles & Research Papers
Showing 20 of 909 academic articles
Su-Hsin Huang, Joon-Khim Loh, Jinn-Tsong Tsai, Ming-Feng Houg et al. • Chinese Journal of Cancer
(2017)
Abstract Background Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s40880-017-0192-9
Ivan Sekaj, Ivan Kénický, Filip Zúbek • Mendel
(2021)
Artificial neural networks are means which are, among several other approaches, effectively usable for modelling and control of non-linear dynamic systems. In case of modelling systems input and output signals are a-priori known, supervised...
DOAJ
Open Access (DOAJ)
DOI: 10.13164/mendel.2021.2.007
Shae T. Hart, Jake Kamenetsky, Christopher A. Kitts • IEEE Access
(2023)
Solving the robotic swarm coverage problem for an elliptical area has various applications for exploring novel environments. Solutions for this problem should cover a specified ellipse and seamlessly adapt to changing numbers of robots. Pre...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2023.3244911
Zhihua Xie BS, Jinfeng Liu PhD, Lixia Hou MS, Haoran Feng MS et al. • Technology in Cancer Research & Treatment
(2026)
Introduction Leukemia is one of the most prevalent cancers in children. The use of total marrow and lymphoid irradiation (TMLI) via helical tomotherapy (TOMO) as a conditioning regimen prior to bone marrow transplant (BMT) has been widely a...
DOAJ
Open Access (DOAJ)
DOI: 10.1177/15330338261426261
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...
DOAJ
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...
DOAJ
Open Access (DOAJ)
DOI: 10.1186/s12888-025-07196-2
salma mostafa ahmed helmy, Salsabil Amin, Abeer mahmoud, El-Sayed El-Horabty • International Journal of Intelligent Computing and Information Sciences
(2026)
The healthcare sector is undergoing rapid transformation driven by advances in artificial intelligence and machine learning, with quantum computing emerging as the next major breakthrough. This paper presents a comparative analysis of class...
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Open Access (DOAJ)
DOI: 10.21608/ijicis.2026.442636.1439
Kirill Djebko, Patrick Schurk, Tom Baumann, Frank Puppe et al. • Aerospace
(2025)
Artificial Intelligence (AI) is rapidly transforming engineering fields, from robotics to aerospace, with applications in control systems for UAVs and satellites. This work builds on a previously developed AI attitude controller for the Inn...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/aerospace12121039
Malik Muhammad Waqar, Hassan Ali, Heng Zhou, Heba G. Mohamed et al. • Sensors
(2025)
In shrimp farming, determining the physical traits of shrimp is vital for assessing their health and growth. One of the critical traits is their size, as it serves as a key indicator of growth rates, biomass, and effective feed management. ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/s25185830
• De Gruyter eBooks
(2020)
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep...
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DOI: https://doi.org/10.1515/9783110670905
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 ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/math14122205
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
Marwan Aly, Mostafa Kamal, Mahmoud Ossman, Kamel El-Sehly et al. • Kafrelsheikh Journal of Information Sciences
(2021)
This paper proposed a smart wearable system for heart disease detection using machine learning and embedded systems. A smart wearable system that able to monitor the heart beat rate condition of patient. The heart beat rate is detected usin...
DOAJ
Open Access (DOAJ)
DOI: 10.21608/kjis.2021.42695.1009
Kamran Kowsari, Donald E. Brown, Mojtaba Heidarysafa, Kiana Jafari Meimandi et al. • International Conference on Machine Learning and Applications
(2017)
Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an importan...
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Open Access
DOI: https://doi.org/10.1109/icmla.2017.0-134
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
Konstantinos Keremis, Eleni Vrochidou, George A. Papakostas • Journal of Imaging
(2025)
The ability of deep learning models to maintain consistent performance under image transformations-termed invariances, is critical for reliable deployment across diverse computer vision applications. This study presents a comprehensive empi...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/jimaging11090322
Chunlong Shao, Ning Zhang, Wei Du, Han Li et al. • Journal of Radiation Research and Applied Sciences
(2026)
Objective: This study was designed to examine the association between preoperative abdominal MRI features derived using a deep learning-based reconstruction (DL-Recon) algorithm and postoperative surgical incision-healing outcomes, while ev...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.jrras.2026.102395
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