Home »
Academic Articles & Research Papers
Showing 20 of 1,495 academic articles
Bo Wen, Wen‐Feng Zeng, Yuxing Liao, Zhiao Shi et al. • PROTEOMICS
(2020)
Proteomics, the study of all the proteins in biological systems, is becoming a data-rich science. Protein sequences and structures are comprehensively catalogued in online databases. With recent advancements in tandem mass spectrometry (MS)...
OPENALEX
cc-by
DOI: https://doi.org/10.1002/pmic.201900335
PMC: 7757195
Ajay Shrestha, Ausif Mahmood • IEEE Access
(2019)
Deep learning (DL) is playing an increasingly important role in our lives. It has already made a huge impact in areas, such as cancer diagnosis, precision medicine, self-driving cars, predictive forecasting, and speech recognition. The pain...
OPENALEX
Open Access
DOI: https://doi.org/10.1109/access.2019.2912200
Wenjun Zhang, Guosheng Yang, Yingzi Lin, Chunli Ji et al. • World Automation Congress (WAC)
(2018)
Deep learning has become a buzz word recently. However, there is a lack of unified definition to deep learning in literature. The goal of this paper is to overview various definitions to deep learning and to show their limitations. Finally,...
OPENALEX
DOI: https://doi.org/10.23919/wac.2018.8430387
Cyprien Alexandre, Rodolphe Devillers, David Mouillot, Raphael Seguin et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
(2024)
Detecting and tracking ships remotely is now required in a wide range of contexts, from military security to illegal immigration control, as well as the management of fisheries and marine protected areas. Among the available methods, radar ...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/JSTARS.2024.3437187
Noritaka Fukunaga, Sho Sanami, Hiroya Kitasaka, Yuji Tsuzuki et al. • Reproductive Medicine and Biology
(2020)
Abstract Purpose To establish an automated pronuclei determination system by analysis using deep learning technology which is able to effectively learn with limited amount of supervised data. Methods An algorithm was developed by explicitly...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/rmb2.12331
Leander van Eekelen, Joey Spronck, Monika Looijen-Salamon, Shoko Vos et al. • Scientific Reports
(2024)
Abstract Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-024-57067-1
ZHANG Lei, LI Yuewen, SHI Yi • Guangtongxin yanjiu
(2026)
Due to the dynamic monitoring capability, Distributed Acoustic Sensing (DAS) has been widely deployed in various industrial scenarios. Deep learning greatly boosts the event detection accuracy of fiber sensing systems. Nevertheless, practic...
DOAJ
Open Access (DOAJ)
Paschalis Bizopoulos, Dimitris Koutsouris • IEEE Reviews in Biomedical Engineering
(2018)
The medical field is creating large amount of data that physicians are unable to decipher and use efficiently. Moreover, rule-based expert systems are inefficient in solving complicated medical tasks or for creating insights using big data....
OPENALEX
Open Access
DOI: https://doi.org/10.1109/rbme.2018.2885714
Erik Gawehn, Jan A. Hiss, Gisbert Schneider • Molecular Informatics
(2015)
Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical ...
OPENALEX
DOI: https://doi.org/10.1002/minf.201501008
Khawja Imran Masud, Md Yasin Zihad, Mehedi Hasan Shuvo, Mst Raonik Jannat et al. • PLoS ONE
(2026)
Early and real-time detection of rice leaf diseases (RLD) poses a significant challenge for farmers, especially in rural regions with limited access to advanced technology. Conventional deep learning models often require substantial computa...
DOAJ
Open Access (DOAJ)
DOI: 10.1371/journal.pone.0356383
Xuedan Du, Yinghao Cai, Shuo Wang, Leijie Zhang • Youth Academic Annual Conference of Chinese Association of Automation (YAC)
(2016)
In recent years, deep learning has achieved great success in many fields, such as computer vision and natural language processing. Compared to traditional machine learning methods, deep learning has a strong learning ability and can make be...
OPENALEX
DOI: https://doi.org/10.1109/yac.2016.7804882
Polina Mamoshina, Armando S. Vieira, Eugene Lane, Alex A. Zhavoronkov • Molecular Pharmaceutics
(2016)
Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this ...
OPENALEX
DOI: https://doi.org/10.1021/acs.molpharmaceut.5b00982
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...
OPENALEX
cc-by
DOI: https://doi.org/10.1186/s40537-019-0192-5
Neil Thompson, Kristjan H. Greenewald, Keeheon Lee, Gabriel F. Manso (2023)
Deep learning's recent history has been one of achievement: from triumphing over humans in the game of Go to world-leading performance in image classification, voice recognition, translation, and other tasks.But this progress has come with ...
OPENALEX
cc-by
DOI: https://doi.org/10.21428/bf6fb269.1f033948
Gabriel Chartrand, Phillip M. Cheng, Eugene Vorontsov, Michal Drozdzal et al. • Radiographics
(2017)
Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods prod...
OPENALEX
DOI: https://doi.org/10.1148/rg.2017170077
Ko-Tsung Hsu, Steven Guan, Parag V. Chitnis • Photoacoustics
(2023)
Iterative reconstruction has demonstrated superior performance in medical imaging under compressed, sparse, and limited-view sensing scenarios. However, iterative reconstruction algorithms are slow to converge and rely heavily on hand-craft...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.pacs.2023.100452
Christof Angermueller, Tanel Pärnamaa, Leopold Parts, Oliver Stegle • Molecular Systems Biology
(2016)
Technological advances in genomics and imaging have led to an explosion of molecular and cellular profiling data from large numbers of samples. This rapid increase in biological data dimension and acquisition rate is challenging conventiona...
OPENALEX
other-oa
DOI: https://doi.org/10.15252/msb.20156651
PMC: 4965871
Dimitrios Papamartzivanos, Felix Gomez Marmol, Georgios Kambourakis • IEEE Access
(2019)
The intrusion detection systems (IDSs) are essential elements when it comes to the protection of an ICT infrastructure. A misuse IDS is a stable method that can achieve high attack detection rates (ADR) while keeping false alarm rates under...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2019.2893871
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 ...
OPENALEX
cc-by-nc
DOI: https://doi.org/10.1093/advances/nmac103
PMC: 9776646
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