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MMSplice: modular modeling improves the predictions of genetic variant effects on splicing

Jun Cheng, Thi Yen Duong Nguyen, Kamil J. Cygan, Muhammed Hasan Çelik et al. • Genome Biology (2019)

Abstract Predicting the effects of genetic variants on splicing is highly relevant for human genetics. We describe the framework MMSplice (modular modeling of splicing) with which we built the winning model of the CAGI5 exon skipping predic...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13059-019-1653-z

A Deep Learning Approach for Network Intrusion Detection System

Ahmad Y. Javaid, Quamar Niyaz, Weiqing Sun, Mansoor Alam • International Conference on Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS) (2016)

A Network Intrusion Detection System (NIDS) helps system administrators to detect network security breaches in their organizations. However, many challenges arise while developing a flexible and efficient NIDS for unforeseen and unpredictab...

OPENALEX cc-by DOI: https://doi.org/10.4108/eai.3-12-2015.2262516

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

Theano: Deep Learning on GPUs with Python

James Bergstra, Frédéric Bastien, Olivier Breuleux, Pascal Lamblin et al. (2012)

In this paper, we present Theano1, a framework in the Python programming language for defining, optimizing and evaluating expressions involving high-level operations on ten-sors. Theano offers most of NumPy’s functionality, but adds automat...

OPENALEX

Review of deep learning for photoacoustic imaging

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...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.pacs.2020.100215 PMC: 7779783

Deep Learning

• 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...

OPENALEX DOI: https://doi.org/10.1515/9783110670905

Computer‐aided diagnosis in the era of deep learning

Heang‐Ping Chan, Lubomir M. Hadjiiski, Ravi K. Samala • Medical Physics (2020)

Computer-aided diagnosis (CAD) has been a major field of research for the past few decades. CAD uses machine learning methods to analyze imaging and/or nonimaging patient data and makes assessment of the patient's condition, which can then ...

OPENALEX Open Access DOI: https://doi.org/10.1002/mp.13764 PMC: 7293164

Face recognition in dense crowd using deep learning approaches with IP camera

Sobhana Mummaneni, Venkata Chaitanya Satya Ramaraju Mudunuri, Sri Veerabhadra Vikas Bommaganti, Bhavya Vani Kalle et al. • Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska (2025)

A facial recognition system is a biometric security and surveillance system that can identify and monitor individuals in a crowded area. Manually monitoring a crowded environment is a difficult and error-prone task. Therefore, in such conte...

DOAJ Open Access (DOAJ) DOI: 10.35784/iapgos.6818

Communicative management in present-day university

Petryshyna Olga, Boyko Mariya • SHS Web of Conferences (2021)

In modern academic community not only communication management plays a great role. Monitoring of expectations, awareness of communicative needs, the course and results of communicative interaction, barriers hindering rational managerial dec...

DOAJ Open Access (DOAJ) DOI: 10.1051/shsconf/202110402012

Comparison of Deep Learning Models for LAI Simulation and Interpretable Hydrothermal Coupling in the Loess Plateau

Junpo Yu, Yajun Si, Wen Zhao, Zeyu Zhou et al. • Plants (2025)

As the world’s largest loess deposit region, the Loess Plateau’s vegetation dynamics are crucial for its regional water–heat balance and ecosystem functioning. Leaf Area Index (LAI) serves as a key indicator bridging canopy architecture and...

DOAJ Open Access (DOAJ) DOI: 10.3390/plants14152391

Deep learning in medical imaging and radiation therapy

Berkman Sahiner, Aria X. Pezeshk, Lubomir M. Hadjiiski, Xiaosong Wang et al. • Medical Physics (2018)

The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; (b) identify common and unique challenges, and strategies that researchers have taken to addr...

OPENALEX Open Access DOI: https://doi.org/10.1002/mp.13264 PMC: 9560030

Deep learning in holography and coherent imaging

Yair Rivenson, Yichen Wu, Aydogan Özcan • Light Science & Applications (2019)

Recent advances in deep learning have given rise to a new paradigm of holographic image reconstruction and phase recovery techniques with real-time performance. Through data-driven approaches, these emerging techniques have overcome some of...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41377-019-0196-0 PMC: 6804620

HDLTex: Hierarchical Deep Learning for Text Classification

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...

OPENALEX Open Access DOI: https://doi.org/10.1109/icmla.2017.0-134

A State-of-the-Art Survey on Deep Learning Theory and Architectures

Md Zahangir Alom, Tarek M. Taha, Chris Yakopcic, Stefan K.E. Westberg et al. • Electronics (2019)

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some ne...

OPENALEX cc-by DOI: https://doi.org/10.3390/electronics8030292