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Rapid profiling of carcinogenic types of Helicobacter pylori infection via deep learning analysis of label-free SERS spectra of human serum

Fen Li, Yu-Ting Si, Jia-Wei Tang, Zeeshan Umar et al. • Computational and Structural Biotechnology Journal (2024)

WHO classified Helicobacter pylori as a Group I carcinogen for gastric cancer as early as 1994. However, despite the high prevalence of H. pylori infection, only about 3 % of infected individuals eventually develop gastric cancer, with the ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.csbj.2024.09.008

Learning to decode linear codes using deep learning

Eliya Nachmani, Yair Be'ery, David Burshtein • Allerton Conference on Communication, Control, and Computing (2016)

A novel deep learning method for improving the belief propagation algorithm is proposed. The method generalizes the standard belief propagation algorithm by assigning weights to the edges of the Tanner graph. These edges are then trained us...

OPENALEX Open Access DOI: https://doi.org/10.1109/allerton.2016.7852251

Applications of Deep Learning and Reinforcement Learning to Biological Data

Mufti Mahmud, M. Shamim Kaiser, Amir Hussain, Stefano Vassanelli • IEEE Transactions on Neural Networks and Learning Systems (2018)

Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body...

OPENALEX Open Access DOI: https://doi.org/10.1109/tnnls.2018.2790388

A novel agricultural commodity price prediction model integrating deep learning and enhanced swarm intelligence algorithm.

Kaixuan Sun, Qi Yao, Yanhui Li • PLoS ONE (2025)

The volatility of agricultural commodity prices significantly affects market stability and financial market dynamics, especially during periods of economic uncertainty and global shocks. Accurate price prediction, however, remains challengi...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0337103

CAMELON: A System for Crime Metadata Extraction and Spatiotemporal Visualization From Online News Articles

Siripen Pongpaichet, Boonyapat Sukosit, Chitchaya Duangtanawat, Jiramed Jamjongdamrongkit et al. • IEEE Access (2024)

Crimes result in not only loss to individuals but also hinder national economic growth. While crime rates have been reported to decrease in developed countries, underdeveloped and developing nations still suffer from prevalent crimes, espec...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3363879

Automated Lung Sound Classification Using a Hybrid CNN-LSTM Network and Focal Loss Function

Georgios Petmezas, Grigorios-Aris Cheimariotis, Leandros Stefanopoulos, Bruno Rocha et al. • Sensors (2022)

Respiratory diseases constitute one of the leading causes of death worldwide and directly affect the patient’s quality of life. Early diagnosis and patient monitoring, which conventionally include lung auscultation, are essential for the ef...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22031232

Deployment optimization of laser chargers in self-organizing power transfer internet of things

Junzhe Hu, Chuanwen Luo, Yi Hong, Guopeng Wang et al. • Wireless Power Transfer (2025)

Recently, the Internet of Things (IoT) has played an important role in many fields. Nevertheless, the fast and uneven energy consumption of IoT Devices (IoTDs) significantly limits the lifetime of IoT networks. One of the effective solution...

DOAJ Open Access (DOAJ) DOI: 10.48130/wpt-0025-0004

SPAF-SegNeXt: Prior-Guided Attention and Frequency-Spatial Hybrid Fusion for Multimodal Sugarcane Segmentation in Remote Sensing

Wei Zhang, Chao Ren, Haoming Bai, Huada Huang et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2026)

Accurate monitoring of the spatial extent of sugarcane cultivation is critical for optimizing land-use efficiency and regulating the sugar industry. However, sugarcane cultivation areas are characterized by complex topography and fragmented...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2026.3716367

Computational Linguistics and Deep Learning

Christopher D. Manning • Computational Linguistics (2015)

Deep Learning waves have lapped at the shores of computational linguistics for several years now, but 2015 seems like the year when the full force of the tsunami hit the major Natural Language Processing (NLP) conferences. However, some pun...

OPENALEX Open Access DOI: https://doi.org/10.1162/coli_a_00239

Deep-learning-based ghost imaging

Meng Lyu, Wei Wang, Hao Wang, Haichao Wang et al. • Scientific Reports (2017)

In this manuscript, we propose a novel framework of computational ghost imaging, i.e., ghost imaging using deep learning (GIDL). With a set of images reconstructed using traditional GI and the corresponding ground-truth counterparts, a deep...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41598-017-18171-7 PMC: 5736587

DeepTox: Toxicity Prediction using Deep Learning

Andreas Mayr, Günter Klambauer, Thomas Unterthiner, Sepp Hochreiter • Frontiers in Environmental Science (2016)

The Tox21 Data Challenge has been the largest effort of the scientific community to compare computational methods for toxicity prediction. This challenge comprised 12,000 environmental chemicals and drugs which were measured for 12 differen...

OPENALEX cc-by DOI: https://doi.org/10.3389/fenvs.2015.00080

Explainable and reliable kidney CT image classification using self-supervised DeiT-Tiny transformer

Sai Sri Hemantha Konala, Srinivas Koppu • Frontiers in Medicine (2026)

IntroductionKidney-related disorders are one of the global health concerns that require timely detection to prevent severe health complications. The use of computed tomography (CT) images for accurate classification of kidney diseases is im...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2026.1893419

<i>H<sup>2</sup>A<sup>2</sup></i>Net: A Hybrid Convolution and Hybrid Resolution Network with Double Attention for Hyperspectral Image Classification

Hao Shi, Guo Cao, Youqiang Zhang, Zixian Ge et al. • Remote Sensing (2022)

Deep learning (DL) has recently been a core ingredient in modern computer vision tasks, triggering a wave of revolutions in various fields. The hyperspectral image (HSI) classification task is no exception. A wide range of DL-based methods ...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14174235

Multi-Head Transformer Architecture with Higher Dimensional Feature Representation for Massive MIMO CSI Feedback

Qing Chen, Aihuang Guo, Yaodong Cui • Applied Sciences (2024)

To achieve the anticipated performance of massive multiple input multiple output (MIMO) systems in wireless communication, it is imperative that the user equipment (UE) accurately feeds the channel state information (CSI) back to the base s...

DOAJ Open Access (DOAJ) DOI: 10.3390/app14041356

Siamese text classification network (SiamTCN) for multi-class multi-label information extraction of typhoon disasters from social media data

Zhi He, Chengle Zhou, Liwei Zou, Suhong Zhou et al. • International Journal of Digital Earth (2025)

Accurately monitoring disaster effects is a crucial task in relief efforts (e.g. typhoon rescue). Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster researc...

DOAJ Open Access (DOAJ) DOI: 10.1080/17538947.2025.2517790

Deep Learning: A Review

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...

OPENALEX cc-by DOI: https://doi.org/10.20944/preprints201810.0218.v1