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Showing 20 of 1,342 academic articles

Opportunities and obstacles for deep learning in biology and medicine

Travers H. Ching, Daniel Scott Himmelstein, Brett K. Beaulieu‐Jones, Alexandr A. Kalinin et al. • Journal of The Royal Society Interface (2018)

Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and m...

OPENALEX cc-by DOI: https://doi.org/10.1098/rsif.2017.0387 PMC: 5938574

Deep Learning and Its Applications in Biomedicine

Chensi Cao, Feng Liu, Hai Tan, Deshou Song et al. • Genomics Proteomics & Bioinformatics (2018)

Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitat...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.gpb.2017.07.003 PMC: 6000200

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images

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

Deep learning in optical metrology: a review

Chao Zuo, Jiaming Qian, Shijie Feng, Wei Yin et al. • Light Science & Applications (2022)

With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones in manufacturing, fundamental research, and engineering applications, such as quality control, n...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41377-022-00714-x PMC: 8866517

Deep Learning in Cardiology

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

Applications of Deep Learning in Biomedicine

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

Deep Learning in Medical Image Analysis

Dinggang G. Shen, Guorong Wu A, Heung‐Il Suk • Annual Review of Biomedical Engineering (2017)

This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical image...

OPENALEX Open Access DOI: https://doi.org/10.1146/annurev-bioeng-071516-044442 PMC: 5479722

Deep Learning for Biometrics

Kalaivani Sundararajan, Damon L. Woodard • ACM Computing Surveys (2018)

In the recent past, deep learning methods have demonstrated remarkable success for supervised learning tasks in multiple domains including computer vision, natural language processing, and speech processing. In this article, we investigate ...

OPENALEX DOI: https://doi.org/10.1145/3190618

Deep Learning for Health Informatics

Daniele Ravì, Charence Wong, Fani Deligianni, Melissa Berthelot et al. • IEEE Journal of Biomedical and Health Informatics (2016)

With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on mac...

OPENALEX cc-by DOI: https://doi.org/10.1109/jbhi.2016.2636665

Cauchy non-convex sparse feature selection method for the high-dimensional small-sample problem in motor imagery EEG decoding

Shaorong Zhang, Shaorong Zhang, Qihui Wang, Benxin Zhang et al. • Frontiers in Neuroscience (2023)

IntroductionThe time, frequency, and space information of electroencephalogram (EEG) signals is crucial for motor imagery decoding. However, these temporal-frequency-spatial features are high-dimensional small-sample data, which poses signi...

DOAJ Open Access (DOAJ) DOI: 10.3389/fnins.2023.1292724

Deep learning in bioinformatics

Seonwoo Min, Byunghan Lee, Sungroh Yoon • Briefings in Bioinformatics (2016)

In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-th...

OPENALEX Open Access DOI: https://doi.org/10.1093/bib/bbw068

The Microbiome Composition of a Man's Penis Predicts Incident Bacterial Vaginosis in His Female Sex Partner With High Accuracy

Supriya D. Mehta, Dan Zhao, Stefan J. Green, Walter Agingu et al. • Frontiers in Cellular and Infection Microbiology (2020)

Background: We determined the predictive accuracy of penile bacteria for incident BV in female sex partners. In this prospective cohort, we enrolled Kenyan men aged 18–35 and their female sex partners aged 16 and older. We assessed BV at ba...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcimb.2020.00433

Integrative multiomics analysis of platelet-related genes unveils molecular subtypes and prognostic signatures in acute myeloid leukemia

Fangmin Zhong, Fangyi Yao, Zihao Wang, Bo Huang et al. • npj Precision Oncology (2025)

Abstract Acute myeloid leukemia (AML) remains challenging due to molecular heterogeneity and limited prognostic models integrating tumor microenvironment dynamics. While thrombocytopenia correlates with poor outcomes, the roles of platelet-...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41698-025-01137-8

Increased Atmospheric Aridity and Reduced Precipitation Drive the 2023 Extreme Wildfire Season in Canada

Gengke Lai, Yongguang Zhang • Geophysical Research Letters (2025)

Abstract Canada experienced an unprecedented wildfire season in 2023. Here, we analyzed the exceptional scale, dominant driving factors, and potential impacts on permafrost of these wildfires using Moderate Resolution Imaging Spectroradiome...

DOAJ Open Access (DOAJ) DOI: 10.1029/2024GL114492