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Learning Eligibility in Cancer Clinical Trials Using Deep Neural Networks

Aurelia Bustos, Antonio Pertusa
<span title="2018-07-23">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/smrngspzhzce7dy6ofycrfxbim" style="color: black;">Applied Sciences</a> </i> &nbsp;
The efficacy and safety of new treatments for patients with these characteristics are, therefore, not defined.  ...  A text classifier was trained using deep neural networks, with pre-trained word-embeddings as inputs, to predict whether or not short free-text statements describing clinical information were considered  ...  kNN) are evaluated using word-embeddings for eligibility classification. • Using learned deep representations, CNN and kNN (in this case, with average word-embeddings) obtain a similar accuracy, outperforming  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app8071206">doi:10.3390/app8071206</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/l4myvrgbavbhvn5ld4gzkrjosm">fatcat:l4myvrgbavbhvn5ld4gzkrjosm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190226152005/http://pdfs.semanticscholar.org/6eef/bd5c4a5b2e666277823d6b759bb9d2e92a5b.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6e/ef/6eefbd5c4a5b2e666277823d6b759bb9d2e92a5b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/app8071206"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Machine Learning in Healthcare Communication

Sarkar Siddique, James C. L. Chow
<span title="2021-02-14">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jvcynst6kngf7esdgvf3pcz4ja" style="color: black;">Encyclopedia</a> </i> &nbsp;
Machine learning (ML) is a study of computer algorithms for automation through experience.  ...  While healthcare communication is important in order to tactfully translate and disseminate information to support and educate patients and public, ML is proven applicable in healthcare with the ability  ...  Deep learning can achieve higher accuracy if trained on big data, especially in the medical field. Useful and important information from big data can be extracted with deep learning.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/encyclopedia1010021">doi:10.3390/encyclopedia1010021</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/k4fj32b7mvbbhljpezmsaxljj4">fatcat:k4fj32b7mvbbhljpezmsaxljj4</a> </span>
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Deep Learning applications for COVID-19

Connor Shorten, Taghi M. Khoshgoftaar, Borko Furht
<span title="2021-01-11">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/pkhnkszyprhb3orbf6g7tqmgiu" style="color: black;">Journal of Big Data</a> </i> &nbsp;
We hope that this survey will help accelerate the use of Deep Learning for COVID-19 research.  ...  We begin by evaluating the current state of Deep Learning and conclude with key limitations of Deep Learning for COVID-19 applications.  ...  Acknowledgements We would like to thank the reviewers in the Data Mining and Machine Learning Laboratory at Florida Atlantic University.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40537-020-00392-9">doi:10.1186/s40537-020-00392-9</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33457181">pmid:33457181</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7797891/">pmcid:PMC7797891</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/aokxo63z2rhdpfxo3egyf3xpcm">fatcat:aokxo63z2rhdpfxo3egyf3xpcm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210112151551/https://journalofbigdata.springeropen.com/track/pdf/10.1186/s40537-020-00392-9.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3b/72/3b729b10a5aefd1a2be90a2f9efb03a9673b8e73.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40537-020-00392-9"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7797891" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Deep Learning Methods in the Medical Device Industry: An Overview

Muhammad Mugees Asif, Sana Asif, Iqra Mubarik, Shanza Nasir
<span title="2022-02-28">2022</span> <i title="Zenodo"> Zenodo </i> &nbsp;
As a result, deep learning approaches have gained traction in the medical device business in recent years, with the majority of studies focusing on diagnosis and image processing.  ...  In this study, we conducted a literature evaluation that was separated into classes based on the domains in which deep learning methods are utilized in the medical device business, as well as an examination  ...  Ali et al use ad---83 vanced technologies, data mining, cloud servers, big data, ontologies, and deep learning for chronic patients.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.6305110">doi:10.5281/zenodo.6305110</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kfs7v3gt75dipkb7636ekgf3hi">fatcat:kfs7v3gt75dipkb7636ekgf3hi</a> </span>
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Systematic Review of Privacy-Preserving Distributed Machine Learning From Federated Databases in Health Care

Fadila Zerka, Samir Barakat, Sean Walsh, Marta Bogowicz, Ralph T. H. Leijenaar, Arthur Jochems, Benjamin Miraglio, David Townend, Philippe Lambin
<span title="">2020</span> <i title="American Society of Clinical Oncology (ASCO)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hurdanwnsbhfjohxhgqwcxdlaq" style="color: black;">JCO Clinical Cancer Informatics</a> </i> &nbsp;
, and a definition of machine/deep learning concepts; (2) a presentation of the adopted review protocol; (3) a presentation of the search results; and (4) a discussion of the findings, limitations of the  ...  In other words, one can learn from separate and isolated datasets without patient data ever leaving the individual clinical institutes.  ...  As for machine learning, deep learning can be distributed to protect patient data. 29, 30 Moreover, distributed deep learning also improves computing performance, as in the case of wireless sensor networks  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1200/cci.19.00047">doi:10.1200/cci.19.00047</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32134684">pmid:32134684</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC7113079/">pmcid:PMC7113079</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rgfhzdm5fvetdclrpyyv3gsfty">fatcat:rgfhzdm5fvetdclrpyyv3gsfty</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200501140745/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC7113079&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b1/15/b115154660d6bc50b24654afbc3b467a7a966715.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1200/cci.19.00047"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7113079" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Deep learning meets ontologies: experiments to anchor the cardiovascular disease ontology in the biomedical literature

Mercedes Arguello Casteleiro, George Demetriou, Warren Read, Maria Jesus Fernandez Prieto, Nava Maroto, Diego Maseda Fernandez, Goran Nenadic, Julie Klein, John Keane, Robert Stevens
<span title="2018-04-12">2018</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/iasjcyzzyncgnohh3aitx65bhq" style="color: black;">Journal of Biomedical Semantics</a> </i> &nbsp;
This study investigates: 1) if word embeddings from Deep Learning algorithms can provide a list of term variants for a given gene/protein of interest; and 2) if biological knowledge from the CVDO can improve  ...  Using more than 14 M PubMed articles (titles and available abstracts), word embeddings were generated with CBOW and Skip-gram.  ...  Acknowledgements Thanks to Tim Furmston for help with software and e-infrastructure, and to the anonymous reviewers for their useful comments. Funding  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13326-018-0181-1">doi:10.1186/s13326-018-0181-1</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/29650041">pmid:29650041</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5896136/">pmcid:PMC5896136</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rnyqpxihlralfcs7c5wxa5aaci">fatcat:rnyqpxihlralfcs7c5wxa5aaci</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180721035245/https://jbiomedsem.biomedcentral.com/track/pdf/10.1186/s13326-018-0181-1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/51/7b/517b96933e34d54c65bd2ca0bbd402a14fef95d4.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s13326-018-0181-1"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5896136" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Pharmacovigilant Machine Learning in Big Data? [article]

Benjamin Skov Kaas-Hansen, Stig Ejdrup Andersen, Søren Brunak, Gesche Jürgens
<span title="2022-03-17">2022</span> <i title="Zenodo"> Zenodo </i> &nbsp;
PhD thesis, submitted to the Graduate School of Health and Medical Sciences, University of Copenhagen, on 4 November 2021.  ...  The funders played no role in designing, conducting, interpreting, or reporting this study. Acknowledgements The authors would like to thank DrugBank for granting access to their database.  ...  Acknowledgements The authors would like thank Innovation Fund Denmark (5153-00002B) and the Novo Nordisk Foundation (NNF14CC0001, NNF17OC0027594) for their financial contribution to BigTempHealth without which this study  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.6284793">doi:10.5281/zenodo.6284793</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eelz7gmdqbaffchoqjnayiz27a">fatcat:eelz7gmdqbaffchoqjnayiz27a</a> </span>
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Deep learning-based ambient assisted living for self-management of cardiovascular conditions

Maria Ahmed Qureshi, Kashif Naseer Qureshi, Gwanggil Jeon, Francesco Piccialli
<span title="2021-01-07">2021</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/a3wauupnbbdj7hbo62upc6grdq" style="color: black;">Neural computing &amp; applications (Print)</a> </i> &nbsp;
learning strategies can be used to improve the medical services.  ...  This systematic literature review presents the detailed literature on ambient assisted living solutions and helps to understand how ambient assisted living helps and motivates patients with cardiovascular  ...  proposed a deep learning approach for phenotyping from the patient electronic health record.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00521-020-05678-w">doi:10.1007/s00521-020-05678-w</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/fkabjm33xza2ncgq6ecu2qifaq">fatcat:fkabjm33xza2ncgq6ecu2qifaq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210429072635/https://link.springer.com/content/pdf/10.1007/s00521-020-05678-w.pdf?error=cookies_not_supported&amp;code=f922bffb-9820-4651-9826-50ea41523d03" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/bb/37/bb37b13a6ef9bc78775b90bc0ed5fa67377e7fb2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s00521-020-05678-w"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

Towards deep phenotyping pregnancy: a systematic review on artificial intelligence and machine learning methods to improve pregnancy outcomes

Lena Davidson, Mary Regina Boland
<span title="2021-01-06">2021</span> <i title="Oxford University Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/op7ztx4fhvairowgqifu7dnvsi" style="color: black;">Briefings in Bioinformatics</a> </i> &nbsp;
The purpose of this study is to systematically review the ways that artificial intelligence (AI) and machine learning (ML), including deep learning (DL), methodologies can inform patient care during pregnancy  ...  We searched English articles on EMBASE, PubMed and SCOPUS. Search terms included ML, AI, pregnancy and informatics.  ...  some case studies on this process [146, 147] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/bib/bbaa369">doi:10.1093/bib/bbaa369</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33406530">pmid:33406530</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8424395/">pmcid:PMC8424395</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rgsf4pdmbvdcdmcwz4zf3hwaca">fatcat:rgsf4pdmbvdcdmcwz4zf3hwaca</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210114092516/https://watermark.silverchair.com/bbaa369.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAArMwggKvBgkqhkiG9w0BBwagggKgMIICnAIBADCCApUGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMhfAKyf1EsWJMa9XUAgEQgIICZkkgqm7802LoCZ9EyIthzIxnGaKZaGkCvt6jCQIOrqCYDxyG_1Yi02CYbN1zh9teljR8XxHjXbZSB-95oc-7ygywtblO8e6kZmLs-8o1LrSr3KlUP_JylF7k7Ni5_8zR9jjqJ418qapWeTjdQuq1Ip-OUapSNCQUFOF33Y4B6ujdINFbonuWG1YhWHgyk5UdrZdhPcII4n-18Ms04hSgkBDvCjcBPFB-KiSY6f2ZKh5GGaXK6XNEs8LU6ibjsnKndMhL4iCpqaqHxlA05gD6h4RQcleJVag6xJHrXdg6EtGkuQ1DnUTVjIH120zx-LV4mN6K_Z8-6eSPIaITiGDlCPxRYGF3pQQonHGhVAVkdv9Ri33AMipHJX78V_6VId1Ew9skFH8-9M2ozI2DOEsHJZC2dZolkZMO2EN8m4-mOoMEy9stTTsDbFUZDLvzTHxC5yP65L101RfS48w9nUNSa_3L06AA4_MuYTnzxmP7yAIVQ7Vmo55GJ8jbTByDa7N04RgN3w-mh5PEwr-DXnWb9NUCTPLgWzryS1lpz-VBb87AMoIc08-WvnYxF3vxHDPPu-gkiErFEyUHUYyOTeaRfVHSHn12Cd-JDNfZsnFsw1u56jCoA11jzprCDm9qM6JwtW_Jb1SQTCoCFPjStvgPrb-lUjoqS3RsnaxrbBEnHDbtao__2rMzRAj1tQ8lO5XDklOaeySRlyKTBmSqdniTH51fSHSvySY2aJJiLHxqeDvN6oaLgi9HAYNQgTXh3852q02vd3FuPVNXwD2ZMFTmCfqSo3w8aaLQGp4skuiVqKbFwDbqnhB_" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/09/45/094502960784a24de8d30bffe35a21eecc935ee2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1093/bib/bbaa369"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> oup.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8424395" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Machine Learning Techniques for Biomedical Natural Language Processing: A comprehensive Review

Essam H. Houssein, Rehab E. Mohamed, Abdelmgeid A. Ali
<span title="">2021</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
Moreover, this review summarizes the utilizing of Deep Learning and Machine Learning techniques in biomedical NLP tasks based on chronic diseases related EHR data.  ...  We review some of the biomedical NLP methods and systems used over EHRs and give an overview of machine learning and deep learning methodologies used to process EHRs and improve the understanding of the  ...  Processing EHRs using machine learning and deep learning methods contributes to a better and more deep understanding of clinical patient trajectories which track the patient status from one health state  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3119621">doi:10.1109/access.2021.3119621</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pl7h35nvqngk3gxpbdxvrgzg2u">fatcat:pl7h35nvqngk3gxpbdxvrgzg2u</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20211017141508/https://ieeexplore.ieee.org/ielx7/6287639/6514899/09568778.pdf?tp=&amp;arnumber=9568778&amp;isnumber=6514899&amp;ref=" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fd/49/fd49ab6e165848f55b9dea4ceb66699f4b555349.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2021.3119621"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Prototyping a precision oncology 3.0 rapid learning platform

Connor Sweetnam, Simone Mocellin, Michael Krauthammer, Nathaniel Knopf, Robert Baertsch, Jeff Shrager
<span title="2018-09-26">2018</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/n5zrklrhlzhtdorf4rk4rmeo3i" style="color: black;">BMC Bioinformatics</a> </i> &nbsp;
We describe a prototype implementation of a platform that could underlie a Precision Oncology Rapid Learning system.  ...  Conclusions: The design choices made in this implementation rest upon ten constitutive hypotheses, which, taken together, define a particular view of how a rapid learning medical platform might be defined  ...  Lucy Suchman provided very useful pointers to the sociological literature. The TrEx statistical code was modelled after Vlod Kalicun's Ruby implementation of the Mocellin et al.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s12859-018-2374-0">doi:10.1186/s12859-018-2374-0</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nujcim7ptne6rgwodrxwdiutxu">fatcat:nujcim7ptne6rgwodrxwdiutxu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191121192901/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC6158802&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a6/fc/a6fcb214be2711b5cce34a4f462b5f8cd57db68e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s12859-018-2374-0"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

Human and machine learning of prognostic prediction for prelabor rupture of membranes and the time of delivery: a nationwide development, validation, and deployment using medical history [article]

Herdiantri Sufriyana, Yu-Wei Wu, Emily Chia-Yu Su
<span title="2021-06-22">2021</span> <i title="Cold Spring Harbor Laboratory"> medRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
We compared a statistical model, machine learning algorithms, and a deep-insight visible neural network (DI-VNN) for PROM and estimating the time of delivery.  ...  DI-VNN outperformed previous models by an external validation set, including one using a biomarker (AUROC 0.641; n=1,177).  ...  given the same specificity may be interpreted as a potential improvement in safety of a patient with PROM, including that in low-resource setting.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2021.06.16.21258884">doi:10.1101/2021.06.16.21258884</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/eda3elt7s5bstbqq2an6h5myfe">fatcat:eda3elt7s5bstbqq2an6h5myfe</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210716194710/https://www.medrxiv.org/content/medrxiv/early/2021/06/22/2021.06.16.21258884.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c4/07/c40778646dc047e63b52a6c0e59cc9da3ae41c5e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2021.06.16.21258884"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> medrxiv.org </button> </a>

Evaluation of Methods for Protein Representation Learning: A Quantitative Analysis [article]

Serbulent Unsal, Heval Atas, Muammer Albayrak, Kemal Turhan, Aybar C. Acar, Tunca Dogan
<span title="2020-10-28">2020</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Data representation learning methods do this by training and using a model that employs statistical and machine/deep learning algorithms.  ...  We believe the conclusions of this study will help researchers in applying machine/deep learning-based representation techniques on protein data for various types of predictive tasks.  ...  We thank Dr Gizem Tatar (faculty member, KTU, Turkey) for reading and commenting on the manuscript, and to Gülbahar Merve Çakmak Şılbır (PhD Candidate, KTU, Turkey) for contributing to the drawing of figures  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2020.10.28.359828">doi:10.1101/2020.10.28.359828</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/os54u5navjhzbgi3jux6qnoouu">fatcat:os54u5navjhzbgi3jux6qnoouu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201214055812/https://www.biorxiv.org/content/biorxiv/early/2020/10/28/2020.10.28.359828.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/6b/5d/6b5de3ae7b2f96ca6d44e375c4759c7a13743088.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2020.10.28.359828"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Deep Learning in Science [article]

Stefano Bianchini, Moritz Müller, Pierre Pelletier
<span title="2020-09-04">2020</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Much of the recent success of Artificial Intelligence (AI) has been spurred on by impressive achievements within a broader family of machine learning methods, commonly referred to as Deep Learning (DL)  ...  These search terms allow us to retrieve DL-related publications from Web of Science across all sciences. Based on that sample, we document the DL diffusion process in the scientific system.  ...  Trends in deep learning research "Deep learning, as it is primarily used, is essentially a statistical technique for classifying patterns, based on sample data, using neural networks with multiple layers  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.01575v2">arXiv:2009.01575v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4ttqgjdjfjbydp7flnhcgg5p7m">fatcat:4ttqgjdjfjbydp7flnhcgg5p7m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200916153406/https://arxiv.org/pdf/2009.01575v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2009.01575v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain [article]

Milad Moradi, Matthias Samwald
<span title="2022-03-07">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Deep learning methods are then described in Section 2.  ...  We narrow down the focus of the study on textual data in Section 3, where natural language processing and its applications in the biomedical domain are described.  ...  Training of a RBM starts with a random state in one layer, then the Gibbs sampler is used to generate data from the RBM.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2202.12678v2">arXiv:2202.12678v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/4nv42mbpuveb7euxkr4b6ojuxi">fatcat:4nv42mbpuveb7euxkr4b6ojuxi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220311091202/https://arxiv.org/ftp/arxiv/papers/2202/2202.12678.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/06/ef/06ef1f9e1a760df942548ab38ea7e49e6145c6bd.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2202.12678v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>
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