{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T11:04:59Z","timestamp":1787915099322,"version":"build-2784847793"},"reference-count":211,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2018,6,1]],"date-time":"2018-06-01T00:00:00Z","timestamp":1527811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2018,6]]},"DOI":"10.1109\/tnnls.2018.2790388","type":"journal-article","created":{"date-parts":[[2018,1,31]],"date-time":"2018-01-31T19:19:07Z","timestamp":1517426347000},"page":"2063-2079","source":"Crossref","is-referenced-by-count":759,"title":["Applications of Deep Learning and Reinforcement Learning to Biological Data"],"prefix":"10.1109","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2037-8348","authenticated-orcid":false,"given":"Mufti","family":"Mahmud","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4604-5461","authenticated-orcid":false,"given":"Mohammed Shamim","family":"Kaiser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8080-082X","authenticated-orcid":false,"given":"Amir","family":"Hussain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefano","family":"Vassanelli","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref170","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2016.10.008"},{"key":"ref172","first-page":"2620","article-title":"On the use of convolutional neural networks and augmented CSP features for multi-class motor imagery of EEG signals classification","author":"yang","year":"2015","journal-title":"Proc EMBC"},{"key":"ref171","doi-asserted-by":"publisher","DOI":"10.1109\/APWC-on-CSE.2016.017"},{"key":"ref174","doi-asserted-by":"publisher","DOI":"10.1109\/EUSIPCO.2015.7362882"},{"key":"ref173","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/14\/1\/016003"},{"key":"ref176","first-page":"493","article-title":"Prediction of driver’s drowsy and alert states from eeg signals with deep learning","author":"hajinoroozi","year":"2015","journal-title":"Proc IEEE CAMSAP"},{"key":"ref175","first-page":"4746","article-title":"Using deep and convolutional neural networks for accurate emotion classification on DEAP dataset","author":"tripathi","year":"2017","journal-title":"Proc IAAI"},{"key":"ref178","doi-asserted-by":"publisher","DOI":"10.1109\/ICME.2014.6890301"},{"key":"ref177","doi-asserted-by":"publisher","DOI":"10.1016\/j.clinph.2009.09.002"},{"key":"ref168","doi-asserted-by":"publisher","DOI":"10.1155\/2012\/107046"},{"key":"ref169","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2017.00103"},{"key":"ref39","article-title":"Deep reinforcement learning: An overview","volume":"abs 1701 7274","author":"li","year":"2017","journal-title":"CoRR"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1287\/ijoc.1080.0305"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2016.2636665"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1038\/nature14236"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2016.00248"},{"key":"ref37","first-page":"17","article-title":"Reinforcement learning: An overview","author":"glorennec","year":"2000","journal-title":"Proc ESIT"},{"key":"ref36","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1613\/jair.301","article-title":"Reinforcement learning: A survey","volume":"4","author":"kaelbling","year":"1996","journal-title":"J Artif Intell Res"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbw068"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1021\/acs.molpharmaceut.5b00982"},{"key":"ref181","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2007.893452"},{"key":"ref180","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(99)00126-5"},{"key":"ref185","doi-asserted-by":"publisher","DOI":"10.1109\/IWW-BCI.2016.7457459"},{"key":"ref184","doi-asserted-by":"publisher","DOI":"10.3389\/fnbot.2016.00009"},{"key":"ref183","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2015.00036"},{"key":"ref182","doi-asserted-by":"publisher","DOI":"10.1145\/2557500.2557533"},{"key":"ref189","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2016.01.082"},{"key":"ref188","doi-asserted-by":"publisher","DOI":"10.1142\/S1469026816500218"},{"key":"ref187","doi-asserted-by":"publisher","DOI":"10.1109\/BSN.2015.7299399"},{"key":"ref186","doi-asserted-by":"publisher","DOI":"10.1109\/CSE.2014.36"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1148\/rg.2017160130"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1038\/icb.2017.16"},{"key":"ref179","article-title":"Learning representations from EEG with deep recurrent-convolutional neural networks","author":"bashivan","year":"2016","journal-title":"CoRR"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1162\/NECO_a_00089"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/0004-3702(89)90049-0"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/BF00337288"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1111\/j.2517-6161.1977.tb01600.x","article-title":"Maximum likelihood from incomplete data via the EM algorithm","volume":"39","author":"dempster","year":"1977","journal-title":"J Roy Statist Soc B Statist Methodol"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1080\/01969727308546046"},{"key":"ref23","article-title":"ISODATA, a novel method of data analysis and pattern classification","author":"ball","year":"1965"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/nrg3920"},{"key":"ref25","author":"hartigan","year":"1975","journal-title":"Clustering Algorithms"},{"key":"ref50","first-page":"255","article-title":"Convolutional networks for images, speech, and time series","author":"lecun","year":"1998","journal-title":"The Handbook of Brain Theory and Neural Networks"},{"key":"ref51","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc NIPS"},{"key":"ref154","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.07.007"},{"key":"ref153","doi-asserted-by":"publisher","DOI":"10.1016\/j.compmedimag.2016.07.004"},{"key":"ref156","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.08.008"},{"key":"ref155","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.01.009"},{"key":"ref150","doi-asserted-by":"publisher","DOI":"10.1109\/BioCAS.2015.7348440"},{"key":"ref152","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.02.060"},{"key":"ref151","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2015.12.014"},{"key":"ref146","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2015.2425041"},{"key":"ref147","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2535865"},{"key":"ref148","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2535865"},{"key":"ref149","doi-asserted-by":"publisher","DOI":"10.1109\/ROBIO.2015.7419037"},{"key":"ref59","first-page":"448","article-title":"Deep Boltzmann machines","author":"salakhutdinov","year":"2009","journal-title":"Proc AISTATS"},{"key":"ref58","first-page":"833","article-title":"Contractive auto-encoders: Explicit invariance during feature extraction","author":"rifai","year":"2011","journal-title":"Proc ICML"},{"key":"ref57","article-title":"Auto-encoding variational Bayes","volume":"abs 1312 6114","author":"kingma","year":"2014","journal-title":"CoRR"},{"key":"ref56","first-page":"1137","article-title":"Efficient learning of sparse representations with an energy-based model","author":"ranzato","year":"2006","journal-title":"Proc NIPS"},{"key":"ref55","first-page":"37","article-title":"Autoencoders, unsupervised learning and deep architectures","author":"baldi","year":"2012","journal-title":"Proc ICUTLW"},{"key":"ref54","first-page":"3371","article-title":"Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion","volume":"11","author":"vincent","year":"2010","journal-title":"J Mach Learn Res"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298594"},{"key":"ref52","article-title":"Very deep convolutional networks for large-scale image recognition","volume":"abs 1409 1556","author":"simonyan","year":"2015","journal-title":"CoRR"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1561\/2200000006"},{"key":"ref167","first-page":"340","article-title":"Deep learning in the EEG diagnosis of Alzheimer’s disease","author":"zhao","year":"2015","journal-title":"Proc ACCV"},{"key":"ref166","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/8\/3\/036015"},{"key":"ref165","doi-asserted-by":"publisher","DOI":"10.1109\/TAMD.2015.2431497"},{"key":"ref164","doi-asserted-by":"publisher","DOI":"10.1109\/BIBE.2014.26"},{"key":"ref163","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM.2013.6732507"},{"key":"ref162","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-09330-7_25"},{"key":"ref161","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2016.2601240"},{"key":"ref160","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/627892"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1038\/nbt1486"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1126\/science.1232919"},{"key":"ref6","author":"vadivambal","year":"2016","journal-title":"Bio-Imaging Principles Techniques and Applications"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1038\/nrg2626"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1152\/physrev.00027.2016"},{"key":"ref159","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-12637-1_63"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1038\/nature15692"},{"key":"ref49","article-title":"A mathematical theory of deep convolutional neural networks for feature extraction","volume":"abs 1512 6293","author":"wiatowski","year":"2015","journal-title":"CoRR"},{"key":"ref157","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2017.05.001"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1038\/498255a"},{"key":"ref158","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2342-8-8"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/78.650093"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref47","article-title":"A critical review of recurrent neural networks for sequence learning","volume":"abs 1506 19","author":"lipton","year":"2015","journal-title":"CoRR"},{"key":"ref42","article-title":"Exact solutions to the nonlinear dynamics of learning in deep linear neural networks","volume":"abs 1312 6120","author":"saxe","year":"2014","journal-title":"CoRR"},{"key":"ref41","author":"goodfellow","year":"2016","journal-title":"Deep Learning"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1016\/0364-0213(90)90002-E"},{"key":"ref43","first-page":"1","article-title":"How to construct deep recurrent neural networks","author":"pascanu","year":"2014","journal-title":"Proc ICLR"},{"key":"ref73","article-title":"Deep reinforcement learning with double Q-learning","volume":"abs 1509 6461","author":"van hasselt","year":"2015","journal-title":"CoRR"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7298640"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.4249\/scholarpedia.1448"},{"key":"ref70","first-page":"1312","article-title":"Universal value function approximators","author":"schaul","year":"2015","journal-title":"Proc ICML"},{"key":"ref76","article-title":"Using deep learning to enhance cancer diagnosis and classification","author":"fakoor","year":"2013","journal-title":"Proc ICML"},{"key":"ref77","first-page":"219","article-title":"A deep learning approach for cancer detection and relevant gene identification","volume":"22","author":"danaee","year":"2016","journal-title":"Proc Pacific Symp Biocomput"},{"key":"ref74","first-page":"2613","article-title":"Double Q-learning","author":"hasselt","year":"2010","journal-title":"Proc NIPS"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1007\/s10278-017-9965-6"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.4172\/jpb.1000419"},{"key":"ref79","first-page":"2483","article-title":"Boosted categorical restricted Boltzmann machine for computational prediction of splice junctions","author":"lee","year":"2015","journal-title":"Proc ICML"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.1984.4767596"},{"key":"ref62","article-title":"On training deep Boltzmann machines","volume":"abs 1203 4416","author":"desjardins","year":"2012","journal-title":"CoRR"},{"key":"ref61","first-page":"14","article-title":"An introduction to restricted Boltzmann machines","author":"fischer","year":"2012","journal-title":"Proc CIARP"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1145\/1390156.1390290"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2015.09.116"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1162\/neco.2006.18.7.1527"},{"key":"ref66","author":"sutton","year":"1998","journal-title":"Reinforcement Learning An Introduction"},{"key":"ref67","doi-asserted-by":"crossref","DOI":"10.1017\/9781108164085","author":"poole","year":"2017","journal-title":"Artificial Intelligence Foundations of Computational Agents"},{"key":"ref68","doi-asserted-by":"crossref","DOI":"10.1201\/9781439821091","author":"busoniu","year":"2010","journal-title":"Reinforcement Learning and Dynamic Programming Using Function Approximators"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553501"},{"key":"ref197","doi-asserted-by":"publisher","DOI":"10.1007\/s12559-016-9404-x"},{"key":"ref198","first-page":"1","article-title":"Hierarchical convolutional neural networks for EEG-based emotion recognition","author":"li","year":"2017","journal-title":"Cognit Comput"},{"key":"ref199","doi-asserted-by":"publisher","DOI":"10.1038\/nature12311"},{"key":"ref193","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2560\/10\/6\/066005"},{"key":"ref194","doi-asserted-by":"publisher","DOI":"10.4028\/www.scientific.net\/AMM.461.565"},{"key":"ref195","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0087253"},{"key":"ref196","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2015.2493079"},{"key":"ref95","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btw255"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1101\/gr.200535.115"},{"key":"ref190","doi-asserted-by":"publisher","DOI":"10.1109\/TBME.2008.926699"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.3300"},{"key":"ref191","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0014760"},{"key":"ref92","first-page":"1","article-title":"Deep modeling of gene expression regulation in erythropoiesis model","author":"denas","year":"2013","journal-title":"Proc of the ICML"},{"key":"ref192","doi-asserted-by":"publisher","DOI":"10.1109\/NER.2011.5910601"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1002\/minf.201600045"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-016-1334-9"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1038\/srep18962"},{"key":"ref99","article-title":"deepMiRGene: Deep neural network based precursor microrna prediction","volume":"abs 1605 17","author":"park","year":"2016","journal-title":"CoRR"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.3547"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1038\/ng.3810"},{"key":"ref82","doi-asserted-by":"publisher","DOI":"10.1186\/s12859-017-1561-8"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btv315"},{"key":"ref84","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkv1025"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btw074"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1109\/EMBC.2014.6944490"},{"key":"ref89","first-page":"86033","article-title":"Deep learning with feature embedding for compound-protein interaction prediction","author":"wan","year":"2016","journal-title":"BioRxiv"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-017-1189-z"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btu703"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1038\/srep11476"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymeth.2016.06.024"},{"key":"ref200","first-page":"3133","article-title":"Do we need hundreds of classifiers to solve real world classification problems?","volume":"15","author":"fern\u00e1ndez-delgado","year":"2014","journal-title":"J Mach Learn Res"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1109\/TAAI.2010.65"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1145\/2975167.2975212"},{"key":"ref209","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2014.00026"},{"key":"ref203","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2014.2377694"},{"key":"ref204","doi-asserted-by":"publisher","DOI":"10.1186\/1532-429X-18-S1-P351"},{"key":"ref201","doi-asserted-by":"publisher","DOI":"10.1038\/nmeth.2016"},{"key":"ref202","doi-asserted-by":"publisher","DOI":"10.1038\/nbt.2486"},{"key":"ref207","article-title":"Intriguing properties of neural networks","volume":"abs 1312 6199","author":"szegedy","year":"2014","journal-title":"CoRR"},{"key":"ref208","doi-asserted-by":"publisher","DOI":"10.1515\/bmt-2012-4412"},{"key":"ref205","doi-asserted-by":"publisher","DOI":"10.1109\/ICPR.2010.579"},{"key":"ref206","article-title":"Understanding representations learned in deep architectures","author":"erhan","year":"2010"},{"key":"ref211","first-page":"489","article-title":"Challenges in deep learning","author":"angelov","year":"2016","journal-title":"Proc ESANN"},{"key":"ref210","first-page":"202","article-title":"A Web-based framework for semi-online parallel processing of extracellular neuronal signals recorded by microelectrode arrays","author":"mahmud","year":"2014","journal-title":"Proc MEA Meeting"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2016.01.024"},{"key":"ref126","article-title":"Alzheimer’s disease diagnostics by a deeply supervised adaptable 3D convolutional network","volume":"abs 1607 556","author":"hosseini-asl","year":"2016","journal-title":"CoRR"},{"key":"ref125","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-50478-0_6"},{"key":"ref124","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2017.2655720"},{"key":"ref129","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46723-8_25"},{"key":"ref128","first-page":"70441","article-title":"DeepAD: Alzheimer’s disease classification via deep convolutional neural networks using MRI and fMRI","author":"sarraf","year":"2016","journal-title":"BioRxiv"},{"key":"ref130","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.10.004"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2015.03.017"},{"key":"ref134","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46723-8_19"},{"key":"ref131","first-page":"2998","article-title":"Parallel multi-dimensional LSTM, with application to fast biomedical volumetric image segmentation","author":"stollenga","year":"2015","journal-title":"Proc NIPS"},{"key":"ref132","first-page":"1493","article-title":"Adaptive multi-column deep neural networks with application to robust image denoising","author":"agostinelli","year":"2013","journal-title":"Proc NIPS"},{"key":"ref136","article-title":"Medical image deep learning with hospital PACS dataset","volume":"abs 1511 6348","author":"cho","year":"2015","journal-title":"CoRR"},{"key":"ref135","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2016.10.007"},{"key":"ref138","doi-asserted-by":"publisher","DOI":"10.1038\/srep24454"},{"key":"ref137","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2482920"},{"key":"ref139","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2528162"},{"key":"ref140","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.05.029"},{"key":"ref141","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.09.029"},{"key":"ref142","doi-asserted-by":"publisher","DOI":"10.1109\/CCBD.2014.42"},{"key":"ref143","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0137036"},{"key":"ref2","author":"magner","year":"2002","journal-title":"A History of the Life Sciences"},{"key":"ref144","doi-asserted-by":"publisher","DOI":"10.1109\/ICDMW.2016.0041"},{"key":"ref1","author":"coleman","year":"1977","journal-title":"Biology in the Nineteenth Century Problems of Form Function and Transformatoin"},{"key":"ref145","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.05.009"},{"key":"ref109","first-page":"411","article-title":"Mitosis detection in breast cancer histology images with deep neural networks","author":"cire?an","year":"2013","journal-title":"Proc MICCAI"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2005.852470"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.1038\/srep21471"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6853873"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2015.2458702"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1109\/BIBM.2014.6999302"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1109\/SYNASC.2011.9"},{"key":"ref102","doi-asserted-by":"publisher","DOI":"10.1109\/SBRN.2010.27"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.1534\/g3.116.033654"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.07.016"},{"key":"ref110","first-page":"2843","article-title":"Deep neural networks segment neuronal membranes in electron microscopy images","author":"cire?an","year":"2012","journal-title":"Proc NIPS"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.gpb.2014.10.001"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1038\/35007262"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.0030116"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/101.8118"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2012.2188013"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-011-5014-9_11"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2016.09.032"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1967.1053964"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40763-5_72"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/MASSP.1986.1165342"},{"key":"ref19","first-page":"267","article-title":"Data mining tasks and methods: Classification: Decision-tree discovery","author":"kohavi","year":"2002","journal-title":"Handbook of Data Mining and Knowledge Discovery"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40763-5_78"},{"key":"ref114","first-page":"81364","article-title":"Deep learning for imaging flow cytometry: Cell cycle analysis of Jurkat cells","author":"eulenberg","year":"2016","journal-title":"BioRxiv"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btw252"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2535222"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1109\/IMCCC.2015.33"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2014.06.077"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2015.2429556"},{"key":"ref122","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2014.00229"},{"key":"ref123","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2016.05.004"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/5962385\/8360119\/08277160.pdf?arnumber=8277160","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,30]],"date-time":"2024-06-30T21:47:39Z","timestamp":1719784059000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8277160\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6]]},"references-count":211,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2018.2790388","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,6]]}}}