{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,18]],"date-time":"2026-01-18T13:04:51Z","timestamp":1768741491232,"version":"3.49.0"},"reference-count":36,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,12,5]],"date-time":"2021-12-05T00:00:00Z","timestamp":1638662400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,5]]},"DOI":"10.1109\/ssci50451.2021.9660190","type":"proceedings-article","created":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T21:09:51Z","timestamp":1643058591000},"page":"1-8","source":"Crossref","is-referenced-by-count":4,"title":["Chest X-Rays Image Classification from $\\beta{-}$ Variational Autoencoders Latent Features"],"prefix":"10.1109","author":[{"given":"Leonardo","family":"Crespi","sequence":"first","affiliation":[]},{"given":"Daniele","family":"Loiacono","sequence":"additional","affiliation":[]},{"given":"Arturo","family":"Chiti","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref33","author":"chollet","year":"2015","journal-title":"Keras"},{"key":"ref32","author":"abadi","year":"2015","journal-title":"TensorFlow Large-Scale Machine Learning on Heterogeneous Systems"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(05)80023-1"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1097\/JTO.0b013e3181ec173d"},{"key":"ref35","first-page":"2825","article-title":"Scikit-learn: Machine learning in Python","volume":"12","author":"pedregosa","year":"2011","journal-title":"Journal of Machine Learning Research"},{"key":"ref34","author":"kingma","year":"2017","journal-title":"Adam A method for stochastic optimization"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.369"},{"key":"ref11","author":"rajpurkar","year":"2017","journal-title":"CheXNet Radiologist-level pneumonia detection on chest X-rays with deep learning"},{"key":"ref12","author":"huang","year":"2016","journal-title":"Densely Connected Convolutional Networks"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.1002686"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-93000-8_62"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2020.3024708"},{"key":"ref16","author":"ye","year":"2020","journal-title":"Weakly supervised lesion localization with probabilistic-cam pooling"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01228-7"},{"key":"ref18","author":"rubin","year":"2018","journal-title":"Large scale automated reading of frontal and lateral chest X-rays using dual convolutional neural networks"},{"key":"ref19","article-title":"Chexpert: A large chest radiograph dataset with uncertainty labels and expert comparison","author":"irvin","year":"1901","journal-title":"CoRR"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-006-6226-1"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JBHI.2016.2636665"},{"key":"ref27","first-page":"1189","article-title":"Greedy function approximation: A gradient boosting machine","volume":"29","author":"friedman","year":"2000","journal-title":"Annals of Statistics"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2016.2553401"},{"key":"ref6","author":"irvin","year":"2019","journal-title":"CheXpert A large chest radiograph dataset with uncertainty labels and expert comparison"},{"key":"ref29","first-page":"4923","article-title":"K-nearest neighbors: From global to local","author":"anava","year":"2016","journal-title":"Proceedings of the 30th International Conference on Neural Information Processing Systems ser NIPS'16"},{"key":"ref5","author":"giacomello","year":"2021","journal-title":"Image embedding and model ensembling for automated chest x-ray interpretation"},{"key":"ref8","author":"pham","year":"2019","journal-title":"Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels"},{"key":"ref7","author":"group","year":"0","journal-title":"Chexpert competition"},{"key":"ref2","author":"simonyan","year":"2014","journal-title":"Very Deep Convolutional Networks for Large-scale Image Recognition"},{"key":"ref9","author":"johnson","year":"2019","journal-title":"MIMIC-CXR-JPG a large publicly available database of labeled chest radiographs"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"ref20","author":"pham","year":"2020","journal-title":"Interpreting chest X-rays via CNNs that exploit hierarchical disease dependencies and uncertainty labels"},{"key":"ref22","article-title":"beta-vae: Learning basic visual concepts with a constrained variational framework","author":"higgins","year":"0","journal-title":"ICLR 2017"},{"key":"ref21","author":"szegedy","year":"2015","journal-title":"Rethinking the inception architecture for computer vision"},{"key":"ref24","author":"chollet","year":"2017","journal-title":"Xception Deep learning with depthwise separable convolutions"},{"key":"ref23","author":"huang","year":"2018","journal-title":"Densely Connected Convolutional Networks"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"278","DOI":"10.1109\/ICDAR.1995.598994","article-title":"Random decision forests","volume":"1","author":"ho","year":"1995","journal-title":"Proceedings of 3rd International Conference on Document Analysis and Recognition"},{"key":"ref25","author":"szegedy","year":"2016","journal-title":"Inception-v4 inception-resnet and the impact of residual connections on learning"}],"event":{"name":"2021 IEEE Symposium Series on Computational Intelligence (SSCI)","location":"Orlando, FL, USA","start":{"date-parts":[[2021,12,5]]},"end":{"date-parts":[[2021,12,7]]}},"container-title":["2021 IEEE Symposium Series on Computational Intelligence (SSCI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9659537\/9659538\/09660190.pdf?arnumber=9660190","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T16:56:30Z","timestamp":1652201790000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9660190\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,5]]},"references-count":36,"URL":"https:\/\/doi.org\/10.1109\/ssci50451.2021.9660190","relation":{},"subject":[],"published":{"date-parts":[[2021,12,5]]}}}