Harminder Singh, J. Goldman, Luc Mottin, Jamil Zaghir, Daniel Keszthelyi, Belinda Lokaj, H. Turbé, Patrick Ruch, Julien Ehrsam, Christian, Lovis, Julien Gobeil, Pablo Ferri, C. Sáez, Antonio Felix de Castro, -. PurificaciónSánchez, Cuesta, J. M. García-Gómez, C. Faviez, Marc Vincent, N. Garcelon, C. Michot, G. Baujat, V. Cormier-Daire, S. Saunier, Xiaoyi, Chen, A. Burgun, Gıyaseddin, Bayrak, M. Toprak, Ural Ko, Thierry Hamon, N. Grabar, L. Mosch, S. Klopfenstein, Maximilian Markus, Wunderlich, Nicolas Frey, F. Balzer, E. Ford, Kathryn Stanley, -. MelanieRees, Roberts, Sarah Giles, Katie Goddard, J. Armes, Gunnar, Ellingsen, M. Lussier, Ian Zenleae, Robert, Kyba, W. Thomas, C. Chronaki, P. Hurlen, G. Cangioli, Jens Kristian Villandsen, Giovanna Maria Ferarri, C. Anderson, A. Islind, M. Óskarsdóttir
{"title":"Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022, Medical Informatics Europe, Nice, France, May 27-30, 2022","authors":"Harminder Singh, J. Goldman, Luc Mottin, Jamil Zaghir, Daniel Keszthelyi, Belinda Lokaj, H. Turbé, Patrick Ruch, Julien Ehrsam, Christian, Lovis, Julien Gobeil, Pablo Ferri, C. Sáez, Antonio Felix de Castro, -. PurificaciónSánchez, Cuesta, J. M. García-Gómez, C. Faviez, Marc Vincent, N. Garcelon, C. Michot, G. Baujat, V. Cormier-Daire, S. Saunier, Xiaoyi, Chen, A. Burgun, Gıyaseddin, Bayrak, M. Toprak, Ural Ko, Thierry Hamon, N. Grabar, L. Mosch, S. Klopfenstein, Maximilian Markus, Wunderlich, Nicolas Frey, F. Balzer, E. Ford, Kathryn Stanley, -. MelanieRees, Roberts, Sarah Giles, Katie Goddard, J. Armes, Gunnar, Ellingsen, M. Lussier, Ian Zenleae, Robert, Kyba, W. Thomas, C. Chronaki, P. Hurlen, G. Cangioli, Jens Kristian Villandsen, Giovanna Maria Ferarri, C. Anderson, A. Islind, M. Óskarsdóttir","doi":"10.3233/shti294","DOIUrl":null,"url":null,"abstract":"The proceedings contain 250 papers. The topics discussed include: applying machine learning to arsenic species and metallomics profiles of toenails to evaluate associations of environmental arsenic with incident cancer cases;user satisfaction with an AI system for chest X-ray analysis implemented in a hospital’s emergency setting;scaling AI projects for radiology – causes and consequences;ECG classification using combination of linear and non-linear features with neural network;dataset comparison tool: utility and privacy;when context matters for credible measurement of drug-drug interactions based on real-world data;a lightweight and interpretable model to classify bundle branch blocks from ECG signals;analysis of stroke assistance in Covid-19 pandemic by process mining techniques;automated diagnosis of autism spectrum disorder condition using shape based features extracted from brainstem;using explainable supervised machine learning to predict burnout in healthcare professionals;and an image based object recognition system for wound detection and classification of diabetic foot and venous leg ulcers.","PeriodicalId":125683,"journal":{"name":"Medical Informatics Europe","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Informatics Europe","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3233/shti294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The proceedings contain 250 papers. The topics discussed include: applying machine learning to arsenic species and metallomics profiles of toenails to evaluate associations of environmental arsenic with incident cancer cases;user satisfaction with an AI system for chest X-ray analysis implemented in a hospital’s emergency setting;scaling AI projects for radiology – causes and consequences;ECG classification using combination of linear and non-linear features with neural network;dataset comparison tool: utility and privacy;when context matters for credible measurement of drug-drug interactions based on real-world data;a lightweight and interpretable model to classify bundle branch blocks from ECG signals;analysis of stroke assistance in Covid-19 pandemic by process mining techniques;automated diagnosis of autism spectrum disorder condition using shape based features extracted from brainstem;using explainable supervised machine learning to predict burnout in healthcare professionals;and an image based object recognition system for wound detection and classification of diabetic foot and venous leg ulcers.
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