{"id":5244,"date":"2023-09-07T13:18:46","date_gmt":"2023-09-07T11:18:46","guid":{"rendered":"https:\/\/bsicos-dev.i3a.es\/?p=5244"},"modified":"2025-09-10T12:50:21","modified_gmt":"2025-09-10T10:50:21","slug":"julia-ramirez-garcia","status":"publish","type":"post","link":"https:\/\/bsicos.i3a.es\/es\/julia-ramirez-garcia\/","title":{"rendered":"Julia Ram\u00edrez Garc\u00eda"},"content":{"rendered":"
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    Investigadores<\/a><\/h3>\n

    Julia Ram\u00edrez Garc\u00eda<\/strong><\/h1>\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/li>\n\t\t<\/ul>\t\t\t\t
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      Faculty Member<\/p>\n

      Tel\u00e9fono:<\/strong> Ext: 842360<\/p>\n

      Email:<\/strong> julia.ramirez@unizar.es<\/p>\n

      Address:<\/strong> Campus R\u00edo Ebro, Edificio Ada Byron, Despacho 2.04 – 50018 Zaragoza (Spain)<\/p><\/blockquote>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>\n\n

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      Julia Ram\u00edrez is an Associate Professor at the University of Zaragoza, Spain, and holds an honorary lectureship in Cardiovascular Data Science at Queen Mary University of London, United Kingdom. Julia received a Ph.D. in Biomedical Engineering from the University of Zaragoza in 2017. The main objective of her PhD was to extract information from the electrocardiogram (ECG) to non-invasively quantify cardiovascular risk. She, then, moved to Queen Mary University of London to investigate the genetics of ECG markers and their role in assessing cardiovascular risk. In January 2022, she returned to the University of Zaragoza thanks to the Mar\u00eda Zambrano Scheme for Attracting International Talent, and in 2023 she became a ‘Ram\u00f3n y Cajal’ Fellow. Her research has been funded by the regional Government of Arag\u00f3n, the Spanish Ministry of Science, the UK Medical Research Council, the British Heart Foundation and the European Commission.<\/p>\n<\/div>\n<\/div><\/div><\/div><\/div><\/div>

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      93 registros<\/span> «<\/a> ‹<\/a> 1 de 4 ›<\/a> »<\/a> <\/div><\/div>

      2026<\/h3>

      Art\u00edculos de revista<\/h3>

      Naderi, H; Kaplan, T; van Duijvenboden, S; Ruiz, E; Aung, N; Chahal, C A; Lekadir, K; Chamling, B; D\u00f6rr, M; Markus, M R P; Petersen, S E; Ram\u00edrez, J; Munroe, P B<\/p>

      Deep learning to predict left ventricular hypertrophy from the electrocardiogra<\/a> Art\u00edculo de revista<\/span> <\/p>

      En: <\/span>EP Europace, <\/span>2026<\/span>.<\/p>

      Enlaces<\/a><\/span> | BibTeX<\/a><\/span><\/p>

      @article{Naderi26,
      \r\ntitle = {Deep learning to predict left ventricular hypertrophy from the electrocardiogra},
      \r\nauthor = {H Naderi and T Kaplan and S {van Duijvenboden} and E Ruiz and N Aung and C A Chahal and K Lekadir and B Chamling and M D\u00f6rr and M R P Markus and S E Petersen and J Ram\u00edrez and P B Munroe},
      \r\nurl = {https:\/\/drive.google.com\/file\/d\/1ZQyqcKkxkRmTYMe4OxzrsivDCxc8ibug\/view},
      \r\nyear  = {2026},
      \r\ndate = {2026-01-01},
      \r\njournal = {EP Europace},
      \r\nkeywords = {},
      \r\npubstate = {published},
      \r\ntppubtype = {article}
      \r\n}
      \r\n<\/pre><\/div>
      Cerrar<\/a><\/p><\/div>