<?xml version="1.0" encoding="UTF-8"?>
<references>
<reference>
  <a1>Luongo, Giorgio</a1>
  <a2>Azzolin, Luca</a2>
  <a2>Schuler, Steffen</a2>
  <a2>Rivolta, Massimo W.</a2>
  <a2>Almeida, Tiago P.</a2>
  <a2>Martínez, Juan P.</a2>
  <a2>Soriano, Diogo C.</a2>
  <a2>Luik, Armin</a2>
  <a2>Müller-Edenborn, Björn</a2>
  <a2>Jadidi, Amir</a2>
  <a2>Dössel, Olaf</a2>
  <a2>Sassi, Roberto</a2>
  <a2>Laguna, Pablo</a2>
  <a2>Loewe, Axel</a2>
  <t1>Machine learning enables noninvasive prediction of atrial fibrillation driver location and acute pulmonary vein ablation success using the 12-lead ECG</t1>
  <t2>Cardiovasc. digit. health j.</t2>
  <sn/>
  <op/>
  <vo/>
  <ab/>
  <la>eng</la>
  <k1/>
  <pb/>
  <pp/>
  <yr>2021</yr>
  <ed/>
  <ul>http://zaguan.unizar.es/record/109482/files/texto_completo.pdf;
	http://zaguan.unizar.es/record/109482/files/texto_completo.jpg?subformat=icon;
	</ul>
  <no>Imported from Invenio.</no>
</reference>

</references>