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5. Effects of cannabis on pulmonary arterial pressure in patients hospitalized for acute cardiac events: From the ADDICT-ICCU study

6. Incremental prognostic value of late gadolinium enhancement extent, transmurality, and pattern in patients with ischemic cardiomyopathy

7. Incremental prognostic value of coronary plaque features on CT angiography in symptomatic patients with obstructive CAD

8. Impacts of illicit drug use on coronary angiographic findings in a multicenter registry of patients with acute coronary syndrome

9. Machine learning score using cardiac MRI to predict cardiovascular events in patients with acute myocarditis

10. Machine learning for major adverse cardiac events prediction in patients with acute coronary syndrome: Results from ADDICT-ICCU study

11. Optimal cut-off point of the global circumferential strain measured at stress for prediction of cardiovascular events

12. Machine learning score using only echocardiographic data for prediction of in-hospital outcomes in ICCU patients

14. In-hospital prognostic value of TAPSE/sPAP in patients hospitalized for acute heart failure

15. Prognostic impact of recreational drug use at 1-year follow-up in patients hospitalized for acute cardiovascular events

16. Invasive coronary angiography features associated with high exhaled carbon monoxide in acute coronary syndromes from a prospective multicentric registry

18. Optimal cut-off thresholds of LGE extent to predict death using machine-learning in a large cohort of ICM patients

20. Left atrioventricular coupling index assessed using cardiac CT as a prognostic marker of cardiovascular death

21. Artificial intelligence fully automated assessment of global longitudinal strain predicts death in patients undergoing stress CMR

22. Factors associated with coronary revascularization in patients with suspected NSTE-ACS from a large multicenter prospective registry

23. Prognostic value of non-ischemic late gadolinium enhancement in patients with ischemic cardiomyopathy

24. Prevalence and epidemiological characteristics of psychoactive substance use in elderly patients: Insight from the ADDICT-ICCU study

25. Impact of carbon monoxide in smokers hospitalised with acute cardiac events

26. Prognostic impact of the extent, location, and pattern of late gadolinium enhancement in non-ischemic dilated cardiomyopathy

27. Machine learning to predict in-hospital outcomes in patients with acute heart failure

28. No difference on angiographic features between women and men in patients with acute coronary syndrome: Insights from the ADDICT-ICCU study

29. Prevalence and in-hospital prognostic impact of illicit drug use in patients hospitalized for acute heart failure

30. Machine-Learning Score using Stress CMR and CCTA for prediction of cardiovascular events in patients with obstructive CAD

31. Left atrioventricular coupling index assessed using cardiac CT as a prognostic marker of cardiovascular death

32. Machine-learning score using CCTA and stress CMR for prediction of cardiovascular events in patients with obstructive CAD

33. Machine learning to predict in-hospital outcomes in patients with acute heart failure

34. Ai-based fully automated left atrioventricular coupling index as a prognostic marker in patients undergoing stress-CMR

35. Machine learning for in-hospital cardiac events prediction in patients with acute coronary syndrome: results from ADDICT-ICCU study

36. Incremental prognostic value of coronary plaque features on CT angiography in symptomatic patients with obstructive CAD

37. Machine-learning score to predict in-hospital outcomes in patients Hospitalized in Intensive Cardiac Care Unit

38. In-hospital prognosis of recreational drug use in patients with acute ST-elevation myocardial infarction: insights from the ADDICT-ICCU study

40. Machine learning to detect recreational drugs use in cardiac intensive care units

41. Safety and incremental prognostic value of stress CMR in patients with known chronic kidney disease

42. No difference on angiographic features between women and men in patients with acute coronary syndrome: insights from the ADDICT-ICCU study

43. Machine learning using cardiovascular magnetic resonance to predict cardiovascular events in patients with acute myocarditis

45. Characterizing patients ineligible for mitral valve intervention: Phenotypic clustering sub-analysis from the CHOICE-MI Registry

46. Prognostic impact of the extent, location, and pattern of late gadolinium enhancement in dilated cardiomyopathy

47. Impacts of illicit drug use on coronary angiographic findings in a multicenter registry of patients with acute coronary syndrome

48. Incremental prognostic value of late gadolinium enhancement extent, transmurality, and pattern in patients with ischaemic cardiomyopathy

49. In-hospital Prognostic Value of TAPSE/sPAP in Patients Hospitalized for Acute Heart Failure

50. Machine learning score focused only on echocardiographic data to predict in-hospital outcomes in ICCU patients. A study from the ADDICT ICCU cohort

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