BEGIN:VCALENDAR VERSION:2.0 METHOD:PUBLISH PRODID:-//ACC//Meetings//EN BEGIN:VTIMEZONE TZID:Eastern Standard Time BEGIN:STANDARD DTSTART:16011101T020000 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 TZNAME:Eastern Standard Time END:STANDARD BEGIN:DAYLIGHT DTSTART:16010301T020000 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 TZNAME:Eastern Daylight Time END:DAYLIGHT END:VTIMEZONE BEGIN:VEVENT DESCRIPTION:\n\n\nWebinar Overview\nUntapping the full potential of opportu nistic detection of subclinical atherosclerotic cardiovascular disease usi ng artificial intelligence (AI).\nSubclinical atherosclerotic cardiovascul ar disease (ASCVD) often remains undetected until it manifests as acute ca rdiovascular events. Advancements in AI have enabled the opportunistic det ection of ASCVD using imaging modalities performed for other clinical indi cations\, such as non-electrocardiogram (ECG) gated chest computed tomogra phy (CT). This session\, hosted by ACC's Health Care Innovation Member Sec tion\, will explore the integration of AI algorithms in analyzing routine imaging studies to identify incidental findings indicative of ASCVD\, ther eby facilitating early intervention and improved patient outcomes.\nKey Ob jectives/Learning Outcomes:\n\nUnderstand the role of AI in analyzing non- ECG gated chest CT scans for the opportunistic detection of coronary arter y calcium and its clinical implications.\nExplore the application of AI-en hanced imaging technologies in identifying subclinical ASCVD during routin e non-cardiac imaging procedures.\nDiscuss the challenges and opportunitie s associated with integrating AI-based opportunistic screening into clinic al workflows. \nEvaluate the impact of early detection of subclinical ASCV D on patient management and outcomes.\n\n\nWebinar Recording\n\n\n-->\n\nW ebinar Participants\nFrancisco Lopez-Jimenez MD\, MS\, MBA\, FACC\nAlexand er Sandhu\, MD\, MS\nRaffi Hagopian\, MD\n\nCredit Information\nNo credit is being offered for this webinar.\n\n\n\n\n\n .videoWrapper {\n pos ition: relative\;\n padding-bottom: 56.25%\; /* 16:9 */\n padding-to p: 25px\;\n height: 0\;\n }\n .videoWrapper iframe {\n positio n: absolute\;\n top: 0\;\n left: 0\;\n width: 100%\;\n height: 100%\;\n }\n DTEND;TZID=Eastern Standard Time:20260513T191500 DTSTAMP:20260501T093324Z DTSTART;TZID=Eastern Standard Time:20260513T190000 LOCATION:Online - Eastern Time (ET) SEQUENCE:0 SUMMARY:AI For CAD Detection UID:9ffd22b6-8d62-416f-aae5-15ed425822f4@acc.org X-ALT-DESC;FMTTYPE=text/html:
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Webinar Overvi ew

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Untapping the full potential of opportu nistic detection of subclinical atherosclerotic cardiovascular disease usi ng artificial intelligence (AI).

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Subclinical athero sclerotic cardiovascular disease (ASCVD) often remains undetected until it manifests as acute cardiovascular events. Advancements in AI have enabled the opportunistic detection of ASCVD using imaging modalities performed f or other clinical indications\, such as non-electrocardiogram (ECG) gated chest computed tomography (CT). This session\, hosted by ACC's Health Care Innovation Member Section\, will explore the integration of AI algorithms in analyzing routine imaging studies to identify incidental findings indi cative of ASCVD\, thereby facilitating early intervention and improved pat ient outcomes.

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Key Objectives/Learning Outc omes:

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  1. Understand the role of AI in analyzing non-ECG gated chest CT scans for the opportunistic detection of coronary artery calcium and its clinical implications.
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  2. Explore t he application of AI-enhanced imaging technologies in identifying subclini cal ASCVD during routine non-cardiac imaging procedures.
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  3. Discuss the challenges and opportunities associated with integrating AI-based opp ortunistic screening into clinical workflows.
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  4. Evaluate the impa ct of early detection of subclinical ASCVD on patient management and outco mes.
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Webinar Participants

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Francisc o Lopez-Jimenez MD\, MS\, MBA\, FACC
\nAlexander Sandhu\, MD\, MS
\nRaffi Hagopian\, MD

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Credit I nformation

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No credit is being offered for this webina r.

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