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    <title>Demystifying AI in Clinical Practice</title>
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    <description>Short one-on-one conversations with practicing radiologists and industry experts on how and where AI is being used in clinical practice today.</description>
    <copyright>Anderson Publishing, Ltd.</copyright>
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    <pubDate>Thu, 05 Mar 2026 13:59:02 -0500</pubDate>
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      <title>Demystifying AI in Clinical Practice</title>
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    <itunes:author>Applied Radiology</itunes:author>
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    <itunes:summary>Short one-on-one conversations with practicing radiologists and industry experts on how and where AI is being used in clinical practice today.</itunes:summary>
    <itunes:subtitle>Short one-on-one conversations with practicing radiologists and industry experts on how and where AI is being used in clinical practice today..</itunes:subtitle>
    <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
    <itunes:owner>
      <itunes:name>Kieran N Anderson</itunes:name>
    </itunes:owner>
    <itunes:complete>No</itunes:complete>
    <itunes:explicit>No</itunes:explicit>
    <item>
      <title>AI Takes Radiology from Diagnosis to Prevention</title>
      <itunes:episode>5</itunes:episode>
      <podcast:episode>5</podcast:episode>
      <itunes:title>AI Takes Radiology from Diagnosis to Prevention</itunes:title>
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      <description>
        <![CDATA[<p>From the Applied Radiology booth at RSNA, one theme surfaced repeatedly across conversations: artificial intelligence is no longer just about reading images faster—it is reshaping how radiology contributes to patient care, access, and population health. That message came through clearly during a live discussion between Kieran Anderson, Group Publisher at Applied Radiology, and<strong> </strong>Suzie Bash, MD, neuroradiologist and Medical Director at RadNet.</p>]]>
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      <content:encoded>
        <![CDATA[<p>From the Applied Radiology booth at RSNA, one theme surfaced repeatedly across conversations: artificial intelligence is no longer just about reading images faster—it is reshaping how radiology contributes to patient care, access, and population health. That message came through clearly during a live discussion between Kieran Anderson, Group Publisher at Applied Radiology, and<strong> </strong>Suzie Bash, MD, neuroradiologist and Medical Director at RadNet.</p>]]>
      </content:encoded>
      <pubDate>Thu, 05 Mar 2026 13:57:45 -0500</pubDate>
      <author>Applied Radiology</author>
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      <itunes:author>Applied Radiology</itunes:author>
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      <itunes:duration>520</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>From the Applied Radiology booth at RSNA, one theme surfaced repeatedly across conversations: artificial intelligence is no longer just about reading images faster—it is reshaping how radiology contributes to patient care, access, and population health. That message came through clearly during a live discussion between Kieran Anderson, Group Publisher at Applied Radiology, and<strong> </strong>Suzie Bash, MD, neuroradiologist and Medical Director at RadNet.</p>]]>
      </itunes:summary>
      <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Guest" img="https://img.transistorcdn.com/vVqVYrjEZBgNBztfOdDSgFI7ZPbQ7z2QCz4QeOLjJKM/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mNjEx/ZTVmYTFmZGE5M2Rh/YTM0NmZkY2ZjMGY4/NWJmMS5qcGc.jpg">Suzie Bash, MD</podcast:person>
      <podcast:person role="Host" img="https://img.transistorcdn.com/DOy-OIUCnJP0hMOT47gYvHg9ZmYte6KB4j_NeKmnbJQ/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mNjYw/NmM0MGZiN2I2MmZl/MmM3ZTJkOGQ4Y2Y1/ZGE1Ni5qcGc.jpg">Kieran Anderson</podcast:person>
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    <item>
      <title>Quantitative Imaging Redefines Value in Neuroradiology</title>
      <itunes:episode>7</itunes:episode>
      <podcast:episode>7</podcast:episode>
      <itunes:title>Quantitative Imaging Redefines Value in Neuroradiology</itunes:title>
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      <link>https://share.transistor.fm/s/06212423</link>
      <description>
        <![CDATA[<p>From the Applied Radiology booth at RSNA, one of the most technically rich—and clinically consequential—conversations focused on the evolving role of quantitative imaging in neuroradiology. In a live discussion, Lawrence Tanenbaum, MD sat down with Suzie Bash, MD to examine how volumetric and quantitative tools are reshaping diagnosis, longitudinal surveillance, and treatment decision-making.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>From the Applied Radiology booth at RSNA, one of the most technically rich—and clinically consequential—conversations focused on the evolving role of quantitative imaging in neuroradiology. In a live discussion, Lawrence Tanenbaum, MD sat down with Suzie Bash, MD to examine how volumetric and quantitative tools are reshaping diagnosis, longitudinal surveillance, and treatment decision-making.</p>]]>
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      <pubDate>Thu, 05 Mar 2026 13:57:18 -0500</pubDate>
      <author>Applied Radiology</author>
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      <itunes:author>Applied Radiology</itunes:author>
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      <itunes:duration>1284</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>From the Applied Radiology booth at RSNA, one of the most technically rich—and clinically consequential—conversations focused on the evolving role of quantitative imaging in neuroradiology. In a live discussion, Lawrence Tanenbaum, MD sat down with Suzie Bash, MD to examine how volumetric and quantitative tools are reshaping diagnosis, longitudinal surveillance, and treatment decision-making.</p>]]>
      </itunes:summary>
      <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" img="https://img.transistorcdn.com/t3ZkfYEKictVJZ84xAqSR9UC4RIavAScv3LaoAq7aOA/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS82ODhm/NTE1NGJiMmQ1NTc4/OGZiMWMwMDZmZWZi/ZDI5MS5qcGc.jpg">Lawrence Tanenbaum, MD</podcast:person>
      <podcast:person role="Guest" img="https://img.transistorcdn.com/vVqVYrjEZBgNBztfOdDSgFI7ZPbQ7z2QCz4QeOLjJKM/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mNjEx/ZTVmYTFmZGE5M2Rh/YTM0NmZkY2ZjMGY4/NWJmMS5qcGc.jpg">Suzie Bash, MD</podcast:person>
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    <item>
      <title>AI in Radiology: Isolated Algorithms to Scalable Clinical Impact</title>
      <itunes:episode>8</itunes:episode>
      <podcast:episode>8</podcast:episode>
      <itunes:title>AI in Radiology: Isolated Algorithms to Scalable Clinical Impact</itunes:title>
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      <description>
        <![CDATA[<p>Artificial intelligence in radiology is often discussed in broad, aspirational terms, but far less attention is paid to what happens after algorithms are cleared, purchased, and deployed. In a recent discussion hosted by Applied Radiology, experts examined how AI is being implemented at scale and what it takes to translate technical capability into meaningful clinical impact.</p><p>During the conversation, Avi Sharma, MD, host of Applied Radiology’s AI Podcast was joined by co-host Lawrence Tanenbaum, MD, and Greg Sorenson, MD, Chief Science Officer at RadNet, and, to explore how AI moves from isolated tools to enterprise-level infrastructure. The discussion focused less on individual algorithms and more on workflow, adoption, and sustainability in real-world imaging environments</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Artificial intelligence in radiology is often discussed in broad, aspirational terms, but far less attention is paid to what happens after algorithms are cleared, purchased, and deployed. In a recent discussion hosted by Applied Radiology, experts examined how AI is being implemented at scale and what it takes to translate technical capability into meaningful clinical impact.</p><p>During the conversation, Avi Sharma, MD, host of Applied Radiology’s AI Podcast was joined by co-host Lawrence Tanenbaum, MD, and Greg Sorenson, MD, Chief Science Officer at RadNet, and, to explore how AI moves from isolated tools to enterprise-level infrastructure. The discussion focused less on individual algorithms and more on workflow, adoption, and sustainability in real-world imaging environments</p>]]>
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      <pubDate>Thu, 05 Mar 2026 13:56:59 -0500</pubDate>
      <author>Applied Radiology</author>
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      <itunes:author>Applied Radiology</itunes:author>
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      <itunes:duration>1060</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Artificial intelligence in radiology is often discussed in broad, aspirational terms, but far less attention is paid to what happens after algorithms are cleared, purchased, and deployed. In a recent discussion hosted by Applied Radiology, experts examined how AI is being implemented at scale and what it takes to translate technical capability into meaningful clinical impact.</p><p>During the conversation, Avi Sharma, MD, host of Applied Radiology’s AI Podcast was joined by co-host Lawrence Tanenbaum, MD, and Greg Sorenson, MD, Chief Science Officer at RadNet, and, to explore how AI moves from isolated tools to enterprise-level infrastructure. The discussion focused less on individual algorithms and more on workflow, adoption, and sustainability in real-world imaging environments</p>]]>
      </itunes:summary>
      <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" img="https://img.transistorcdn.com/3Ub-fJ79AKbc5mbdJyQNjSEJUryBOSSmTMLHTp6eocM/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80MzJm/NDY4NzM3OGFmZWM4/ZDg3ODI3ODYwNDA2/MDVkZC5qcGc.jpg">Avishkar (Avi) Sharma, MD, CIIP</podcast:person>
      <podcast:person role="Host" img="https://img.transistorcdn.com/t3ZkfYEKictVJZ84xAqSR9UC4RIavAScv3LaoAq7aOA/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS82ODhm/NTE1NGJiMmQ1NTc4/OGZiMWMwMDZmZWZi/ZDI5MS5qcGc.jpg">Lawrence Tanenbaum, MD</podcast:person>
      <podcast:person role="Guest" img="https://img.transistorcdn.com/j4a3IxN46KW0iGlHYoErs6pdEvFzjmk6extR02f0ASU/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS84NjMy/OTkwMWM3Mzk2YjJk/NmVlNjc3M2UzODhm/NDEyNC5qcGc.jpg">Greg Sorensen</podcast:person>
    </item>
    <item>
      <title>Foundation Models Emerge as the “Electricity” of Radiology AI</title>
      <itunes:episode>6</itunes:episode>
      <podcast:episode>6</podcast:episode>
      <itunes:title>Foundation Models Emerge as the “Electricity” of Radiology AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/d59b6780</link>
      <description>
        <![CDATA[<p>Fans of the PBS television series <em>Downton Abbey</em>, set in early 20th-century England, witnessed the far-reaching effects of the Second Industrial Revolution—particularly innovations in electricity, mechanization, and communication—on the lives of its characters. <em>What fueled this all-encompassing change, </em>and what does it have in common with artificial intelligence in health care? </p><p>During a discussion with Nina Kottler, MD, Chief Medical AI Officer at Mosaic Clinical Technologies, Lawrence Tanenbaum, MD, raised the comparison as a way to describe how foundational technologies perhaps, not so quietly, reshape professional life</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Fans of the PBS television series <em>Downton Abbey</em>, set in early 20th-century England, witnessed the far-reaching effects of the Second Industrial Revolution—particularly innovations in electricity, mechanization, and communication—on the lives of its characters. <em>What fueled this all-encompassing change, </em>and what does it have in common with artificial intelligence in health care? </p><p>During a discussion with Nina Kottler, MD, Chief Medical AI Officer at Mosaic Clinical Technologies, Lawrence Tanenbaum, MD, raised the comparison as a way to describe how foundational technologies perhaps, not so quietly, reshape professional life</p>]]>
      </content:encoded>
      <pubDate>Thu, 05 Mar 2026 13:56:36 -0500</pubDate>
      <author>Applied Radiology</author>
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      <itunes:author>Applied Radiology</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/E6vHyU3__eWxfG4-qGbnLLgjbAE5TXkRhUGAosc9r1A/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS82YjE0/NzMwNzBjNmNkZmFl/NDdmNTFiNzQyZTE4/OTIzZC5wbmc.jpg"/>
      <itunes:duration>1589</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Fans of the PBS television series <em>Downton Abbey</em>, set in early 20th-century England, witnessed the far-reaching effects of the Second Industrial Revolution—particularly innovations in electricity, mechanization, and communication—on the lives of its characters. <em>What fueled this all-encompassing change, </em>and what does it have in common with artificial intelligence in health care? </p><p>During a discussion with Nina Kottler, MD, Chief Medical AI Officer at Mosaic Clinical Technologies, Lawrence Tanenbaum, MD, raised the comparison as a way to describe how foundational technologies perhaps, not so quietly, reshape professional life</p>]]>
      </itunes:summary>
      <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" img="https://img.transistorcdn.com/t3ZkfYEKictVJZ84xAqSR9UC4RIavAScv3LaoAq7aOA/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS82ODhm/NTE1NGJiMmQ1NTc4/OGZiMWMwMDZmZWZi/ZDI5MS5qcGc.jpg">Lawrence Tanenbaum, MD</podcast:person>
      <podcast:person role="Guest" img="https://img.transistorcdn.com/LD4YtORN5jd-zcubAl9JcvR_ZeTqAYTHRzqBuzWK-Xs/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8yMTg1/MmE0Zjk1YzViMTU2/MDNhNjM0YTQ1NmNk/NzZjMC5qcGc.jpg">Nina Kottler, MD</podcast:person>
    </item>
    <item>
      <title>AI in Neuro Imaging | Before, During, &amp; Post Imaging</title>
      <itunes:episode>4</itunes:episode>
      <podcast:episode>4</podcast:episode>
      <itunes:title>AI in Neuro Imaging | Before, During, &amp; Post Imaging</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">20b6e38d-9d4a-4eb5-9dd8-c384c7dfc720</guid>
      <link>https://share.transistor.fm/s/53a3f045</link>
      <description>
        <![CDATA[<p>Dr. Avi Sharma sits down with Dr. Suzie Bash to discuss her use of AI in clinical practice as it relates to managing patients with Alzheimer disease. </p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Dr. Avi Sharma sits down with Dr. Suzie Bash to discuss her use of AI in clinical practice as it relates to managing patients with Alzheimer disease. </p>]]>
      </content:encoded>
      <pubDate>Thu, 10 Jul 2025 05:52:18 -0400</pubDate>
      <author>Applied Radiology</author>
      <enclosure url="https://media.transistor.fm/53a3f045/3f3dcc47.mp3" length="23619783" type="audio/mpeg"/>
      <itunes:author>Applied Radiology</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/wrzFxtXhcnxav4r36BkxTSApawlTMDSmX_RFhJFcIAM/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9iYzBh/OWZiODE5MmM4ZjYz/OGI1YzRiYTZkMjUz/NDZkMS5wbmc.jpg"/>
      <itunes:duration>1475</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Dr. Avi Sharma sits down with Dr. Suzie Bash to discuss her use of AI in clinical practice as it relates to managing patients with Alzheimer disease. </p>]]>
      </itunes:summary>
      <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" img="https://img.transistorcdn.com/3Ub-fJ79AKbc5mbdJyQNjSEJUryBOSSmTMLHTp6eocM/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80MzJm/NDY4NzM3OGFmZWM4/ZDg3ODI3ODYwNDA2/MDVkZC5qcGc.jpg">Avishkar (Avi) Sharma, MD, CIIP</podcast:person>
      <podcast:person role="Guest" img="https://img.transistorcdn.com/vVqVYrjEZBgNBztfOdDSgFI7ZPbQ7z2QCz4QeOLjJKM/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9mNjEx/ZTVmYTFmZGE5M2Rh/YTM0NmZkY2ZjMGY4/NWJmMS5qcGc.jpg">Suzie Bash, MD</podcast:person>
    </item>
    <item>
      <title>AI in Medical Imaging | What's on the Horizon</title>
      <itunes:episode>3</itunes:episode>
      <podcast:episode>3</podcast:episode>
      <itunes:title>AI in Medical Imaging | What's on the Horizon</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/592f95f2</link>
      <description>
        <![CDATA[<p>Dr. Avi Sharma sits down with Dr. Ari Goldberg to discuss the current state of AI in medical imaging. </p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Dr. Avi Sharma sits down with Dr. Ari Goldberg to discuss the current state of AI in medical imaging. </p>]]>
      </content:encoded>
      <pubDate>Wed, 23 Apr 2025 09:44:59 -0400</pubDate>
      <author>Applied Radiology</author>
      <enclosure url="https://media.transistor.fm/592f95f2/5caaf219.mp3" length="15001047" type="audio/mpeg"/>
      <itunes:author>Applied Radiology</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/AOH43CyUewfkRC_qh0Tt0xRs3CQv0j2W4p25cjpI54M/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS8xNzg5/OTU4MGFlM2NjY2Ix/OWIxMTk3MTFjMTE5/ZGVmYy5wbmc.jpg"/>
      <itunes:duration>936</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Dr. Avi Sharma sits down with Dr. Ari Goldberg to discuss the current state of AI in medical imaging. </p>]]>
      </itunes:summary>
      <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" img="https://img.transistorcdn.com/3Ub-fJ79AKbc5mbdJyQNjSEJUryBOSSmTMLHTp6eocM/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80MzJm/NDY4NzM3OGFmZWM4/ZDg3ODI3ODYwNDA2/MDVkZC5qcGc.jpg">Avishkar (Avi) Sharma, MD, CIIP</podcast:person>
      <podcast:person role="Guest" img="https://img.transistorcdn.com/YvkL4JNAXR2P3F2Xeq1X-WzUUsw6TEO8ovv236lXw5Y/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS83ZDRm/M2IwZWI0ZjFhYWE5/ZjJlMGRhNzc3NThl/MDRjNy5qcGc.jpg">Ari Goldberg, MD</podcast:person>
    </item>
    <item>
      <title>AI in Pediatric Imaging</title>
      <itunes:episode>2</itunes:episode>
      <podcast:episode>2</podcast:episode>
      <itunes:title>AI in Pediatric Imaging</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://share.transistor.fm/s/f3842c43</link>
      <description>
        <![CDATA[<p>Host Dr. Avi Sharma sits down with Dr. Aashim Bhatia, a pediatric neuroradiologist at CHOP to talk about the current state of artificial intelligence in clinical practice and the need for more tools in pediatric imaging.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Host Dr. Avi Sharma sits down with Dr. Aashim Bhatia, a pediatric neuroradiologist at CHOP to talk about the current state of artificial intelligence in clinical practice and the need for more tools in pediatric imaging.</p>]]>
      </content:encoded>
      <pubDate>Wed, 26 Mar 2025 18:39:43 -0400</pubDate>
      <author>Applied Radiology</author>
      <enclosure url="https://media.transistor.fm/f3842c43/7e86059f.mp3" length="19204310" type="audio/mpeg"/>
      <itunes:author>Applied Radiology</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/exdzAA4E4sIQ_eYFREjLeGgcZKhZlcVZbp-GS1SoBaU/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS84MWIx/MTdhM2ZkMjFkNmQz/ZmRiNDNkNjkwMTlk/ZjhiYy5wbmc.jpg"/>
      <itunes:duration>1201</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Host Dr. Avi Sharma sits down with Dr. Aashim Bhatia, a pediatric neuroradiologist at CHOP to talk about the current state of artificial intelligence in clinical practice and the need for more tools in pediatric imaging.</p>]]>
      </itunes:summary>
      <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" img="https://img.transistorcdn.com/3Ub-fJ79AKbc5mbdJyQNjSEJUryBOSSmTMLHTp6eocM/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80MzJm/NDY4NzM3OGFmZWM4/ZDg3ODI3ODYwNDA2/MDVkZC5qcGc.jpg">Avishkar (Avi) Sharma, MD, CIIP</podcast:person>
      <podcast:person role="Guest" href="https://www.chop.edu/doctors/bhatia-aashim" img="https://img.transistorcdn.com/c39BiTAvTd2yHxOq4Hp0bO9ENdw0nY1zJHkh1C5WDkY/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80Y2Fi/YmNkYWNjN2QwZWRh/NjUwY2E2MTU1NDBm/MDY5MS5wbmc.jpg">Aashim Bhatia, MD</podcast:person>
    </item>
    <item>
      <title>Introduction to Demystifying AI in Clinical Practice</title>
      <itunes:episode>1</itunes:episode>
      <podcast:episode>1</podcast:episode>
      <itunes:title>Introduction to Demystifying AI in Clinical Practice</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">e0d56c45-ac21-4b13-96ee-6dab33ca7565</guid>
      <link>https://share.transistor.fm/s/b768a8c2</link>
      <description>
        <![CDATA[<p>Applied Radiology Publisher, Kieran Anderson kicks of this podcast series with Dr. Avi Sharma, a body radiologists and Director of AI at Jefferson Health about how they think about and incorporate AI into their workflow at Jefferson.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>Applied Radiology Publisher, Kieran Anderson kicks of this podcast series with Dr. Avi Sharma, a body radiologists and Director of AI at Jefferson Health about how they think about and incorporate AI into their workflow at Jefferson.</p>]]>
      </content:encoded>
      <pubDate>Wed, 26 Mar 2025 18:39:31 -0400</pubDate>
      <author>Applied Radiology</author>
      <enclosure url="https://media.transistor.fm/b768a8c2/56cd959d.mp3" length="9389375" type="audio/mpeg"/>
      <itunes:author>Applied Radiology</itunes:author>
      <itunes:image href="https://img.transistorcdn.com/MJN-4l9U_EF_KSQ6Z1hwBHs6oRzNEizmNVDIxV3KQ88/rs:fill:0:0:1/w:1400/h:1400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9jYzI2/MTM3YTVlOTE4NDUw/NTYxNTgwNmJjMDFk/YTRhNy5wbmc.jpg"/>
      <itunes:duration>587</itunes:duration>
      <itunes:summary>
        <![CDATA[<p>Applied Radiology Publisher, Kieran Anderson kicks of this podcast series with Dr. Avi Sharma, a body radiologists and Director of AI at Jefferson Health about how they think about and incorporate AI into their workflow at Jefferson.</p>]]>
      </itunes:summary>
      <itunes:keywords>AI, Artificial Intelligence, Applied Radiology, Radiology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
      <podcast:person role="Host" img="https://img.transistorcdn.com/3Ub-fJ79AKbc5mbdJyQNjSEJUryBOSSmTMLHTp6eocM/rs:fill:0:0:1/w:800/h:800/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS80MzJm/NDY4NzM3OGFmZWM4/ZDg3ODI3ODYwNDA2/MDVkZC5qcGc.jpg">Avishkar (Avi) Sharma, MD, CIIP</podcast:person>
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