Patient Satisfaction Scores Part 2

<p>In this episode, I am continuing my discussion on Patient Satisfaction Scores and how Artificial Intelligence can be applied to classify and analyze these scores to extract meaningful information. </p> <p><br></p> <p><a href="https://hlthanalyticinsights.gumroad.com/l/healthinformatics">eBook</a><strong>: </strong>https://hlthanalyticinsights.gumroad.com/l/healthinformatics</p> <p>Resources: </p> <p><a href="https://www.thieme-connect.com/products/ejournals/pdf/10.1055/s-0040-1708049.pdf" target="_blank" rel="noopener noreferer">Natural Language Processing to Extract Meaningful Information from Patient Experience Feedback: </a></p> <p>https://www.thieme-connect.com/products/ejournals/pdf/10.1055/s-0040-1708049.pdf</p> <p><br></p> <p> </p> <p>Welcome to the Health Analytic Insights Podcast. This podcast is ALL about creating a community of like-minded individuals who are passionate about the field of health informatics. I hope to share information and advice in topics such as health analytics, digital health, biomedical engineering and data visualization in healthcare and in exchange I would love to hear from you DEAR listener about your experience and interest in this field, you can drop me a line at <a href="mailto:healthcareanalyticinsights@gmail.com">⁠healthanalyticinsights@gmail.com⁠</a>.</p> <p>Sign up to the newsletter and get your FREE guide to starting your career in health informatics <a href="https://mailchi.mp/e4cd52ccaaf5/health-analytic-insights">⁠here⁠</a>.   </p> <p><strong>DISCLAIMER: The views expressed on this podcast are my own and do not reflect those of people, organizations or institutions that I might be associated with in a professional capacity, unless explicitly stated. The views expressed by the guests on this show are their own and may or may not reflect those of people, organizations or institutions that I might be associated with in a professional capacity, unless explicitly stated.</strong></p>