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Artificial Intelligence as a Tool for Creating Patient Visit Summary: A Scoping Review and Guide to Implementation in an Erectile Dysfunction Clinic
Purpose of Review In modern healthcare, the integration of artificial intelligence (AI) has revolutionized clinical practices, particularly in data management and patient visit summary creation. Manual creation of patient summary is repetitive, time-consuming, prone to errors, and increases clinicia...
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Published in: | Current urology reports 2025-12, Vol.26 (1), p.20, Article 20 |
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description | Purpose of Review
In modern healthcare, the integration of artificial intelligence (AI) has revolutionized clinical practices, particularly in data management and patient visit summary creation. Manual creation of patient summary is repetitive, time-consuming, prone to errors, and increases clinicians’ workload. AI, through voice recognition and Natural Language Processing (NLP), can automate this task more accurately and efficiently. Erectile dysfunction (ED) clinics, which deal with specific pattern of conditions together with an involvement of broader systemic issues, can greatly benefit from AI-driven patient summary. This scoping review examined the evidence on AI-generated patient summary and evaluated their implementation in ED clinics.
Recent Findings
A total of 381 articles were initially identified, 11 studies were included for the analysis. These studies showcased various methodologies, such as AI-assisted clinical notes and NLP algorithms. Most studies have demonstrated the ability of AI to be used in real life clinical scenarios. Major electronic health record platforms are also integrating AI to their system. However, to date, no studies have specifically addressed AI for patient summary creation in ED clinics. |
doi_str_mv | 10.1007/s11934-024-01237-1 |
format | article |
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In modern healthcare, the integration of artificial intelligence (AI) has revolutionized clinical practices, particularly in data management and patient visit summary creation. Manual creation of patient summary is repetitive, time-consuming, prone to errors, and increases clinicians’ workload. AI, through voice recognition and Natural Language Processing (NLP), can automate this task more accurately and efficiently. Erectile dysfunction (ED) clinics, which deal with specific pattern of conditions together with an involvement of broader systemic issues, can greatly benefit from AI-driven patient summary. This scoping review examined the evidence on AI-generated patient summary and evaluated their implementation in ED clinics.
Recent Findings
A total of 381 articles were initially identified, 11 studies were included for the analysis. These studies showcased various methodologies, such as AI-assisted clinical notes and NLP algorithms. Most studies have demonstrated the ability of AI to be used in real life clinical scenarios. Major electronic health record platforms are also integrating AI to their system. However, to date, no studies have specifically addressed AI for patient summary creation in ED clinics.</description><identifier>ISSN: 1527-2737</identifier><identifier>ISSN: 1534-6285</identifier><identifier>EISSN: 1534-6285</identifier><identifier>DOI: 10.1007/s11934-024-01237-1</identifier><identifier>PMID: 39556140</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Artificial Intelligence ; Electronic Health Records ; Erectile Dysfunction - therapy ; Humans ; Male ; Medicine ; Medicine & Public Health ; Natural Language Processing ; Nephrology ; Review ; Topical Collection on Men’s Health ; Urology</subject><ispartof>Current urology reports, 2025-12, Vol.26 (1), p.20, Article 20</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c228t-6995c9eaa361d51286f2ef7cf4fcedc80b738abad21f14f4bf6df45735d3d3023</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39556140$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lumbiganon, Supanut</creatorcontrib><creatorcontrib>Abou Chawareb, Elia</creatorcontrib><creatorcontrib>Moukhtar Hammad, Muhammed A.</creatorcontrib><creatorcontrib>Azad, Babak</creatorcontrib><creatorcontrib>Shah, Dillan</creatorcontrib><creatorcontrib>Yafi, Faysal A.</creatorcontrib><title>Artificial Intelligence as a Tool for Creating Patient Visit Summary: A Scoping Review and Guide to Implementation in an Erectile Dysfunction Clinic</title><title>Current urology reports</title><addtitle>Curr Urol Rep</addtitle><addtitle>Curr Urol Rep</addtitle><description>Purpose of Review
In modern healthcare, the integration of artificial intelligence (AI) has revolutionized clinical practices, particularly in data management and patient visit summary creation. Manual creation of patient summary is repetitive, time-consuming, prone to errors, and increases clinicians’ workload. AI, through voice recognition and Natural Language Processing (NLP), can automate this task more accurately and efficiently. Erectile dysfunction (ED) clinics, which deal with specific pattern of conditions together with an involvement of broader systemic issues, can greatly benefit from AI-driven patient summary. This scoping review examined the evidence on AI-generated patient summary and evaluated their implementation in ED clinics.
Recent Findings
A total of 381 articles were initially identified, 11 studies were included for the analysis. These studies showcased various methodologies, such as AI-assisted clinical notes and NLP algorithms. Most studies have demonstrated the ability of AI to be used in real life clinical scenarios. Major electronic health record platforms are also integrating AI to their system. However, to date, no studies have specifically addressed AI for patient summary creation in ED clinics.</description><subject>Artificial Intelligence</subject><subject>Electronic Health Records</subject><subject>Erectile Dysfunction - therapy</subject><subject>Humans</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Natural Language Processing</subject><subject>Nephrology</subject><subject>Review</subject><subject>Topical Collection on Men’s Health</subject><subject>Urology</subject><issn>1527-2737</issn><issn>1534-6285</issn><issn>1534-6285</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><recordid>eNp9UctuEzEUtSoQbQM_0AW6SzbT-jHP7qK0tJEqgWhhazn2deRqxk5tD6j_wQfjNIUlC-ta9zykew4hZ4yeM0q7i8TYIOqK8vIYF13FjsgJa8qq5X3zZv_nXcU70R2T05QeKeWU9vU7ciyGpmlZTU_I72XMzjrt1Ahrn3Ec3Ra9RlAJFDyEMIINEVYRVXZ-C1_LQJ_hh0suw_08TSo-X8IS7nXY7Qnf8KfDX6C8gZvZGYQcYD3tRpyKrIiDB-cLDNcRdXYjwtVzsrPXL9BqdN7p9-StVWPCD69zQb5_vn5Y3VZ3X27Wq-VdpTnvc9UOQ6MHVEq0zDSM963laDtta6vR6J5uOtGrjTKcWVbbemNbY-umE40RRlAuFuTTwXcXw9OMKcvJJV0yUB7DnKRgfGj7gZdMF4QfqDqGlCJauYtuf7tkVO7bkIc2ZGlDvrQhWRF9fPWfNxOaf5K_8ReCOBBSgfwWo3wMc_Tl5v_Z_gFWPpc_</recordid><startdate>20251201</startdate><enddate>20251201</enddate><creator>Lumbiganon, Supanut</creator><creator>Abou Chawareb, Elia</creator><creator>Moukhtar Hammad, Muhammed A.</creator><creator>Azad, Babak</creator><creator>Shah, Dillan</creator><creator>Yafi, Faysal A.</creator><general>Springer US</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>20251201</creationdate><title>Artificial Intelligence as a Tool for Creating Patient Visit Summary: A Scoping Review and Guide to Implementation in an Erectile Dysfunction Clinic</title><author>Lumbiganon, Supanut ; Abou Chawareb, Elia ; Moukhtar Hammad, Muhammed A. ; Azad, Babak ; Shah, Dillan ; Yafi, Faysal A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c228t-6995c9eaa361d51286f2ef7cf4fcedc80b738abad21f14f4bf6df45735d3d3023</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Artificial Intelligence</topic><topic>Electronic Health Records</topic><topic>Erectile Dysfunction - therapy</topic><topic>Humans</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Natural Language Processing</topic><topic>Nephrology</topic><topic>Review</topic><topic>Topical Collection on Men’s Health</topic><topic>Urology</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lumbiganon, Supanut</creatorcontrib><creatorcontrib>Abou Chawareb, Elia</creatorcontrib><creatorcontrib>Moukhtar Hammad, Muhammed A.</creatorcontrib><creatorcontrib>Azad, Babak</creatorcontrib><creatorcontrib>Shah, Dillan</creatorcontrib><creatorcontrib>Yafi, Faysal A.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Current urology reports</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lumbiganon, Supanut</au><au>Abou Chawareb, Elia</au><au>Moukhtar Hammad, Muhammed A.</au><au>Azad, Babak</au><au>Shah, Dillan</au><au>Yafi, Faysal A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Artificial Intelligence as a Tool for Creating Patient Visit Summary: A Scoping Review and Guide to Implementation in an Erectile Dysfunction Clinic</atitle><jtitle>Current urology reports</jtitle><stitle>Curr Urol Rep</stitle><addtitle>Curr Urol Rep</addtitle><date>2025-12-01</date><risdate>2025</risdate><volume>26</volume><issue>1</issue><spage>20</spage><pages>20-</pages><artnum>20</artnum><issn>1527-2737</issn><issn>1534-6285</issn><eissn>1534-6285</eissn><abstract>Purpose of Review
In modern healthcare, the integration of artificial intelligence (AI) has revolutionized clinical practices, particularly in data management and patient visit summary creation. Manual creation of patient summary is repetitive, time-consuming, prone to errors, and increases clinicians’ workload. AI, through voice recognition and Natural Language Processing (NLP), can automate this task more accurately and efficiently. Erectile dysfunction (ED) clinics, which deal with specific pattern of conditions together with an involvement of broader systemic issues, can greatly benefit from AI-driven patient summary. This scoping review examined the evidence on AI-generated patient summary and evaluated their implementation in ED clinics.
Recent Findings
A total of 381 articles were initially identified, 11 studies were included for the analysis. These studies showcased various methodologies, such as AI-assisted clinical notes and NLP algorithms. Most studies have demonstrated the ability of AI to be used in real life clinical scenarios. Major electronic health record platforms are also integrating AI to their system. However, to date, no studies have specifically addressed AI for patient summary creation in ED clinics.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>39556140</pmid><doi>10.1007/s11934-024-01237-1</doi></addata></record> |
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subjects | Artificial Intelligence Electronic Health Records Erectile Dysfunction - therapy Humans Male Medicine Medicine & Public Health Natural Language Processing Nephrology Review Topical Collection on Men’s Health Urology |
title | Artificial Intelligence as a Tool for Creating Patient Visit Summary: A Scoping Review and Guide to Implementation in an Erectile Dysfunction Clinic |
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