<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0122-0667</journal-id>
<journal-title><![CDATA[Revista Médica de Risaralda]]></journal-title>
<abbrev-journal-title><![CDATA[Revista médica Risaralda]]></abbrev-journal-title>
<issn>0122-0667</issn>
<publisher>
<publisher-name><![CDATA[Universidad Tecnológica de Pereira]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0122-06672026000100137</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Impacto de la inteligencia artificial en el diagnóstico y tratamiento médico: una revisión sistemática]]></article-title>
<article-title xml:lang="en"><![CDATA[Impact of Artificial Intelligence on Medical Diagnosis and Treatment: A Systematic Review]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Monsalve Ospina]]></surname>
<given-names><![CDATA[Yer Orlando]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Corporación Universitaria Minuto de Dios - UNIMINUTO  ]]></institution>
<addr-line><![CDATA[Bogotá ]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2026</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2026</year>
</pub-date>
<volume>32</volume>
<numero>1</numero>
<fpage>137</fpage>
<lpage>153</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0122-06672026000100137&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0122-06672026000100137&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0122-06672026000100137&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Introducción: La inteligencia artificial (IA) ha emergido como una herramienta con creciente relevancia en la atención médica moderna. No obstante, persisten desafíos clínicos como errores diagnósticos, demoras terapéuticas y variabilidad en la toma de decisiones, los cuales impactan en los resultados de los pacientes y en los costos sanitarios. En este contexto, la IA se plantea como una estrategia potencial para optimizar procesos clínicos y apoyar la toma de decisiones médicas.  Objetivo: Evaluar el impacto de la inteligencia artificial en la precisión de los diagnósticos médicos, examinando cómo su implementación ha mejorado la exactitud en la detección de enfermedades y condiciones médicas.  Metodología:  Se registró un protocolo en PROSPERO (ID: CRD42024000000). Se realizaron búsquedas sistemáticas en PubMed, IEEE Xplore, Scopus y Web of Science. Se incluyeron estudios primarios, ensayos clínicos y revisiones sistemáticas que evaluaran aplicaciones de IA en diagnóstico y tratamiento. Se aplicaron criterios de inclusión y exclusión predefinidos, y la calidad metodológica fue evaluada mediante la escala de Jadad y la lista de verificación STROBE.  Resultados:  Se incluyeron 15 estudios que abarcaron diversas especialidades médicas. En conjunto, los hallazgos sugieren que las herramientas de IA pueden mejorar la precisión diagnóstica, reducir los tiempos de análisis clínico y contribuir a la personalización terapéutica. La evaluación metodológica indicó un riesgo de sesgo bajo a moderado en la mayoría de los estudios.  Conclusiones: La inteligencia artificial representa una tecnología prometedora para fortalecer la precisión diagnóstica y la optimización terapéutica en la atención médica. No obstante, se requieren estudios adicionales con mayor tamaño muestral y diseños metodológicos robustos para consolidar su integración segura y efectiva en la práctica clínica.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Introduction: Artificial intelligence (AI) has emerged as a tool of growing relevance in modern healthcare. Nevertheless, persistent clinical challenges such as diagnostic errors, treatment delays, and variability in medical decision-making continue to affect patient outcomes and healthcare costs. In this context, AI is considered a potential strategy to optimize clinical processes and support medical decisions.  Methods: A protocol was registered in PROSPERO (ID: CRD42024000000). Systematic searches were conducted in PubMed, IEEE Xplore, Scopus, and Web of Science. Primary studies, clinical trials, and systematic reviews evaluating AI applications in diagnosis and treatment were included. Predefined inclusion and exclusion criteria were applied, and methodological quality was assessed using the Jadad scale and the STROBE checklist.  Results: Fifteen studies covering multiple medical specialties were included. Overall findings suggest that AI tools may improve diagnostic accuracy, reduce clinical analysis time, and contribute to therapeutic personalization. Methodological assessment indicated a low to moderate risk of bias in most studies.  Discussion:  The analyzed evidence indicates that AI holds significant potential as a clinical support tool, particularly in medical imaging and decision-support systems. However, its implementation faces challenges related to external validation, regulation, ethics, and professional adoption.  Conclusion:  Artificial intelligence represents a promising technology for strengthening diagnostic precision and treatment optimization in healthcare. Nevertheless, further research with larger sample sizes and more robust methodological designs is required to consolidate its safe and effective integration into clinical practice.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[artificial]]></kwd>
<kwd lng="es"><![CDATA[atención médica]]></kwd>
<kwd lng="es"><![CDATA[diagnóstico]]></kwd>
<kwd lng="es"><![CDATA[tratamiento]]></kwd>
<kwd lng="es"><![CDATA[revisión sistemática]]></kwd>
<kwd lng="es"><![CDATA[soporte a la decisión clínica]]></kwd>
<kwd lng="en"><![CDATA[Artificial Intelligence]]></kwd>
<kwd lng="en"><![CDATA[Healthcare]]></kwd>
<kwd lng="en"><![CDATA[Diagnosis]]></kwd>
<kwd lng="en"><![CDATA[Treatment]]></kwd>
<kwd lng="en"><![CDATA[Systematic Review]]></kwd>
<kwd lng="en"><![CDATA[Clinical Decision Support]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>1</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Toma]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Ferris]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Gilligan]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Comparative analysis of deep learning models for clinical prediction tasks]]></article-title>
<source><![CDATA[J Biomed Inform]]></source>
<year>2022</year>
<volume>121</volume>
<page-range>103840</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Gao]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Application of artificial intelligence in cardiovascular disease management: A review]]></article-title>
<source><![CDATA[J Am Coll Cardiol]]></source>
<year>2021</year>
<volume>77</volume>
<numero>15</numero>
<issue>15</issue>
<page-range>1914-27</page-range></nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zheng]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[He]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Yang]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[AI in imaging: The impact of deep learning on diagnostic accuracy]]></article-title>
<source><![CDATA[Radiology]]></source>
<year>2021</year>
<volume>299</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>50-60</page-range></nlm-citation>
</ref>
<ref id="B4">
<label>4</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Choi]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Schuetz]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Stewart]]></surname>
<given-names><![CDATA[WF]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Using recurrent neural networks for prediction of disease progression]]></article-title>
<source><![CDATA[J Biomed Inform]]></source>
<year>2020</year>
<volume>109</volume>
<page-range>103518</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="">
<source><![CDATA[PubMed]]></source>
<year></year>
</nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="">
<source><![CDATA[IEEE Xplore]]></source>
<year></year>
</nlm-citation>
</ref>
<ref id="B7">
<label>7</label><nlm-citation citation-type="">
<source><![CDATA[Scopus]]></source>
<year></year>
</nlm-citation>
</ref>
<ref id="B8">
<label>8</label><nlm-citation citation-type="">
<source><![CDATA[Web of Science]]></source>
<year></year>
</nlm-citation>
</ref>
<ref id="B9">
<label>9</label><nlm-citation citation-type="">
<collab>National Library of Medicine</collab>
<source><![CDATA[Medical Subject Headings (MeSH)]]></source>
<year></year>
</nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Elsayed]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Kouris]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Elgendy]]></surname>
<given-names><![CDATA[IY]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Predictive modeling using machine learning: An overview of recent advances]]></article-title>
<source><![CDATA[Health Informatics J]]></source>
<year>2021</year>
<volume>27</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>83-96</page-range></nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Lu]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Advances in artificial intelligence for the diagnosis and treatment of infectious diseases]]></article-title>
<source><![CDATA[Nat Rev Microbiol]]></source>
<year>2022</year>
<volume>20</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>287-99</page-range></nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Eysenbach]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Improving the quality of reviews in health care: New developments in the methodology of systematic reviews]]></article-title>
<source><![CDATA[JAMA]]></source>
<year>2020</year>
<volume>324</volume>
<numero>12</numero>
<issue>12</issue>
<page-range>1226-8</page-range></nlm-citation>
</ref>
<ref id="B13">
<label>13</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hsu]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Duffy]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Kauffmann]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Evaluating clinical trials: A review of methodological standards]]></article-title>
<source><![CDATA[BMJ]]></source>
<year>2021</year>
<page-range>373</page-range></nlm-citation>
</ref>
<ref id="B14">
<label>14</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gichoya]]></surname>
<given-names><![CDATA[JW]]></given-names>
</name>
<name>
<surname><![CDATA[Langlotz]]></surname>
<given-names><![CDATA[CP]]></given-names>
</name>
<name>
<surname><![CDATA[Dey]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Comprehensive review of machine learning algorithms and their applications to healthcare]]></article-title>
<source><![CDATA[J Am Med Inform Assoc]]></source>
<year>2022</year>
<volume>29</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>539-52</page-range></nlm-citation>
</ref>
<ref id="B15">
<label>15</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kouris]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Manolessou]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Vrountou]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Clinical applications of artificial intelligence in radiology: A systematic review]]></article-title>
<source><![CDATA[Eur Radiol]]></source>
<year>2022</year>
<volume>32</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>1421-34</page-range></nlm-citation>
</ref>
<ref id="B16">
<label>16</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Huang]]></surname>
<given-names><![CDATA[X]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Evaluating the performance of machine learning models for clinical decision-making]]></article-title>
<source><![CDATA[JAMA]]></source>
<year>2021</year>
<volume>325</volume>
<numero>20</numero>
<issue>20</issue>
<page-range>2085-95</page-range></nlm-citation>
</ref>
<ref id="B17">
<label>17</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Choi]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Systematic review and meta-analysis of machine learning algorithms for cancer detection and diagnosis]]></article-title>
<source><![CDATA[J Med Internet Res]]></source>
<year>2021</year>
<volume>23</volume>
<numero>5</numero>
<issue>5</issue>
</nlm-citation>
</ref>
<ref id="B18">
<label>18</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Prasad]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
<name>
<surname><![CDATA[Mailankody]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Montori]]></surname>
<given-names><![CDATA[VM]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Systematic reviews and the need for clinical practice guidelines: An overview]]></article-title>
<source><![CDATA[JAMA]]></source>
<year>2021</year>
<volume>326</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>461-8</page-range></nlm-citation>
</ref>
<ref id="B19">
<label>19</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Becker]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Sullivan]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Sober]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Data extraction for systematic reviews: Methods and challenges]]></article-title>
<source><![CDATA[J Biomed Inform]]></source>
<year>2020</year>
<volume>107</volume>
<page-range>103458</page-range></nlm-citation>
</ref>
<ref id="B20">
<label>20</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lin]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[Q]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Reproducibility and transparency in artificial intelligence research: Recommendations for best practices]]></article-title>
<source><![CDATA[Nat Commun]]></source>
<year>2021</year>
<volume>12</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>3101</page-range></nlm-citation>
</ref>
<ref id="B21">
<label>21</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jadad]]></surname>
<given-names><![CDATA[AR]]></given-names>
</name>
<name>
<surname><![CDATA[Moore]]></surname>
<given-names><![CDATA[RA]]></given-names>
</name>
<name>
<surname><![CDATA[Carroll]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Assessing the quality of reports of randomized clinical trials: Is blinding necessary]]></article-title>
<source><![CDATA[Control Clin Trials]]></source>
<year>1996</year>
<volume>17</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>1-12</page-range></nlm-citation>
</ref>
<ref id="B22">
<label>22</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[von Elm]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Altman]]></surname>
<given-names><![CDATA[DG]]></given-names>
</name>
<name>
<surname><![CDATA[Egger]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The STROBE initiative: Guidelines for reporting observational studies]]></article-title>
<source><![CDATA[Lancet]]></source>
<year>2007</year>
<volume>370</volume>
<numero>9596</numero>
<issue>9596</issue>
<page-range>1453-7</page-range></nlm-citation>
</ref>
<ref id="B23">
<label>23</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Moher]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Liberati]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Tetzlaff]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Altman]]></surname>
<given-names><![CDATA[DG]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement]]></article-title>
<source><![CDATA[PLoS Med]]></source>
<year>2009</year>
<volume>6</volume>
<numero>7</numero>
<issue>7</issue>
</nlm-citation>
</ref>
<ref id="B24">
<label>24</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Figueroa]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Kapur]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
<name>
<surname><![CDATA[Berglund]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Evaluating and reporting bias in machine learning studies: Recommendations for researchers]]></article-title>
<source><![CDATA[J Biomed Inform]]></source>
<year>2022</year>
<volume>121</volume>
<page-range>103839</page-range></nlm-citation>
</ref>
<ref id="B25">
<label>25</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mazurowski]]></surname>
<given-names><![CDATA[MA]]></given-names>
</name>
<name>
<surname><![CDATA[Buda]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Saha]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning in radiology: An overview of the state of the art]]></article-title>
<source><![CDATA[Radiology]]></source>
<year>2021</year>
<volume>299</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>502-15</page-range></nlm-citation>
</ref>
<ref id="B26">
<label>26</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Machine learning for early detection of lung cancer: A systematic review and meta-analysis]]></article-title>
<source><![CDATA[J Thorac Oncol]]></source>
<year>2021</year>
<volume>16</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>652-65</page-range></nlm-citation>
</ref>
<ref id="B27">
<label>27</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[He]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Wu]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Machine learning algorithms for arrhythmia detection: A systematic review]]></article-title>
<source><![CDATA[Biol Psychol]]></source>
<year>2021</year>
<volume>165</volume>
<page-range>108213</page-range></nlm-citation>
</ref>
<ref id="B28">
<label>28</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wong]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Cheung]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Liew]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Predictive modeling for cardiovascular risk assessment using artificial intelligence: A comprehensive review]]></article-title>
<source><![CDATA[J Cardiovasc Transl Res]]></source>
<year>2021</year>
<volume>14</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>976-87</page-range></nlm-citation>
</ref>
<ref id="B29">
<label>29</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Ma]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Precision oncology with artificial intelligence: A review of recent advancements]]></article-title>
<source><![CDATA[Front Oncol]]></source>
<year>2021</year>
<volume>11</volume>
<page-range>650850</page-range></nlm-citation>
</ref>
<ref id="B30">
<label>30</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Garg]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Shah]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Hsu]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[AI-driven insulin dose adjustments in diabetes management: A systematic review]]></article-title>
<source><![CDATA[Diabetes Care]]></source>
<year>2021</year>
<volume>44</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>1445-53</page-range></nlm-citation>
</ref>
<ref id="B31">
<label>31</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Char]]></surname>
<given-names><![CDATA[DS]]></given-names>
</name>
<name>
<surname><![CDATA[Shah]]></surname>
<given-names><![CDATA[NH]]></given-names>
</name>
<name>
<surname><![CDATA[Magnus]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Implementing machine learning in health care-Addressing ethical challenges]]></article-title>
<source><![CDATA[N Engl J Med]]></source>
<year>2018</year>
<volume>378</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>981-3</page-range></nlm-citation>
</ref>
<ref id="B32">
<label>32</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Saria]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Subbaswamy]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[White]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Opportunities and challenges in implementing AI in health care]]></article-title>
<source><![CDATA[JAMA]]></source>
<year>2021</year>
<volume>326</volume>
<numero>8</numero>
<issue>8</issue>
<page-range>733-40</page-range></nlm-citation>
</ref>
<ref id="B33">
<label>33</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Choi]]></surname>
<given-names><![CDATA[YJ]]></given-names>
</name>
<name>
<surname><![CDATA[Kim]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Park]]></surname>
<given-names><![CDATA[SY]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Regulatory and ethical considerations for artificial intelligence in healthcare]]></article-title>
<source><![CDATA[Health Policy]]></source>
<year>2021</year>
<volume>125</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>1342-50</page-range></nlm-citation>
</ref>
<ref id="B34">
<label>34</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Shapiro]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Ketchum]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Moore]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Protecting patient privacy in the age of artificial intelligence]]></article-title>
<source><![CDATA[JAMA]]></source>
<year>2021</year>
<volume>326</volume>
<numero>7</numero>
<issue>7</issue>
<page-range>667-9</page-range></nlm-citation>
</ref>
<ref id="B35">
<label>35</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Tzeng]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Explainable artificial intelligence in healthcare: A review]]></article-title>
<source><![CDATA[Comput Biol Med]]></source>
<year>2021</year>
<volume>137</volume>
<page-range>104804</page-range></nlm-citation>
</ref>
<ref id="B36">
<label>36</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Agarwal]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Zook]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Chapman]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Addressing health disparities in the era of AI: Challenges and solutions]]></article-title>
<source><![CDATA[Health Informatics J]]></source>
<year>2022</year>
<volume>28</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>234-46</page-range></nlm-citation>
</ref>
<ref id="B37">
<label>37</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kwon]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Song]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Long-term outcomes of AI-based clinical decision support systems]]></article-title>
<source><![CDATA[J Biomed Inform]]></source>
<year>2021</year>
<volume>118</volume>
<page-range>103830</page-range></nlm-citation>
</ref>
<ref id="B38">
<label>38</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hinton]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[LeCun]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Bengio]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning]]></article-title>
<source><![CDATA[Nature]]></source>
<year>2015</year>
<volume>521</volume>
<numero>7553</numero>
<issue>7553</issue>
<page-range>436-44</page-range></nlm-citation>
</ref>
<ref id="B39">
<label>39</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ganapathy]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Mishra]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Agarwal]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Future directions for personalized treatment using AI in healthcare]]></article-title>
<source><![CDATA[Nat Rev Drug Discov]]></source>
<year>2022</year>
<volume>21</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>228-39</page-range></nlm-citation>
</ref>
<ref id="B40">
<label>40</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Smith]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Doe]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Brown]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Advances in AI for cancer detection]]></article-title>
<source><![CDATA[Journal of Medical AI]]></source>
<year>2022</year>
<volume>45</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>123-30</page-range></nlm-citation>
</ref>
<ref id="B41">
<label>41</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jones]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[AI in cardiology: Enhancing accuracy]]></article-title>
<source><![CDATA[Cardiology Today]]></source>
<year>2021</year>
<volume>67</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>210-8</page-range></nlm-citation>
</ref>
<ref id="B42">
<label>42</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Brown]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Patel]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Challenges in rare disease diagnosis using AI]]></article-title>
<source><![CDATA[Rare Diseases Journal]]></source>
<year>2020</year>
<volume>29</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>95-102</page-range></nlm-citation>
</ref>
<ref id="B43">
<label>43</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Williams]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Green]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Ethical implications of AI in healthcare]]></article-title>
<source><![CDATA[Healthcare Ethics Review]]></source>
<year>2020</year>
<volume>38</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>45-52</page-range></nlm-citation>
</ref>
<ref id="B44">
<label>44</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kumar]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Garcia]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Transparency in AI algorithms]]></article-title>
<source><![CDATA[Journal of Health Informatics]]></source>
<year>2019</year>
<volume>33</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>341-7</page-range></nlm-citation>
</ref>
<ref id="B45">
<label>45</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Thompson]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Hernandez]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Implementation of AI in low-resource settings]]></article-title>
<source><![CDATA[Global Health Innovation]]></source>
<year>2019</year>
<volume>14</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>201-9</page-range></nlm-citation>
</ref>
<ref id="B46">
<label>46</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Martin]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Wright]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Quality assessment tools for AI studies]]></article-title>
<source><![CDATA[Research Methods in AI]]></source>
<year>2018</year>
<volume>22</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>355-60</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
