{"id":60234,"date":"2026-03-02T19:11:25","date_gmt":"2026-03-02T19:11:25","guid":{"rendered":"https:\/\/emergeamericas.com\/session\/the-invisible-patient-designing-equitable-ai-for-the-health-system-of-tomorrow\/"},"modified":"2026-09-16T02:24:47","modified_gmt":"2026-09-16T02:24:47","slug":"the-invisible-patient-designing-equitable-ai-for-the-health-system-of-tomorrow","status":"publish","type":"session","link":"https:\/\/emergeamericas.com\/es\/session\/the-invisible-patient-designing-equitable-ai-for-the-health-system-of-tomorrow\/","title":{"rendered":"El paciente invisible: Dise\u00f1ar una IA equitativa para el sistema sanitario del ma\u00f1ana"},"content":{"rendered":"","protected":false},"excerpt":{"rendered":"

La inteligencia artificial est\u00e1 transformando la atenci\u00f3n sanitaria, pero no a todos por igual. A medida que la IA se integra en los flujos de trabajo cl\u00ednicos, las herramientas de triaje y las plataformas de salud del consumidor, los riesgos de exclusi\u00f3n aumentan r\u00e1pidamente. Las poblaciones infrarrepresentadas, las experiencias sanitarias emocionalmente complejas y las afecciones que no encajan en las estructuras de codificaci\u00f3n tradicionales suelen estar ausentes de los conjuntos de datos y las decisiones sobre productos que dan forma a la atenci\u00f3n digital. Este panel explora lo que sucede cuando desplegamos la IA sanitaria sin dise\u00f1ar intencionadamente para la inclusi\u00f3n. \u00bfC\u00f3mo se traducen las lagunas de datos en lagunas de resultados? \u00bfCu\u00e1les son los riesgos \u00e9ticos y financieros de ampliar los sistemas sesgados? \u00bfY qui\u00e9n asume la responsabilidad cuando pacientes invisibles pasan desapercibidos para la IA? Reuniendo la innovaci\u00f3n de las startups, el liderazgo responsable de la IA y la inversi\u00f3n sanitaria institucional, esta conversaci\u00f3n examina c\u00f3mo construir sistemas de IA que ampl\u00eden la visibilidad, mejoren los resultados e integren la equidad en la propia arquitectura de la atenci\u00f3n.<\/p>","protected":false},"featured_media":0,"template":"","meta":{"_acf_changed":false,"_lmt_disableupdate":"","_lmt_disable":"","_links_to":"","_links_to_target":""},"tags":[503],"stage":[508],"topic":[473,377,395,391],"speaker-year":[],"class_list":["post-60234","session","type-session","status-publish","hentry","tag-503","stage-emerge-health-stage","topic-tech-for-enterprise","topic-ai","topic-fintech","topic-healthtech"],"acf":[],"yoast_head":"\nThe Invisible Patient: Designing Equitable AI for the Health System of Tomorrow - eMerge Americas<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/emergeamericas.com\/es\/session\/the-invisible-patient-designing-equitable-ai-for-the-health-system-of-tomorrow\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"The Invisible Patient: Designing Equitable AI for the Health System of Tomorrow\" \/>\n<meta property=\"og:description\" content=\"Artificial intelligence is reshaping healthcare, but not everyone is being reshaped equally. As AI becomes embedded into clinical workflows, triage tools, and consumer health platforms, the risks of exclusion scale rapidly. Underrepresented populations, emotionally complex health experiences, and conditions that don\u2019t fit traditional coding structures are often absent from the datasets and product decisions shaping digital care. This panel explores what happens when we deploy health AI without intentionally designing for inclusion. How do data gaps translate into outcome gaps? What are the ethical and financial risks of scaling biased systems? And who bears responsibility when invisible patients remain unseen by AI? 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