Matches in SemOpenAlex for { <https://semopenalex.org/work/W4293243996> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W4293243996 endingPage "306" @default.
- W4293243996 startingPage "294" @default.
- W4293243996 abstract "La Inteligencia Artificial (IA) tiene el impacto actual que tuvo la electricidad; y los datos, su materia prima, son el nuevo petróleo de la era moderna. Encontrar el valor de ello en el contexto de su utilidad clínica son el vínculo que acerca las ciencias de la computación a las ciencias de la salud. La toma de decisiones basadas en datos propios apoyada en algoritmos computacionales que “aprenden” a resolver un problema con grandes cantidades de datos está llevando a la medicina personalizada y de precisión a tener un rol cada vez más relevante. La cirugía no se escapa de ello. Con tecnologías que parecen ser futurista y lejanas, y en ocasiones confusas, es un deber de la divulgación científica publicar el estado del arte de una realidad con la que convivimos a diario. Conocer las bases de la computación desde las publicaciones de Alan Turing en 1937, permite comprender mejor por qué estamos asistiendo hoy a un momento histórico en que confluyen un gran volumen de datos con un gran poder computacional, que ha llevado al desarrollo actual de estas técnicas que hoy vemos transversalmente en todas las industrias, como en la salud. Es por ello que en esta revisión se pretende reunir y aclarar los conceptos más relevantes de la ciencia de datos en general, enlazado con sus aplicaciones y desarrollo en medicina y cirugía cardíaca. Con ello, se pretende lograr un acercamiento, al menos teórico, a todo el potencial que las técnicas modernas en el cómputo de datos permiten. Artificial Intelligence (AI) has the current impact that electricity had; and data, its raw material, is the new oil of the modern age. Finding the value of it in the context of its clinical utility is the link that brings computer science closer to health science. Decision-making based on proprietary data supported by computational algorithms that “learn” to solve a problem with large amounts of data is leading personalized and precision medicine to play an increasingly relevant role. Surgery is no exception. With technologies that seem to be futuristic and distant, and sometimes confusing, it is a duty of popular science to publish the state of the art of a reality with which we live daily. Knowing the bases of the computer since from publications of Alan Turing in 1937, allows us to better understand why we are witnessing today a historical moment in which a large volume of data converges with a great computational power, which has led to the current development of these techniques, that today we see transversally in all industries, such as in health. That is why this review aims to gather and clarify the most relevant concepts of data science in general, linked to its applications and development in medicine and cardiac surgery. With this, it is intended to achieve an approach, at least theoretical, to the full potential that modern techniques in data computation allow." @default.
- W4293243996 created "2022-08-27" @default.
- W4293243996 creator A5078536269 @default.
- W4293243996 date "2022-05-01" @default.
- W4293243996 modified "2023-10-14" @default.
- W4293243996 title "Proyecciones de la ciencia de datos en la cirugía cardíaca" @default.
- W4293243996 cites W1641476759 @default.
- W4293243996 cites W1974369017 @default.
- W4293243996 cites W1976773836 @default.
- W4293243996 cites W2001771035 @default.
- W4293243996 cites W2039818644 @default.
- W4293243996 cites W2089485759 @default.
- W4293243996 cites W2128326189 @default.
- W4293243996 cites W2137914002 @default.
- W4293243996 cites W2143235696 @default.
- W4293243996 cites W2164269479 @default.
- W4293243996 cites W2185907055 @default.
- W4293243996 cites W2346178339 @default.
- W4293243996 cites W2519007024 @default.
- W4293243996 cites W2525984666 @default.
- W4293243996 cites W2571536841 @default.
- W4293243996 cites W2580456502 @default.
- W4293243996 cites W2610332124 @default.
- W4293243996 cites W2625625371 @default.
- W4293243996 cites W2745975212 @default.
- W4293243996 cites W2750898199 @default.
- W4293243996 cites W2755943579 @default.
- W4293243996 cites W2771699637 @default.
- W4293243996 cites W2783734843 @default.
- W4293243996 cites W2790209545 @default.
- W4293243996 cites W2791385109 @default.
- W4293243996 cites W2794717203 @default.
- W4293243996 cites W2809487627 @default.
- W4293243996 cites W2885740121 @default.
- W4293243996 cites W2886353729 @default.
- W4293243996 cites W2886503076 @default.
- W4293243996 cites W2887277110 @default.
- W4293243996 cites W2887388803 @default.
- W4293243996 cites W2894773715 @default.
- W4293243996 cites W2905209797 @default.
- W4293243996 cites W2919115771 @default.
- W4293243996 cites W2921303908 @default.
- W4293243996 cites W2953251344 @default.
- W4293243996 cites W2980966386 @default.
- W4293243996 cites W2986224545 @default.
- W4293243996 cites W2994543800 @default.
- W4293243996 cites W3091364893 @default.
- W4293243996 cites W3098949126 @default.
- W4293243996 cites W3103685091 @default.
- W4293243996 doi "https://doi.org/10.1016/j.rmclc.2022.05.007" @default.
- W4293243996 hasPublicationYear "2022" @default.
- W4293243996 type Work @default.
- W4293243996 citedByCount "0" @default.
- W4293243996 crossrefType "journal-article" @default.
- W4293243996 hasAuthorship W4293243996A5078536269 @default.
- W4293243996 hasBestOaLocation W42932439961 @default.
- W4293243996 hasConcept C138885662 @default.
- W4293243996 hasConcept C142362112 @default.
- W4293243996 hasConcept C15708023 @default.
- W4293243996 hasConcept C17744445 @default.
- W4293243996 hasConceptScore W4293243996C138885662 @default.
- W4293243996 hasConceptScore W4293243996C142362112 @default.
- W4293243996 hasConceptScore W4293243996C15708023 @default.
- W4293243996 hasConceptScore W4293243996C17744445 @default.
- W4293243996 hasIssue "3" @default.
- W4293243996 hasLocation W42932439961 @default.
- W4293243996 hasOpenAccess W4293243996 @default.
- W4293243996 hasPrimaryLocation W42932439961 @default.
- W4293243996 hasRelatedWork W1531601525 @default.
- W4293243996 hasRelatedWork W2748952813 @default.
- W4293243996 hasRelatedWork W2758277628 @default.
- W4293243996 hasRelatedWork W2899084033 @default.
- W4293243996 hasRelatedWork W2948807893 @default.
- W4293243996 hasRelatedWork W3173606202 @default.
- W4293243996 hasRelatedWork W3183948672 @default.
- W4293243996 hasRelatedWork W4387497383 @default.
- W4293243996 hasRelatedWork W2778153218 @default.
- W4293243996 hasRelatedWork W3110381201 @default.
- W4293243996 hasVolume "33" @default.
- W4293243996 isParatext "false" @default.
- W4293243996 isRetracted "false" @default.
- W4293243996 workType "article" @default.