Big Data Analytics in Healthcare
- Autores
- Del Giorgio Solfa, Federico; Simonato, Fernando Rogelio
- Año de publicación
- 2023
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research.
- Materia
-
Ciencias de la Computación e Información
Big Data Analytics
Machine Learning
Patient Outcomes
Healthcare Delivery
Artificial Intelligence (AI) - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/11967
Ver los metadatos del registro completo
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Big Data Analytics in HealthcareDel Giorgio Solfa, FedericoSimonato, Fernando RogelioCiencias de la Computación e InformaciónBig Data AnalyticsMachine LearningPatient OutcomesHealthcare DeliveryArtificial Intelligence (AI)Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research.2023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/11967enginfo:eu-repo/semantics/altIdentifier/doi/10.54489/ijcim.v3i1.235info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:40:21Zoai:digital.cic.gba.gob.ar:11746/11967Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:40:21.774CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
Big Data Analytics in Healthcare |
title |
Big Data Analytics in Healthcare |
spellingShingle |
Big Data Analytics in Healthcare Del Giorgio Solfa, Federico Ciencias de la Computación e Información Big Data Analytics Machine Learning Patient Outcomes Healthcare Delivery Artificial Intelligence (AI) |
title_short |
Big Data Analytics in Healthcare |
title_full |
Big Data Analytics in Healthcare |
title_fullStr |
Big Data Analytics in Healthcare |
title_full_unstemmed |
Big Data Analytics in Healthcare |
title_sort |
Big Data Analytics in Healthcare |
dc.creator.none.fl_str_mv |
Del Giorgio Solfa, Federico Simonato, Fernando Rogelio |
author |
Del Giorgio Solfa, Federico |
author_facet |
Del Giorgio Solfa, Federico Simonato, Fernando Rogelio |
author_role |
author |
author2 |
Simonato, Fernando Rogelio |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias de la Computación e Información Big Data Analytics Machine Learning Patient Outcomes Healthcare Delivery Artificial Intelligence (AI) |
topic |
Ciencias de la Computación e Información Big Data Analytics Machine Learning Patient Outcomes Healthcare Delivery Artificial Intelligence (AI) |
dc.description.none.fl_txt_mv |
Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research. |
description |
Healthcare professionals decide wisely about personalized medicine, treatment plans, and resource allocation by utilizing big data analytics and machine learning. To guarantee that algorithmic recommendations are impartial and fair, however, ethical issues relating to prejudice and data privacy must be taken into account. Big data analytics and machine learning have a great potential to disrupt healthcare, and as these technologies continue to evolve, new opportunities to reform healthcare and enhance patient outcomes may arise. In order to investigate the patient’s outcomes with empirical evidence, this research was conducted using an online survey to incorporate healthcare professionals, patient’s reviews, and clinical staff. The data were analyzed using SmartPLS 4.0 to predict the structural model. The findings revealed a direct impact as positive influence of using machine learning on healthcare performance and patient outcomes through big data analytics. Moreover, it is evident that this can lead to personalized treatment plans, early interventions, and improved patient outcomes. Additionally, big data analytics can help healthcare providers optimize resource allocation, improve operational efficiency, and reduce costs. The impact of big data analytics on patient outcome and healthcare performance is expected to continue to grow, making it an important area for investment and research. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
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publishedVersion |
dc.identifier.none.fl_str_mv |
https://digital.cic.gba.gob.ar/handle/11746/11967 |
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https://digital.cic.gba.gob.ar/handle/11746/11967 |
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eng |
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eng |
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info:eu-repo/semantics/altIdentifier/doi/10.54489/ijcim.v3i1.235 |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
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