The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment
Precision medicine is emerging as an integral component in delivering care in the health system leading to better diagnosis and optimizing the treatment of patients. This growth is due to the new technologies in the data science field that have led to the ability to model complex diseases. Precision...
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| Format: | article |
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2022
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| Online Access: | https://hdl.handle.net/11073/32317 |
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| _version_ | 1864513444218142720 |
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| author | Badr, Yara |
| author2 | Kader, Lamis Abdul Shamayleh, Abdulrahim |
| author2_role | author author |
| author_facet | Badr, Yara Kader, Lamis Abdul Shamayleh, Abdulrahim |
| author_role | author |
| dc.creator.none.fl_str_mv | Badr, Yara Kader, Lamis Abdul Shamayleh, Abdulrahim |
| dc.date.none.fl_str_mv | 2022-04-03 2025-11-19T09:41:32Z 2025-11-19T09:41:32Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | Badr, Y., Abdul Kader, L., & Shamayleh, A. (2024). The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment. Journal of Personalized Medicine, 14(4), 383. https://doi.org/10.3390/jpm14040383 2075-4426 https://hdl.handle.net/11073/32317 10.3390/jpm14040383 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | MDPI |
| dc.relation.none.fl_str_mv | https://doi.org/10.3390/jpm14040383 |
| dc.rights.none.fl_str_mv | Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
| dc.subject.none.fl_str_mv | Precision medicine Big data Challenges Opportunities Benefits Stakeholders Solutions Applications |
| dc.title.none.fl_str_mv | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment |
| dc.type.none.fl_str_mv | Peer-Reviewed Published version info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | Precision medicine is emerging as an integral component in delivering care in the health system leading to better diagnosis and optimizing the treatment of patients. This growth is due to the new technologies in the data science field that have led to the ability to model complex diseases. Precision medicine is based on genomics and omics facilities that provide information about molecular proteins and biomarkers that could lead to discoveries for the treatment of patients suffering from various diseases. However, the main problems related to precision medicine are the ability to analyze, interpret, and integrate data. Hence, there is a lack of smooth transition from conventional to precision medicine. Therefore, this work reviews the limitations and discusses the benefits of overcoming them if big data tools are utilized and merged with precision medicine. The results from this review indicate that most of the literature focuses on the challenges rather than providing flexible solutions to adapt big data to precision medicine. As a result, this paper adds to the literature by proposing potential technical, educational, and infrastructural solutions in big data for a better transition to precision medicine. |
| format | article |
| id | aus_5279eeb9506738f170fc405b3f839d68 |
| identifier_str_mv | Badr, Y., Abdul Kader, L., & Shamayleh, A. (2024). The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment. Journal of Personalized Medicine, 14(4), 383. https://doi.org/10.3390/jpm14040383 2075-4426 10.3390/jpm14040383 |
| language_invalid_str_mv | en |
| network_acronym_str | aus |
| network_name_str | aus |
| oai_identifier_str | oai:repository.aus.edu:11073/32317 |
| publishDate | 2022 |
| publisher.none.fl_str_mv | MDPI |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
| spelling | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient TreatmentBadr, YaraKader, Lamis AbdulShamayleh, AbdulrahimPrecision medicineBig dataChallengesOpportunitiesBenefitsStakeholdersSolutionsApplicationsPrecision medicine is emerging as an integral component in delivering care in the health system leading to better diagnosis and optimizing the treatment of patients. This growth is due to the new technologies in the data science field that have led to the ability to model complex diseases. Precision medicine is based on genomics and omics facilities that provide information about molecular proteins and biomarkers that could lead to discoveries for the treatment of patients suffering from various diseases. However, the main problems related to precision medicine are the ability to analyze, interpret, and integrate data. Hence, there is a lack of smooth transition from conventional to precision medicine. Therefore, this work reviews the limitations and discusses the benefits of overcoming them if big data tools are utilized and merged with precision medicine. The results from this review indicate that most of the literature focuses on the challenges rather than providing flexible solutions to adapt big data to precision medicine. As a result, this paper adds to the literature by proposing potential technical, educational, and infrastructural solutions in big data for a better transition to precision medicine.MDPI2025-11-19T09:41:32Z2025-11-19T09:41:32Z2022-04-03Peer-ReviewedPublished versioninfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfBadr, Y., Abdul Kader, L., & Shamayleh, A. (2024). The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment. Journal of Personalized Medicine, 14(4), 383. https://doi.org/10.3390/jpm140403832075-4426https://hdl.handle.net/11073/3231710.3390/jpm14040383enhttps://doi.org/10.3390/jpm14040383Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/oai:repository.aus.edu:11073/323172025-11-19T11:31:27Z |
| spellingShingle | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment Badr, Yara Precision medicine Big data Challenges Opportunities Benefits Stakeholders Solutions Applications |
| status_str | publishedVersion |
| title | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment |
| title_full | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment |
| title_fullStr | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment |
| title_full_unstemmed | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment |
| title_short | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment |
| title_sort | The Use of Big Data in Personalized Healthcare to Reduce Inventory Waste and Optimize Patient Treatment |
| topic | Precision medicine Big data Challenges Opportunities Benefits Stakeholders Solutions Applications |
| url | https://hdl.handle.net/11073/32317 |