Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine
Critical illness refers to severe diseases or conditions where health status changes rapidly and may pose an immediate threat to life within a short period of time. The key to successful treatment of critically ill patients involves various aspects of diagnosis, including early prediction of adverse...
Tallennettuna:
| Aineistotyyppi: | Online |
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| Kieli: | englanti |
| Julkaistu: |
MDPI - Multidisciplinary Digital Publishing Institute
2024
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| Aiheet: | |
| Linkit: | ONIX_20240514_9783725809097_547 |
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| _version_ | 1869521322683400192 |
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| collection | Directory of Open Access Books |
| description | Critical illness refers to severe diseases or conditions where health status changes rapidly and may pose an immediate threat to life within a short period of time. The key to successful treatment of critically ill patients involves various aspects of diagnosis, including early prediction of adverse events, accurate identification of pathogens, and differential diagnosis of symptoms. Critically ill patients typically generate vast amounts of data from medical equipment such as bedside monitors, ventilators, and renal replacement therapy devices. Handling such large volumes of data is challenging for human intuition alone. Artificial intelligence can learn complex data structures to acquire knowledge and insights, thereby profoundly impacting the management of critically ill patients. In this context, we have organized this Special Issue to explore the application of artificial intelligence in the management of major diseases, aiming to significantly advance future healthcare. In this Special Issue, researchers from various countries and regions have explored the application of artificial intelligence in critical care, covering aspects such as diagnosis, management, and prognosis. Overall, these studies elucidate the transformative impact of artificial intelligence and machine learning on medical diagnosis and prognosis, heralding a new era of precision medicine that holds promise for improving patient outcomes and optimizing healthcare services. |
| format | Online |
| id | doab-20.500.12854ir-137932 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| publisher | MDPI - Multidisciplinary Digital Publishing Institute |
| publisherStr | MDPI - Multidisciplinary Digital Publishing Institute |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1379322024-05-14T14:58:49Z Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine Zhang, Zhongheng machine learning postoperative death prediction model neonatal pain on-site assessment artificial intelligence blood sampling real-world data intensive care unit COVID-19 early prediction clinical biomarkers appendicitis diagnosis fuzzy logic decision making acute kidney injury serum electrolyte neonatal pain assessment inter-rater variability neonatal intensive care units neonatal nursing pain management pneumonia ventilator associated clinical decision system PICU burn patient prognosis prolonged hospital stay skin graft needed adverse complications hospital information systems traumatic brain injury mortality computer-assisted system sepsis explainable artificial intelligence biomarker n/a thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXT Computer applications in industry and technology Critical illness refers to severe diseases or conditions where health status changes rapidly and may pose an immediate threat to life within a short period of time. The key to successful treatment of critically ill patients involves various aspects of diagnosis, including early prediction of adverse events, accurate identification of pathogens, and differential diagnosis of symptoms. Critically ill patients typically generate vast amounts of data from medical equipment such as bedside monitors, ventilators, and renal replacement therapy devices. Handling such large volumes of data is challenging for human intuition alone. Artificial intelligence can learn complex data structures to acquire knowledge and insights, thereby profoundly impacting the management of critically ill patients. In this context, we have organized this Special Issue to explore the application of artificial intelligence in the management of major diseases, aiming to significantly advance future healthcare. In this Special Issue, researchers from various countries and regions have explored the application of artificial intelligence in critical care, covering aspects such as diagnosis, management, and prognosis. Overall, these studies elucidate the transformative impact of artificial intelligence and machine learning on medical diagnosis and prognosis, heralding a new era of precision medicine that holds promise for improving patient outcomes and optimizing healthcare services. 2024-05-14T14:58:44Z 2024-05-14T14:58:44Z 2024 book ONIX_20240514_9783725809097_547 9783725809097 9783725809103 https://directory.doabooks.org/handle/20.500.12854/137932 eng application/octet-stream Attribution-NonCommercial-NoDerivatives 4.0 International https://mdpi.com/books/pdfview/book/9197 https://mdpi.com/books/pdfview/book/9197 MDPI - Multidisciplinary Digital Publishing Institute 10.3390/books978-3-7258-0910-3 10.3390/books978-3-7258-0910-3 46cabcaa-dd94-4bfe-87b4-55023c1b36d0 9783725809097 9783725809103 152 open access |
| spellingShingle | machine learning postoperative death prediction model neonatal pain on-site assessment artificial intelligence blood sampling real-world data intensive care unit COVID-19 early prediction clinical biomarkers appendicitis diagnosis fuzzy logic decision making acute kidney injury serum electrolyte neonatal pain assessment inter-rater variability neonatal intensive care units neonatal nursing pain management pneumonia ventilator associated clinical decision system PICU burn patient prognosis prolonged hospital stay skin graft needed adverse complications hospital information systems traumatic brain injury mortality computer-assisted system sepsis explainable artificial intelligence biomarker n/a thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXT Computer applications in industry and technology Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine |
| title | Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine |
| title_full | Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine |
| title_fullStr | Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine |
| title_full_unstemmed | Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine |
| title_short | Application of Artificial Intelligence to Advance Individualized Diagnosis and Treatment in Emergency and Critical Care Medicine |
| title_sort | application of artificial intelligence to advance individualized diagnosis and treatment in emergency and critical care medicine |
| topic | machine learning postoperative death prediction model neonatal pain on-site assessment artificial intelligence blood sampling real-world data intensive care unit COVID-19 early prediction clinical biomarkers appendicitis diagnosis fuzzy logic decision making acute kidney injury serum electrolyte neonatal pain assessment inter-rater variability neonatal intensive care units neonatal nursing pain management pneumonia ventilator associated clinical decision system PICU burn patient prognosis prolonged hospital stay skin graft needed adverse complications hospital information systems traumatic brain injury mortality computer-assisted system sepsis explainable artificial intelligence biomarker n/a thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXT Computer applications in industry and technology |
| topic_facet | machine learning postoperative death prediction model neonatal pain on-site assessment artificial intelligence blood sampling real-world data intensive care unit COVID-19 early prediction clinical biomarkers appendicitis diagnosis fuzzy logic decision making acute kidney injury serum electrolyte neonatal pain assessment inter-rater variability neonatal intensive care units neonatal nursing pain management pneumonia ventilator associated clinical decision system PICU burn patient prognosis prolonged hospital stay skin graft needed adverse complications hospital information systems traumatic brain injury mortality computer-assisted system sepsis explainable artificial intelligence biomarker n/a thema EDItEUR::U Computing and Information Technology::UX Applied computing::UXT Computer applications in industry and technology |
| url | ONIX_20240514_9783725809097_547 |