Analyzing explainable AI in healthcare and the pharmaceutical industry:
Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications...
Gespeichert in:
| Weitere Verfasser: | , , , , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hershey, Pennsylvania
IGI Global
2024
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| Schlagworte: | |
| Online-Zugang: | DE-91 DE-898 DE-1050 Volltext |
| Zusammenfassung: | Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions.This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making. |
| Beschreibung: | 1 Online-Ressource (294 Seiten) |
| ISBN: | 9798369354704 |
| DOI: | 10.4018/979-8-3693-5468-1 |
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| 520 | |a Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions.This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making. | ||
| 650 | 4 | |a Artificial intelligence |x Medical applications | |
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| 700 | 1 | |a M. K., Nallakaruppan |d 1982- |4 edt | |
| 700 | 1 | |a Milanova, Mariofanna G. |4 edt | |
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| discipline | Informatik Wirtschaftswissenschaften Medizin |
| doi_str_mv | 10.4018/979-8-3693-5468-1 |
| format | Electronic eBook |
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| illustrated | Not Illustrated |
| indexdate | 2024-12-17T19:01:35Z |
| institution | BVB |
| isbn | 9798369354704 |
| language | English |
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| physical | 1 Online-Ressource (294 Seiten) |
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| spelling | Analyzing explainable AI in healthcare and the pharmaceutical industry Veena Grover, Balamurugan Balusamy, Nallakaruppan M.K., Vijay Anand, Mariofanna Milanovaeditor Analyzing explainable artificial intelligence in healthcare and the pharmaceutical industry Hershey, Pennsylvania IGI Global 2024 1 Online-Ressource (294 Seiten) txt rdacontent c rdamedia cr rdacarrier Healthcare and pharmaceuticals are rapidly advancing with technological innovations, and the lack of understanding of AI algorithms poses a significant challenge in these fields. The need for more transparency in AI decision-making processes raises concerns about accountability, ethical implications, and regulatory compliance. As stakeholders in these critical sectors seek clarity and understanding, Analyzing Explainable AI in Healthcare and the Pharmaceutical Industry provides a reliable resource to discover new solutions.This book serves as a comprehensive guide, unraveling the complexities of explainable artificial intelligence (XAI) and its pivotal role in transforming healthcare and pharmaceutical practices. Demystifying AI algorithms and revealing their decision-making mechanisms equips readers with the foundational knowledge needed to confidently navigate AI integration in these domains. From healthcare professionals to policymakers, its insights cater to a diverse audience, fostering cross-disciplinary collaboration and facilitating informed decision-making. Artificial intelligence Medical applications Anand, Vijay edt Balusamy, Balamurugan edt Grover, Veena edt M. K., Nallakaruppan 1982- edt Milanova, Mariofanna G. edt Erscheint auch als Druck-Ausgabe 9798369354681 https://doi.org/10.4018/979-8-3693-5468-1 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Analyzing explainable AI in healthcare and the pharmaceutical industry Artificial intelligence Medical applications |
| title | Analyzing explainable AI in healthcare and the pharmaceutical industry |
| title_alt | Analyzing explainable artificial intelligence in healthcare and the pharmaceutical industry |
| title_auth | Analyzing explainable AI in healthcare and the pharmaceutical industry |
| title_exact_search | Analyzing explainable AI in healthcare and the pharmaceutical industry |
| title_full | Analyzing explainable AI in healthcare and the pharmaceutical industry Veena Grover, Balamurugan Balusamy, Nallakaruppan M.K., Vijay Anand, Mariofanna Milanovaeditor |
| title_fullStr | Analyzing explainable AI in healthcare and the pharmaceutical industry Veena Grover, Balamurugan Balusamy, Nallakaruppan M.K., Vijay Anand, Mariofanna Milanovaeditor |
| title_full_unstemmed | Analyzing explainable AI in healthcare and the pharmaceutical industry Veena Grover, Balamurugan Balusamy, Nallakaruppan M.K., Vijay Anand, Mariofanna Milanovaeditor |
| title_short | Analyzing explainable AI in healthcare and the pharmaceutical industry |
| title_sort | analyzing explainable ai in healthcare and the pharmaceutical industry |
| topic | Artificial intelligence Medical applications |
| topic_facet | Artificial intelligence Medical applications |
| url | https://doi.org/10.4018/979-8-3693-5468-1 |
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