دورية أكاديمية
Synthetic Data and Its Utility in Pathology and Laboratory Medicine.
| العنوان: | Synthetic Data and Its Utility in Pathology and Laboratory Medicine. |
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| المؤلفون: | Pantanowitz J; Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania., Manko CD; Guthrie Clinic Robert Packer Hospital; Geisinger Commonwealth School of Medicine, Guthrie, Pennsylvania., Pantanowitz L; Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania., Rashidi HH; Computational Pathology and AI Center of Excellence (CPACE), University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania; Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania. Electronic address: rashidihh@upmc.edu. |
| المصدر: | Laboratory investigation; a journal of technical methods and pathology [Lab Invest] 2024 Aug; Vol. 104 (8), pp. 102095. Date of Electronic Publication: 2024 Jun 24. |
| نوع المنشور: | Journal Article; Review |
| اللغة: | English |
| بيانات الدورية: | Publisher: Elsevier Inc Country of Publication: United States NLM ID: 0376617 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1530-0307 (Electronic) Linking ISSN: 00236837 NLM ISO Abbreviation: Lab Invest Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: 2023- : [New York] : Elsevier Inc. Original Publication: Baltimore : Williams & Wilkins |
| مواضيع طبية MeSH: | Machine Learning*, Humans ; Pathology ; Artificial Intelligence |
| مستخلص: | In our rapidly expanding landscape of artificial intelligence, synthetic data have become a topic of great promise and also some concern. This review aimed to provide pathologists and laboratory professionals with a primer on the role of synthetic data and how it may soon shape the landscape within our field. Using synthetic data presents many advantages but also introduces a milieu of new obstacles and limitations. This review aimed to provide pathologists and laboratory professionals with a primer on the general concept of synthetic data and its potential to transform our field. By leveraging synthetic data, we can help accelerate the development of various machine learning models and enhance our medical education and research/quality study needs. This review explored the methods for generating synthetic data, including rule-based, machine learning model-based and hybrid approaches, as they apply to applications within pathology and laboratory medicine. We also discussed the limitations and challenges associated with such synthetic data, including data quality, malicious use, and ethical bias/concerns and challenges. By understanding the potential benefits (ie, medical education, training artificial intelligence programs, and proficiency testing, etc) and limitations of this new data realm, we can not only harness its power to improve patient outcomes, advance research, and enhance the practice of pathology but also become readily aware of their intrinsic limitations. (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.) |
| فهرسة مساهمة: | Keywords: artificial intelligence; data simulation; generative AI; laboratory medicine; machine learning models; pathology artificial intelligence; pathology education; synthetic data |
| تواريخ الأحداث: | Date Created: 20240626 Date Completed: 20240822 Latest Revision: 20240822 |
| رمز التحديث: | 20240823 |
| DOI: | 10.1016/j.labinv.2024.102095 |
| PMID: | 38925488 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1530-0307 |
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| DOI: | 10.1016/j.labinv.2024.102095 |