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Artificial intelligence in diagnostic pathology.
Shafi, Saba; Parwani, Anil V.
Afiliación
  • Shafi S; Department of Pathology, The Ohio State University Wexner Medical Center, E409 Doan Hall, 410 West 10th Ave, Columbus, OH, 43210, USA.
  • Parwani AV; Department of Pathology, The Ohio State University Wexner Medical Center, E409 Doan Hall, 410 West 10th Ave, Columbus, OH, 43210, USA. anil.parwani@osumc.edu.
Diagn Pathol ; 18(1): 109, 2023 Oct 03.
Article en En | MEDLINE | ID: mdl-37784122
Digital pathology (DP) is being increasingly employed in cancer diagnostics, providing additional tools for faster, higher-quality, accurate diagnosis. The practice of diagnostic pathology has gone through a staggering transformation wherein new tools such as digital imaging, advanced artificial intelligence (AI) algorithms, and computer-aided diagnostic techniques are being used for assisting, augmenting and empowering the computational histopathology and AI-enabled diagnostics. This is paving the way for advancement in precision medicine in cancer. Automated whole slide imaging (WSI) scanners are now rendering diagnostic quality, high-resolution images of entire glass slides and combining these images with innovative digital pathology tools is making it possible to integrate imaging into all aspects of pathology reporting including anatomical, clinical, and molecular pathology. The recent approvals of WSI scanners for primary diagnosis by the FDA as well as the approval of prostate AI algorithm has paved the way for starting to incorporate this exciting technology for use in primary diagnosis. AI tools can provide a unique platform for innovations and advances in anatomical and clinical pathology workflows. In this review, we describe the milestones and landmark trials in the use of AI in clinical pathology with emphasis on future directions.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Patología Clínica / Neoplasias Tipo de estudio: Diagnostic_studies Límite: Humans / Male Idioma: En Revista: Diagn Pathol Asunto de la revista: PATOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Patología Clínica / Neoplasias Tipo de estudio: Diagnostic_studies Límite: Humans / Male Idioma: En Revista: Diagn Pathol Asunto de la revista: PATOLOGIA Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos