Literature DB >> 32763920

Current and future applications of artificial intelligence in pathology: a clinical perspective.

Emad A Rakha1, Michael Toss2, Sho Shiino2, Paul Gamble3, Ronnachai Jaroensri3, Craig H Mermel3, Po-Hsuan Cameron Chen3.   

Abstract

During the last decade, a dramatic rise in the development and application of artificial intelligence (AI) tools for use in pathology services has occurred. This trend is often expected to continue and reshape the field of pathology in the coming years. The deployment of computational pathology and applications of AI tools can be considered as a paradigm shift that will change pathology services, making them more efficient and capable of meeting the needs of this era of precision medicine. Despite the success of AI models, the translational process from discovery to clinical applications has been slow. The gap between self-contained research and clinical environment may be too wide and has been largely neglected. In this review, we cover the current and prospective applications of AI in pathology. We examine its applications in diagnosis and prognosis, and we offer insights for considerations that could improve clinical applicability of these tools. Then, we discuss its potential to improve workflow efficiency, and its benefits in pathologist education. Finally, we review the factors that could influence adoption in clinical practices and the associated regulatory processes. © Author(s) (or their employer(s)) 2021. No commercial re-use. See rights and permissions. Published by BMJ.

Keywords:  breast; pathology department, hospital; telepathology

Mesh:

Year:  2020        PMID: 32763920     DOI: 10.1136/jclinpath-2020-206908

Source DB:  PubMed          Journal:  J Clin Pathol        ISSN: 0021-9746            Impact factor:   3.411


  9 in total

Review 1.  Implementation of Artificial Intelligence in Diagnostic Practice as a Next Step after Going Digital: The UMC Utrecht Perspective.

Authors:  Rachel N Flach; Nina L Fransen; Andreas F P Sonnen; Tri Q Nguyen; Gerben E Breimer; Mitko Veta; Nikolas Stathonikos; Carmen van Dooijeweert; Paul J van Diest
Journal:  Diagnostics (Basel)       Date:  2022-04-21

2.  iMIL4PATH: A Semi-Supervised Interpretable Approach for Colorectal Whole-Slide Images.

Authors:  Pedro C Neto; Sara P Oliveira; Diana Montezuma; João Fraga; Ana Monteiro; Liliana Ribeiro; Sofia Gonçalves; Isabel M Pinto; Jaime S Cardoso
Journal:  Cancers (Basel)       Date:  2022-05-18       Impact factor: 6.575

3.  A promising deep learning-assistive algorithm for histopathological screening of colorectal cancer.

Authors:  Cowan Ho; Zitong Zhao; Xiu Fen Chen; Jan Sauer; Sahil Ajit Saraf; Rajasa Jialdasani; Kaveh Taghipour; Aneesh Sathe; Li-Yan Khor; Kiat-Hon Lim; Wei-Qiang Leow
Journal:  Sci Rep       Date:  2022-02-09       Impact factor: 4.379

4.  Assessment of deep learning algorithms to predict histopathological diagnosis of breast cancer: first Moroccan prospective study on a private dataset.

Authors:  H El Agouri; M Azizi; H El Attar; M El Khannoussi; A Ibrahimi; R Kabbaj; H Kadiri; S BekarSabein; S EchCharif; C Mounjid; B El Khannoussi
Journal:  BMC Res Notes       Date:  2022-02-19

5.  Feature Paper Special Issue for Editorial Board Members (EBMs) of Diseases.

Authors:  Maurizio Battino
Journal:  Diseases       Date:  2022-03-22

Review 6.  Prognostic impact of perineural invasion in oral cancer: a systematic review.

Authors:  Debora Modelli Vianna Ocampo Quintana; Rogerio Aparecido Dedivitis; Luiz Paulo Kowalski
Journal:  Acta Otorhinolaryngol Ital       Date:  2022-02       Impact factor: 2.618

7.  RFID analysis of the complexity of cellular pathology workflow-An opportunity for digital pathology.

Authors:  Lisa Browning; Kieron White; Darrin Siiankoski; Richard Colling; Derek Roskell; Eve Fryer; Helen Hemsworth; Sharon Roberts-Gant; Ruud Roelofsen; Jens Rittscher; Clare Verrill
Journal:  Front Med (Lausanne)       Date:  2022-08-01

Review 8.  Developing image analysis methods for digital pathology.

Authors:  Peter Bankhead
Journal:  J Pathol       Date:  2022-05-23       Impact factor: 9.883

Review 9.  CAD systems for colorectal cancer from WSI are still not ready for clinical acceptance.

Authors:  Sara P Oliveira; Pedro C Neto; João Fraga; Diana Montezuma; Ana Monteiro; João Monteiro; Liliana Ribeiro; Sofia Gonçalves; Isabel M Pinto; Jaime S Cardoso
Journal:  Sci Rep       Date:  2021-07-13       Impact factor: 4.379

  9 in total

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