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Month wise articles
Figures next to the month indicate the number of articles in that month
2022
March
[
1
]
January
[
10
]
2021
December
[
7
]
November
[
9
]
September
[
8
]
August
[
2
]
July
[
1
]
June
[
4
]
May
[
3
]
April
[
4
]
March
[
7
]
February
[
3
]
January
[
6
]
2020
December
[
2
]
November
[
5
]
October
[
3
]
September
[
2
]
August
[
8
]
July
[
4
]
June
[
2
]
May
[
1
]
April
[
3
]
March
[
3
]
February
[
6
]
January
[
1
]
2019
December
[
6
]
November
[
4
]
September
[
4
]
August
[
3
]
July
[
6
]
June
[
1
]
May
[
2
]
April
[
6
]
March
[
3
]
February
[
4
]
January
[
2
]
2018
December
[
10
]
November
[
4
]
October
[
3
]
September
[
4
]
August
[
1
]
July
[
3
]
June
[
5
]
May
[
4
]
April
[
10
]
March
[
2
]
February
[
4
]
2017
December
[
5
]
November
[
4
]
October
[
3
]
September
[
9
]
July
[
5
]
June
[
2
]
May
[
4
]
April
[
6
]
March
[
6
]
February
[
7
]
2016
December
[
7
]
November
[
5
]
October
[
3
]
September
[
7
]
August
[
1
]
July
[
7
]
May
[
8
]
April
[
7
]
March
[
4
]
February
[
2
]
January
[
5
]
2015
November
[
4
]
October
[
5
]
September
[
5
]
August
[
4
]
July
[
3
]
June
[
19
]
May
[
5
]
April
[
1
]
March
[
5
]
February
[
9
]
January
[
3
]
2014
November
[
2
]
October
[
5
]
September
[
4
]
August
[
6
]
July
[
8
]
June
[
1
]
May
[
3
]
March
[
8
]
February
[
3
]
January
[
4
]
2013
December
[
5
]
November
[
2
]
October
[
4
]
September
[
4
]
August
[
3
]
July
[
3
]
June
[
5
]
May
[
7
]
March
[
18
]
February
[
1
]
January
[
1
]
2012
December
[
6
]
November
[
1
]
October
[
4
]
September
[
4
]
August
[
7
]
July
[
2
]
June
[
1
]
May
[
2
]
April
[
7
]
March
[
6
]
February
[
7
]
January
[
13
]
2011
December
[
3
]
November
[
1
]
October
[
7
]
August
[
9
]
July
[
3
]
June
[
7
]
May
[
3
]
March
[
6
]
February
[
8
]
January
[
6
]
2010
December
[
4
]
November
[
1
]
October
[
6
]
September
[
1
]
August
[
6
]
July
[
6
]
May
[
5
]
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Guidelines:
Integrating the health-care enterprise pathology and laboratory medicine guideline for digital pathology interoperability
Rajesh C Dash, Nicholas Jones, Riki Merrick, Gunter Haroske, James Harrison, Craig Sayers, Nick Haarselhorst, Mikael Wintell, Markus D Herrmann, François Macary
J Pathol Inform
2021, 12:16 (24 March 2021)
DOI
:10.4103/jpi.jpi_98_20
Integrating the health-care enterprise (IHE) is an international initiative to promote the use of standards to achieve interoperability among health information technology systems. The Pathology and Laboratory Medicine domain within IHE has brought together subject matter experts, electronic health record vendors, and digital imaging vendors, to initiate development of a series of digital pathology interoperability guidelines, called “integration profiles” within IHE. This effort begins with documentation of common use cases, followed by identification of available data and technology standards best utilized to achieve those use cases. An integration profile that describes the information flow and technology interactions is then published for trial use. Real world testing occurs in “connectathon” events, in which multiple vendors attempt to connect their products following the interoperability guidance parameters set forth in the profile. This paper describes the overarching set of integration profiles, one of which has been published, to support key digital pathology use cases.
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Original Article:
Selection of representative histologic slides in interobserver reproducibility studies: Insights from expert review for ovarian carcinoma subtype classification
Marios A Gavrielides, Brigitte M Ronnett, Russell Vang, Fahime Sheikhzadeh, Jeffrey D Seidman
J Pathol Inform
2021, 12:15 (22 March 2021)
DOI
:10.4103/jpi.jpi_56_20
Background:
Observer studies in pathology often utilize a limited number of representative slides per case, selected and reported in a nonstandardized manner. Reference diagnoses are commonly assumed to be generalizable to all slides of a case. We examined these issues in the context of pathologist concordance for histologic subtype classification of ovarian carcinomas (OCs).
Materials and Methods:
A cohort of 114 OCs consisting of 72 cases with a single representative slide (Group 1) and 42 cases with multiple representative slides (148 slides, 2-“6 sections per case, Group 2) was independently reviewed by three experts in gynecologic pathology (case-based review). In a follow-up study, each individual slide was independently reviewed in a randomized order by the same pathologists (section-based review).
Results:
Average interobserver concordance varied from 100% for Group 1 to 64.3% for Group 2 (86.8% across all cases). Across Group 2, 19 cases (45.2%) had at least one slide classified as a different subtype than the subtype assigned from case-based review, demonstrating the impact of intratumoral heterogeneity. Section-based concordance across individual sections from Group 2 was comparable to case-based concordance for those cases indicating diagnostic challenges at the individual section level. Findings demonstrate the increased diagnostic complexity of heterogeneous tumors that require multiple section sampling and its impact on pathologist performance.
Conclusions:
The proportion of cases with multiple representative slides in cohorts used in validation studies, such as those conducted to evaluate artificial intelligence/machine learning tools, can influence diagnostic performance, and if not accounted for, can cause disparities between research and real-world observations and between research studies. Case selection in validation studies should account for tumor heterogeneity to create balanced datasets in terms of diagnostic complexity.
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Commentary:
Commentary: The digital fate of glomeruli in renal biopsy
Ilaria Girolami, Stefano Marletta, Albino Eccher
J Pathol Inform
2021, 12:14 (22 March 2021)
DOI
:10.4103/jpi.jpi_102_20
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Review Article:
Artificial intelligence in pathology: From prototype to product
André Homeyer, Johannes Lotz, Lars Ole Schwen, Nick Weiss, Daniel Romberg, Henning Höfener, Norman Zerbe, Peter Hufnagl
J Pathol Inform
2021, 12:13 (22 March 2021)
DOI
:10.4103/jpi.jpi_84_20
Modern image analysis techniques based on artificial intelligence (AI) have great potential to improve the quality and efficiency of diagnostic procedures in pathology and to detect novel biomarkers. Despite thousands of published research papers on applications of AI in pathology, hardly any research implementations have matured into commercial products for routine use. Bringing an AI solution for pathology to market poses significant technological, business, and regulatory challenges. In this paper, we provide a comprehensive overview and advice on how to meet these challenges. We outline how research prototypes can be turned into a product-ready state and integrated into the IT infrastructure of clinical laboratories. We also discuss business models for profitable AI solutions and reimbursement options for computer assistance in pathology. Moreover, we explain how to obtain regulatory approval so that AI solutions can be launched as
in vitro
diagnostic medical devices. Thus, this paper offers computer scientists, software companies, and pathologists a road map for transforming prototypes of AI solutions into commercial products.
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Commentary:
Commentary: Leveraging edge computing technology for digital pathology
Mustafa Yousif, Ulysses G J Balis, Anil V Parwani, Liron Pantanowitz
J Pathol Inform
2021, 12:12 (22 March 2021)
DOI
:10.4103/jpi.jpi_112_20
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Editorial:
Virtual mega-meetings: Here to stay?
Lewis A Hassell, Hans J G Hassell
J Pathol Inform
2021, 12:11 (15 March 2021)
DOI
:10.4103/jpi.jpi_99_20
Among the paradigms changed by the COVID-19 pandemic is the traditional academic and educational conference. In the vein of turning lemons into lemonade, many organizations and individuals have discovered ways that this public health necessitated change can be transformed into a boon to both participants and organizations. However, the question of whether this shift becomes permanent, or a component of the future of academic and educational meetings remains to be seen, and likely will depend on the solution to some of the challenges that have not been sweetened by the shift. This editorial draws on experience with a limited scope of virtual meetings in two different disciplines to make the case that the Virtual Mega-Conference is likely to continue to be a part of life in the years ahead.
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Editorial:
Europe unites for the digital transformation of pathology: The role of the new ESDIP
Catarina Eloy, Norman Zerbe, Filippo Fraggetta
J Pathol Inform
2021, 12:10 (12 March 2021)
DOI
:10.4103/jpi.jpi_80_20
The European Society for Digital and Integrative Pathology (ESDIP) was formally founded in 2016 in Berlin. After a well-participated annual general meeting, ESDIP members elected a new active structure for the next term of office. The priority goals of this new and highly motivated team will be to support the digital transformation in the pathology laboratories, to build inter-institutional bridges for cooperation, to establish a solid educational program, and to increase the collaboration with industry partners.
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