Is the Time Right to Start Using Digital Pathology and Artificial Intelligence for the Diagnosis of Lymphoma?

Salama, Mohamed E.; Macon, William R.; Pantanowitz, Liron

doi:10.4103/jpi.jpi_16_20

Cited by 8 publications

(7 citation statements)

References 5 publications

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“…Many professionals are involved in the introduction of AI in DP, ranging from the bioengineer to the pathologist up to the biomedical laboratory technician. There is also no doubt that AI could represent a serious opportunity for the DP laboratories [ 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 ]. It is, however, the time to investigate the full introduction in the routine.…”

Section: Discussionmentioning

confidence: 99%

“…We dedicated particular attention to the critical issues, given that AI will rely heavily on it. In the same study, we highlighted the opportunities and the challenges of AI according to the most recent studies [ 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 ]. Some important development guidelines have been identified.…”

Section: Introductionmentioning

confidence: 96%

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Artificial Intelligence in Digital Pathology: What Is the Future? Part 2: An Investigation on the Insiders

et al. 2021

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Motivation: This study deals with the introduction of artificial intelligence (AI) in digital pathology (DP). The study starts from the highlights of a companion paper. Objective: The aim was to investigate the consensus and acceptance of the insiders on this issue. Procedure: An electronic survey based on the standardized package Microsoft Forms (Microsoft, Redmond, WA, USA) was proposed to a sample of biomedical laboratory technicians (149 admitted in the study, 76 males, 3 females, mean age 44.2 years). Results: The survey showed no criticality. It highlighted (a) the good perception of the basic training on both groups, and (b) a uniformly low perceived knowledge of AI (as arisen from the graded questions). Expectations, perceived general impact, perceived changes in the work-flow, and worries clearly emerged in the study. Conclusions: The of AI in DP is an unstoppable process, as well as the increase of the digitalization in the health domain. Stakeholders must not look with suspicion towards AI, which can represent an important resource, but should invest in monitoring and consensus training initiatives based also on electronic surveys.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 96%

Artificial Intelligence in Digital Pathology: What Is the Future? Part 2: An Investigation on the Insiders

et al. 2021

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“…( digital pathology [Title]) AND ( artificial intelligence [Title]) currently reports 17 works [ 6 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ].…”

Section: Towards the Revolution Of The Digital Pathology And Artificial Intelligencementioning

confidence: 99%

“…There is currently optimism about the opportunities of ANNs, as has been highlighted above in the studies [ 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 ]. There are several difficulties with deploying AI tools in practice depending on the expectance and the objectives of the pathologist.…”

Section: Towards the Revolution Of The Digital Pathology And Artificial Intelligencementioning

confidence: 99%

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Artificial Intelligence in Digital Pathology: What Is the Future? Part 1: From the Digital Slide Onwards

Giovagnoli

Giansanti

2021

Healthcare

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This commentary aims to address the field of Artificial intelligence (AI) in Digital Pathology (DP) both in terms of the global situation and research perspectives. It has four polarities. First, it revisits the evolutions of digital pathology with particular care to the two fields of the digital cytology and the digital histology. Second, it illustrates the main fields in the employment of AI in DP. Third, it looks at the future directions of the research challenges from both a clinical and technological point of view. Fourth, it discusses the transversal problems among these challenges and implications and introduces the immediate work to implement.

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Use of Artificial Intelligence in Implementing Mainstream Precision Medicine to Improve Traditional Symptom-driven Practice of Medicine: Allowing Early Interventions and Tailoring better-personalised Cancer Treatments

Luvhengo

Molefi

Δημητριου

et al. 2023

Artificial Intelligence and Precision Oncology

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Is the Time Right to Start Using Digital Pathology and Artificial Intelligence for the Diagnosis of Lymphoma?

Cited by 8 publications

References 5 publications

Artificial Intelligence in Digital Pathology: What Is the Future? Part 2: An Investigation on the Insiders

Artificial Intelligence in Digital Pathology: What Is the Future? Part 2: An Investigation on the Insiders

Artificial Intelligence in Digital Pathology: What Is the Future? Part 1: From the Digital Slide Onwards

Use of Artificial Intelligence in Implementing Mainstream Precision Medicine to Improve Traditional Symptom-driven Practice of Medicine: Allowing Early Interventions and Tailoring better-personalised Cancer Treatments

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