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Pathologists

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Identifying pathological slices of gastric cancer via deep learning.

Journal of the Formosan Medical Association = Taiwan yi zhi
BACKGROUND: The accuracy of histopathology diagnosis largely depends on the pathologist's experience. It usually takes over 10 years to cultivate a senior pathologist, and small numbers of them lead to a high workload for those available. Meanwhile, ...

[Artificial intelligence: a solution for the lack of pathologists?].

Der Pathologe
Given the rapid developments, there is no doubt that artificial intelligence (AI) will substantially impact pathological diagnostics. However, it remains an open question if AI will primarily be another diagnostic tool, such as immunohistochemistry, ...

Assessment of deep learning assistance for the pathological diagnosis of gastric cancer.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Previous studies on deep learning (DL) applications in pathology have focused on pathologist-versus-algorithm comparisons. However, DL will not replace the breadth and contextual knowledge of pathologists; rather, only through their combination may t...

Dual resolution deep learning network with self-attention mechanism for classification and localisation of colorectal cancer in histopathological images.

Journal of clinical pathology
AIMS: Microscopic examination is a basic diagnostic technology for colorectal cancer (CRC), but it is very laborious. We developed a dual resolution deep learning network with self-attention mechanism (DRSANet) which combines context and details for ...

Pathologist-Patient Visits-Revisited.

The American journal of surgical pathology
Direct pathologist-patient encounters are infrequent, but there has been a modest movement toward such interactions in the past 2 decades. The present article places that movement in perspective. It includes a discussion of diverse factors-including ...

Deep learning-based fully automated diagnosis of melanocytic lesions by using whole slide images.

The Journal of dermatological treatment
BACKGROUND: Erroneous diagnoses of melanocytic lesions (benign, atypical, and malignant types) result in inappropriate surgical treatment plans.

A deep learning model for breast ductal carcinoma in situ classification in whole slide images.

Virchows Archiv : an international journal of pathology
The pathological differential diagnosis between breast ductal carcinoma in situ (DCIS) and invasive ductal carcinoma (IDC) is of pivotal importance for determining optimum cancer treatment(s) and clinical outcomes. Since conventional diagnosis by pat...

Semantic annotation for computational pathology: multidisciplinary experience and best practice recommendations.

The journal of pathology. Clinical research
Recent advances in whole-slide imaging (WSI) technology have led to the development of a myriad of computer vision and artificial intelligence-based diagnostic, prognostic, and predictive algorithms. Computational Pathology (CPath) offers an integrat...

[The first data challenge of the french society of pathology: An international competition in 2020, a research tool in A.I. for the future?].

Annales de pathologie
The french society of pathology (SFP) organized in 2020 its first data challenge with the help of Health Data Hub (HDH). The organisation of this event first consisted in recruiting almost 5000 slides of uterus cervical biopsies obtained in 20 pathol...

Computer-assisted mitotic count using a deep learning-based algorithm improves interobserver reproducibility and accuracy.

Veterinary pathology
The mitotic count (MC) is an important histological parameter for prognostication of malignant neoplasms. However, it has inter- and intraobserver discrepancies due to difficulties in selecting the region of interest (MC-ROI) and in identifying or cl...