Digital pathology has gone through considerable technical advances during the past few
years and certain aspects of digital diagnostics have been widely and swiftly adopted in …

Numerous machine learning (ML) models have been developed for breast cancer using
various types of data. Successful external validation (EV) of ML models is important …

Low-and middle-income countries (LMICs) represent a big source of data not only for
endemic diseases but also for neoplasms. Data is the fuel which drives the modern era …

This paper discusses some overlooked challenges faced when working with machine
learning models for histopathology and presents a novel opportunity to support" Learning …

Objective: To validate the concordance of automated detection of Ki67 in digital images of
breast cancer with the manual eyeball/hotspot method. Study Design: Descriptive study …

Introduction Adequate and timely access to pathology services is a key to scale up cancer
control, however, there is an extremely shortage of pathologists in Tanzania. Telepathology …

As one of the leading technological advances in histopathology in recent years, digital
pathology and the move towards fully digitised workflows is transforming clinical practice …

Introduction Colorectal cancer (CRC) constitutes around 10% of global cancer diagnoses
and death due to cancer. Treatment involves the surgical resection of the tumor and regional …

Pathology as a medical discipline, on the one hand, studies the etiology and occurrence
mechanism of diseases and provides an important theoretical basis for human beings to …

Determinar, a partir da literatura vigente, as evidências científicas sobre o uso da patologia
digital e computacional na prática clínica, considerando benefícios, limitações e …