Latest AI and machine learning research in pathology for healthcare professionals.
OBJECTIVE: To develop and investigate a deep learning model with data integration of ultrasound cont...
It is challenging to diagnose drowning in autopsy even with the help of post-mortem multi-slice comp...
Screening of lymph node metastases in colorectal cancer (CRC) can be a cumbersome task, but it is am...
BACKGROUND AND OBJECTIVE: Current studies based on digital biopsy images have achieved satisfactory ...
OBJECTIVE: Early detection and precise diagnosis of breast cancer (BC) plays an essential part in en...
A long-standing challenge in pneumonia diagnosis is recognizing the pathological lung texture, espec...
Currently, the active surveillance of men with favorable intermediate-risk localized prostate cancer...
DNA as an informational polymer has, for the past 30 years, progressively become an essential molecu...
Thyroid cancer is the most common endocrine cancer. Papillary thyroid cancer (PTC) is the most preva...
The micronucleus (MN) assay is used worldwide by regulatory bodies to evaluate chemicals for genetic...
Nowadays, morphology and molecular analyses at the single-cell level have a fundamental role in unde...
Microscopic analysis of breast cancer images is the primary task in diagnosing cancer malignancy. Re...
BACKGROUND: The histological diagnosis of alveolar echinococcosis can be challenging. Decision suppo...
Congenital heart defect (CHD) refers to the overall structural abnormality of the heart or large blo...
BACKGROUND: Accurate pathological diagnosis of invasion depth and histologic grade is key for clinic...
Clinical data on robot-assisted radical prostatectomy (RARP) performed with the new Hugo robot-assis...
Acquisition of a standard section is a prerequisite for ultrasound diagnosis. For a long time, there...
OBJECTIVES: To determine whether bSSFP images are useful for visualizing prostatic lesionsin MRI-gui...
Lung cancer is one of the malignant tumors with the highest incidence and mortality in the world. Th...
OBJECTIVES: This study aims to develop and evaluate the deep learning-based classification model for...
Recently, deep learning using convolutional neural networks (CNNs) has yielded consistent results in...