Latest AI and machine learning research in pathology for healthcare professionals.
UNLABELLED: Intratumoral heterogeneity arising from tumor evolution poses significant challenges bio...
The traditional manual breast cancer diagnosis method of pathological images is time-consuming and l...
Serial section electron microscopy (ssEM) can provide comprehensive 3D ultrastructural information o...
To diagnose muscle disease, histopathologic evaluation of muscle biopsy is essential. In addition, s...
Electronic Medical Record (EMR) is the data basis of intelligent diagnosis. The diagnosis results of...
Reverberant Shear Wave Elastography (RSWE) is an ultrasound elastography technique that offers great...
We use deep learning methods to predict human induced pluripotent stem cell (hiPSC) formation using ...
Breast conserving surgery aims at the complete removal of malignant lesions while minimizing healthy...
Segmentation of the thoracic region and breast tissues is crucial for analyzing and diagnosing the p...
This paper performs in simulations deep learning (DL) for high quality and high quantitative ultraso...
Accurate segmentation of nuclei is an essential step in analysis of digital histology images for dia...
The global longitudinal strain of the myocardial tissue has been shown to be a better indicator of c...
Transfer learning from ImageNet pretrained weights is widely used when training Deep Learning models...
Whole Slide Images (WSIs) in digital pathology are used to diagnose cancer subtypes. The difference ...
OBJECTIVES: To assess the protective effect of L-carnitine in reducing cisplatin toxicity via estima...
BACKGROUND: Immunophenotypic analysis of cell populations by flow cytometry has an established role ...
Blood velocity inversion based on magnetoelectric effect is helpful for the development of daily mon...
Aiming at the dilemma of expensive and difficult maintenance, lack of technical data and insufficien...
Digitalisation of pathology slides allows pathologists to make diagnoses using a high-resolution com...
Deciphering the cellular composition in genome-wide spatially resolved transcriptomic data is a crit...
Gliomas are the most common neuroepithelial brain tumors, different by various biological tissue typ...