[HTML][HTML] All you need is data preparation: A systematic review of image harmonization techniques in Multi-center/device studies for medical support systems
Abstract Background and Objectives Artificial intelligence (AI) models trained on multi-
centric and multi-device studies can provide more robust insights and research findings …
centric and multi-device studies can provide more robust insights and research findings …
Application of Machine Learning in Predicting Perioperative Outcomes in Patients with Cancer: A Narrative Review for Clinicians
G Brydges, A Uppal, V Gottumukkala - Current Oncology, 2024 - mdpi.com
This narrative review explores the utilization of machine learning (ML) and artificial
intelligence (AI) models to enhance perioperative cancer care. ML and AI models offer …
intelligence (AI) models to enhance perioperative cancer care. ML and AI models offer …
Impact of h&e stain normalization on deep learning models in cancer image classification: performance, complexity, and trade-offs
Simple Summary This research study investigates the impact of stain normalization on deep
learning models for cancer image classification by evaluating model performance …
learning models for cancer image classification by evaluating model performance …
[HTML][HTML] Performance and limitations of a supervised deep learning approach for the histopathological Oxford Classification of glomeruli with IgA nephropathy
Abstract Background and Objective The Oxford Classification for IgA nephropathy is the
most successful example of an evidence-based nephropathology classification system. The …
most successful example of an evidence-based nephropathology classification system. The …
CytoGAN: Unpaired staining transfer by structure preservation for cytopathology image analysis
With the development of digital pathology, deep learning is increasingly being applied to
endometrial cell morphology analysis for cancer screening. And cytology images with …
endometrial cell morphology analysis for cancer screening. And cytology images with …
[HTML][HTML] SurvIAE: survival prediction with interpretable autoencoders from diffuse large B-Cells lymphoma gene expression data
Abstract Background In Diffuse Large B-Cell Lymphoma (DLBCL), several methodologies
are emerging to derive novel biomarkers to be incorporated in the risk assessment. We …
are emerging to derive novel biomarkers to be incorporated in the risk assessment. We …
A Super-resolution Network for High-Resolution Reconstruction of Landslide Main bodies in Remote sensing Imagery using coordinated attention mechanisms and …
H Zhang, C Ye, Y Zhou, R Tang, R Wei - Remote Sensing, 2023 - mdpi.com
The lack of high-resolution training sets for intelligent landslide recognition using high-
resolution remote sensing images is a major challenge. To address this issue, this paper …
resolution remote sensing images is a major challenge. To address this issue, this paper …
An explainable radiogenomic framework to predict mutational status of KRAS and EGFR in lung adenocarcinoma patients
B Prencipe, C Delprete, E Garolla, F Corallo, M Gravina… - Bioengineering, 2023 - mdpi.com
The complex pathobiology of lung cancer, and its spread worldwide, has prompted research
studies that combine radiomic and genomic approaches. Indeed, the early identification of …
studies that combine radiomic and genomic approaches. Indeed, the early identification of …
Deep learning model with pathological knowledge for detection of colorectal neuroendocrine tumor
K Zheng, J Duan, R Wang, H Chen, H He, X Zheng… - Cell Reports …, 2024 - cell.com
Colorectal neuroendocrine tumors (NETs) differ significantly from colorectal carcinoma
(CRC) in terms of treatment strategy and prognosis, necessitating a cost-effective approach …
(CRC) in terms of treatment strategy and prognosis, necessitating a cost-effective approach …
Generative Adversarial Networks for Stain Normalisation in Histopathology
The rapid growth of digital pathology in recent years has provided an ideal opportunity for
the development of artificial intelligence-based tools to improve the accuracy and efficiency …
the development of artificial intelligence-based tools to improve the accuracy and efficiency …