A novel multi-neural ensemble approach for cancer diagnosis
Cancer is a complex worldwide health concern that resulted in 10 million cancer deaths in
2018; hence, early cancer detection is crucial. Early detection involves developing more …
2018; hence, early cancer detection is crucial. Early detection involves developing more …
A two-stage adaptive thresholding segmentation for noisy low-contrast images
J Song, W Jiao, K Lankowicz, Z Cai, H Bi - Ecological informatics, 2022 - Elsevier
Image recognition is the process of recognizing and classifying objects with machine
learning algorithms. Image binarization is the first and most challenging step in image …
learning algorithms. Image binarization is the first and most challenging step in image …
Special issue “The advance of solid tumor research in China”: Prognosis prediction for stage II colorectal cancer by fusing computed tomography radiomics and deep …
Currently, the prognosis assessment of stage II colorectal cancer (CRC) remains a difficult
clinical problem; therefore, more accurate prognostic predictors must be developed. In our …
clinical problem; therefore, more accurate prognostic predictors must be developed. In our …
Quantifying the cell morphology and predicting biological behavior of signet ring cell carcinoma using deep learning
Q Da, S Deng, J Li, H Yi, X Huang, X Yang, T Yu… - Scientific reports, 2022 - nature.com
Signet ring cell carcinoma (SRCC) is a malignant tumor of the digestive system. This tumor
has long been considered to be poorly differentiated and highly invasive because it has a …
has long been considered to be poorly differentiated and highly invasive because it has a …
Analysis of Colorectal and Gastric Cancer Classification: A Mathematical Insight Utilizing Traditional Machine Learning Classifiers
Cancer remains a formidable global health challenge, claiming millions of lives annually.
Timely and accurate cancer diagnosis is imperative. While numerous reviews have explored …
Timely and accurate cancer diagnosis is imperative. While numerous reviews have explored …
Advancements in traditional machine learning techniques for detection and diagnosis of fatal cancer types: Comprehensive review of biomedical imaging datasets
Accurate cancer detection and diagnosis are imperative for advancing patient outcomes and
mitigating mortality rates. This extensive review scrutinizes the progress within the domain of …
mitigating mortality rates. This extensive review scrutinizes the progress within the domain of …
The application of metal artifact reduction methods on computed tomography scans for radiotherapy applications: A literature review
S Puvanasunthararajah, D Fontanarosa… - Journal of Applied …, 2021 - Wiley Online Library
Metal artifact reduction (MAR) methods are used to reduce artifacts from metals or metal
components in computed tomography (CT). In radiotherapy (RT), CT is the most used …
components in computed tomography (CT). In radiotherapy (RT), CT is the most used …
Prognostic image-based quantification of CD8CD103 T cell subsets in high-grade serous ovarian cancer patients
ST Paijens, A Vledder, D Loiero, EW Duiker… - …, 2021 - Taylor & Francis
ABSTRACT CD103-positive tissue resident memory-like CD8+ T cells (CD8CD103 TRM)
are associated with improved prognosis across malignancies, including high-grade serous …
are associated with improved prognosis across malignancies, including high-grade serous …
Prostate cancer prognosis using multi-layer perceptron and class balancing techniques
Prostate malignancy is one of the most common malignancies. Early prediction of a cancer
diagnosis can upsurge the endurance rate of cancer patients. The advancement of cancer …
diagnosis can upsurge the endurance rate of cancer patients. The advancement of cancer …
Machine learning in neuro-oncology: Toward novel development fields
V Di Nunno, M Fordellone, G Minniti, S Asioli… - Journal of Neuro …, 2022 - Springer
Abstract Purpose Artificial Intelligence (AI) involves several and different techniques able to
elaborate a large amount of data responding to a specific planned outcome. There are …
elaborate a large amount of data responding to a specific planned outcome. There are …