[HTML][HTML] Diagnostic Accuracy of Machine-Learning Models on Predicting Chemo-Brain in Breast Cancer Survivors Previously Treated with Chemotherapy: A Meta …
A Turcu-Stiolica, M Bogdan, EA Dumitrescu… - International Journal of …, 2022 - mdpi.com
We performed a meta-analysis of chemo-brain diagnostic, pooling sensitivities, and
specificities in order to assess the accuracy of a machine-learning (ML) algorithm in breast …
specificities in order to assess the accuracy of a machine-learning (ML) algorithm in breast …
[HTML][HTML] Weakly supervised learning with positive and unlabeled data for automatic brain tumor segmentation
D Wolf, S Regnery, R Tarnawski, B Bobek-Billewicz… - Applied Sciences, 2022 - mdpi.com
Featured Application The proposed solution provides a quick approach for the annotation of
the necessary training data to create an application-specific machine learning model that …
the necessary training data to create an application-specific machine learning model that …
A scaling up approach: a research agenda for medical imaging analysis with applications in deep learning
Medical anomaly identification using machine learning is a significant subject that has
received a lot of attention. Artificial neural networks' successor, deep learning, is a well …
received a lot of attention. Artificial neural networks' successor, deep learning, is a well …
A hybrid random forest classifier for chronic kidney disease prediction from 2D ultrasound kidney images
Chronic kidney disease (CKD) is one of the causes of mortality in almost all countries across
the globe and the notable thing is its asymptomatic nature in the early stages. This disease …
the globe and the notable thing is its asymptomatic nature in the early stages. This disease …
Genetic Algorithm Based Feature Selection and Optimized Edge Detection for Brain Tumor Detection
N Thota, M Vallapuri, V Bhavana - 2023 7th International …, 2023 - ieeexplore.ieee.org
This paper presents a novel approach for brain tumor detection using Steady-State Genetic
Algorithms for filter optimization and feature selection. The proposed method utilizes two …
Algorithms for filter optimization and feature selection. The proposed method utilizes two …
High-performance Intelligent Systems for Real-time Medical Imaging
Health is always the first thing to be taken care of particularly when a human being is taken
into consideration. Most of the people are unaware of hidden diseases inside their bodies …
into consideration. Most of the people are unaware of hidden diseases inside their bodies …
[PDF][PDF] A comparative analysis of segmentation techniques for malignant tumour detection
C Duma, Y Singh - Sacair 2023, 2023 - 2023.sacair.org.za
This study aimed to compare three segmentation techniques—U-Net, Random Forest, and
Fuzzy C-Means—for malignant tumour detection in medical images. We used a publicly …
Fuzzy C-Means—for malignant tumour detection in medical images. We used a publicly …
[图书][B] Improving deep neural network training with batch size and learning rate optimization for head and neck tumor segmentation on 2D and 3D medical images
Z Douglas - 2022 - search.proquest.com
Medical imaging is a key tool used in healthcare to diagnose and prognose patients by
aiding the detection of a variety of diseases and conditions. In practice, medical image …
aiding the detection of a variety of diseases and conditions. In practice, medical image …
[PDF][PDF] U-Net: Convolutional Network for Segmentation with DIC-C2DH-HeLa Dataset
U Kazemi, MH Shakoor - kdip.ir
Image segmentation is a basic issue in machine vision. One of the important tasks of
machine vision and image processing is to recognize the pattern and one of the most …
machine vision and image processing is to recognize the pattern and one of the most …