Combining CNN features with voting classifiers for optimizing performance of brain tumor classification
Simple Summary This study presents a hybrid model for brain tumor detection. Contrary to
manual featur extraction, features extracted from a convolutional neural network are used to …
manual featur extraction, features extracted from a convolutional neural network are used to …
Improving prediction of cervical cancer using knn imputed smote features and multi-model ensemble learning approach
H Karamti, R Alharthi, AA Anizi, RM Alhebshi… - Cancers, 2023 - mdpi.com
Simple Summary This paper presents a cervical cancer detection approach where the KNN
Imputer techniques is used to fill the missing values and after that SMOTE upsampled …
Imputer techniques is used to fill the missing values and after that SMOTE upsampled …
[HTML][HTML] A novel approach for breast cancer detection using optimized ensemble learning framework and XAI
Breast cancer (BC) is a common and highly lethal ailment. It stands as the second leading
contributor to cancer-related deaths in women worldwide. The timely identification of this …
contributor to cancer-related deaths in women worldwide. The timely identification of this …
Data-centric automated approach to predict autism spectrum disorder based on selective features and explainable artificial intelligence
Autism spectrum disorder (ASD) is a neurodevelopmental condition marked by notable
challenges in cognitive function, understanding language, recognizing objects, interacting …
challenges in cognitive function, understanding language, recognizing objects, interacting …
Enhancing prediction of brain tumor classification using images and numerical data features
Brain tumors, along with other diseases that harm the neurological system, are a significant
contributor to global mortality. Early diagnosis plays a crucial role in effectively treating brain …
contributor to global mortality. Early diagnosis plays a crucial role in effectively treating brain …
Citation context analysis using combined feature embedding and deep convolutional neural network model
Citation creates a link between citing and the cited author, and the frequency of citation has
been regarded as the basic element to measure the impact of research and knowledge …
been regarded as the basic element to measure the impact of research and knowledge …
Improving prediction of cervical cancer using KNN imputer and multi-model ensemble learning
T Aljrees - Plos one, 2024 - journals.plos.org
Cervical cancer is a leading cause of women's mortality, emphasizing the need for early
diagnosis and effective treatment. In line with the imperative of early intervention, the …
diagnosis and effective treatment. In line with the imperative of early intervention, the …
A Comparison of Machine Learning Models for Mapping Tree Species Using WorldView-2 Imagery in the Agroforestry Landscape of West Africa
Farmland trees are a vital part of the local economy as trees are used by farmers for
fuelwood as well as food, fodder, medicines, fibre, and building materials. As a result …
fuelwood as well as food, fodder, medicines, fibre, and building materials. As a result …
[PDF][PDF] Social media sentiment analysis using convolutional neural network (CNN) dan gated recurrent unit (GRU)
AZR Adam, EB Setiawan - Jurnal Ilmiah Teknik Elektro Komputer …, 2023 - researchgate.net
The advancing technologies are aimed to maximize human performance. One of the great
developments in technology is social media. The social media used in this study is Twitter …
developments in technology is social media. The social media used in this study is Twitter …
Enhancing safety of construction workers in Korea: an integrated text mining and machine learning framework for predicting accident types
JW Yoo, J Park, H Park - International journal of injury control and …, 2024 - Taylor & Francis
Construction workers face a high risk of various occupational accidents, many of which can
result in fatalities. This study aims to develop a prediction model for nine prevalent types of …
result in fatalities. This study aims to develop a prediction model for nine prevalent types of …