Machine-learning-based disease diagnosis: A comprehensive review
Globally, there is a substantial unmet need to diagnose various diseases effectively. The
complexity of the different disease mechanisms and underlying symptoms of the patient …
complexity of the different disease mechanisms and underlying symptoms of the patient …
Diagnostic strategies for breast cancer detection: from image generation to classification strategies using artificial intelligence algorithms
JA Basurto-Hurtado, IA Cruz-Albarran… - Cancers, 2022 - mdpi.com
Simple Summary With the recent advances in the field of artificial intelligence, it has been
possible to develop robust and accurate methodologies that can deliver noticeable results in …
possible to develop robust and accurate methodologies that can deliver noticeable results in …
Artificial intelligence based medical decision support system for early and accurate breast cancer prediction
Feature selection, which picks the optimal subset of characteristics related to the target data
by deleting unnecessary data, is one of the most important aspects of the machine learning …
by deleting unnecessary data, is one of the most important aspects of the machine learning …
[Retracted] Detection of Breast Cancer Using Histopathological Image Classification Dataset with Deep Learning Techniques
Cancer is one of the top causes of mortality, and it arises when cells in the body grow
abnormally, like in the case of breast cancer. For people all around the world, it has now …
abnormally, like in the case of breast cancer. For people all around the world, it has now …
Guaranteeing correctness in Black-Box Machine Learning: A Fusion of Explainable AI and formal methods for Healthcare decision-making
In recent years, Explainable Artificial Intelligence (XAI) has attracted considerable attention
from the research community, primarily focusing on elucidating the opaque decision-making …
from the research community, primarily focusing on elucidating the opaque decision-making …
Breast cancer classification by a new approach to assessing deep neural network-based uncertainty quantification methods
F Hamedani-KarAzmoudehFar… - … Signal Processing and …, 2023 - Elsevier
Deep learning-based approaches have become widespread in medical fields and have
achieved profound success in recent years. Nonetheless, most of these approaches cannot …
achieved profound success in recent years. Nonetheless, most of these approaches cannot …
Artificial intelligence methods available for cancer research
Cancer is a heterogeneous and multifaceted disease with a significant global footprint.
Despite substantial technological advancements for battling cancer, early diagnosis and …
Despite substantial technological advancements for battling cancer, early diagnosis and …
Enhancing breast cancer detection and classification using advanced multi-model features and ensemble machine learning techniques
Breast cancer (BC) is the most common cancer among women, making it essential to have
an accurate and dependable system for diagnosing benign or malignant tumors. It is …
an accurate and dependable system for diagnosing benign or malignant tumors. It is …
An explainable artificial intelligence model for the classification of breast cancer
Breast cancer is the most common cancer among women and globally affects both genders.
The disease arises due to abnormal growth of tissue formed of malignant cells. Early …
The disease arises due to abnormal growth of tissue formed of malignant cells. Early …
Breast cancer diagnosis using hybrid AlexNet-ELM and chimp optimization algorithm evolved by Nelder-mead simplex approach
C Junyue, DQ Zeebaree, C Qingfeng… - … Signal Processing and …, 2023 - Elsevier
This study proposes a Hybrid AlexNet-Extreme Learning Machine (ELM) approach for breast
cancer diagnosis using mammography images. Batch normalization is applied to improve …
cancer diagnosis using mammography images. Batch normalization is applied to improve …