Untangling classification methods for melanoma skin cancer
A Kumar, A Vatsa - Frontiers in big Data, 2022 - frontiersin.org
Skin cancer is the most common cancer in the USA, and it is a leading cause of death
worldwide. Every year, more than five million patients are newly diagnosed in the USA. The …
worldwide. Every year, more than five million patients are newly diagnosed in the USA. The …
Breast Cancer-Risk Factors and Prediction Using Machine-Learning Algorithms and Data Source: A Review of Literature
Breast cancer (BC) is a major health concern worldwide. It is a complex and multifactorial
disease, and identifying its risk factors is crucial for early detection and effective treatment …
disease, and identifying its risk factors is crucial for early detection and effective treatment …
Comparative analysis and visualization of breast cancer using machine learning models
A Rani, N Sharma - 2022 10th International Conference on …, 2022 - ieeexplore.ieee.org
In recent decades, humans especially women are now commonly threatened by breast
cancer, which has a high morbidity and fatality rate. It is challenging for doctors to develop a …
cancer, which has a high morbidity and fatality rate. It is challenging for doctors to develop a …
A Convolutional Neural Network Based Prediction Model for Classification of Skin Cancer Images
There has been an unprecedented rise in the cases of skin diseases since past few decades
owing to several factors. Among several skin diseases, skin cancer has also taken a steep …
owing to several factors. Among several skin diseases, skin cancer has also taken a steep …
Attraction-Repulsion Swarming: A Generalized Framework of t-SNE via Force Normalization and Tunable Interactions
J Lu, J Calder - arxiv preprint arxiv:2411.10617, 2024 - arxiv.org
We propose a new method for data visualization based on attraction-repulsion swarming
(ARS) dynamics, which we call ARS visualization. ARS is a generalized framework that is …
(ARS) dynamics, which we call ARS visualization. ARS is a generalized framework that is …
Supervised Learning Techniques for Sentiment Analysis
Data mining implies the application of techniques of obtaining useful knowledge from a
huge data. Another term for data mining is knowledge discovery from data. For the same …
huge data. Another term for data mining is knowledge discovery from data. For the same …
Simultaneous count data feature selection and clustering using Multinomial Nested Dirichlet Mixture
The elevating effect of the curse of dimensionality in count data has made clustering a
challenging task. This paper solves this by adopting the concept of feature saliency as a …
challenging task. This paper solves this by adopting the concept of feature saliency as a …
An Analysis Employing Various Machine Learning Algorithms for Detection of Malicious URLs
F Rizvi, S Mohi ud din, N Sharma… - International Advanced …, 2022 - Springer
Currently, there are millions and trillions of webpages online. Therefore, in order to protect
their data, users must be able to distinguish between trustworthy and dangerous websites …
their data, users must be able to distinguish between trustworthy and dangerous websites …
Development of an Artificial intelligence Breast Cancer diagnostic tool
RSP de Castro - 2023 - search.proquest.com
Breast cancer poses a global healthcare challenge due to its prevalence and multifactorial
etiology. Despite advances in early detection and treatment, therapeutic approaches like …
etiology. Despite advances in early detection and treatment, therapeutic approaches like …
[PDF][PDF] MSc Applied AI and Data Science
E Iton - 2022 - solent.ac.uk
Breast cancer is one of the major causes of deaths in females worldwide. This project is
focused on creating a system to identify the chances of the disease recurring in both …
focused on creating a system to identify the chances of the disease recurring in both …