4.6 Article

Breast Cancer Prediction Using Fine Needle Aspiration Features and Upsampling with Supervised Machine Learning

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Computer Science, Information Systems

Automated disease diagnosis and precaution recommender system using supervised machine learning

Furqan Rustam et al.

Summary: Similar to many other professions, the medical field has witnessed significant automation in the past decade. However, existing artificial intelligence applications in healthcare still lack the desired accuracy and efficiency. To address this issue, a study introduces an automatic healthcare system that can replace doctors at an initial stage of diagnosis and provide necessary precautions. The system consists of two modules: Module-1 trains machine learning models using disease symptoms dataset, while Module-2 interacts with users through voice input and utilizes trained models for disease prediction and precaution recommendations. The proposed approach achieves an accuracy of 99.9% in real-time evaluation.

MULTIMEDIA TOOLS AND APPLICATIONS (2022)

Article Oncology

Breast Cancer Statistics, 2022

Angela N. Giaquinto et al.

Summary: This article provides an update on female breast cancer statistics in the United States, including data on incidence, mortality, survival, and mammography screening. It shows that breast cancer incidence rates have increased over the past few decades, driven by localized-stage and hormone receptor-positive disease. However, breast cancer mortality rates have been steadily declining since 1989, although at a slower pace in recent years. Despite lower incidence rates, there remains a racial disparity in breast cancer mortality, with higher rates among Black women compared to White women.

CA-A CANCER JOURNAL FOR CLINICIANS (2022)

Article Chemistry, Analytical

Non-Invasive Driver Drowsiness Detection System

Hafeez Ur Rehman Siddiqui et al.

Summary: Drowsiness while driving can lead to accidents, and real-time accurate fatigue detection systems are needed to reduce accident rates. This research utilizes IR-UWB radar to classify drowsy and non-drowsy driver states based on respiration rate, with Support Vector Machine showing the best performance.

SENSORS (2021)

Article Computer Science, Information Systems

Wireless Capsule Endoscopy Bleeding Images Classification Using CNN Based Model

Furqan Rustam et al.

Summary: This study aims to devise a system using a deep neural network approach, named BIR (bleedy image recognizer), for automatic analysis of WCE images to assist practitioners in robust diagnosis. By combining MobileNet with a custom-built CNN model, the system achieved high accuracy, precision, and recall using a dataset of 1650 WCE images.

IEEE ACCESS (2021)

Article Computer Science, Information Systems

Mez: An Adaptive Messaging System for Latency-Sensitive Multi-Camera Machine Vision at the IoT Edge

Anjus George et al.

Summary: Mez is a novel publish-subscribe messaging system designed for latency sensitive multi-camera machine vision applications at the IoT Edge. By dynamically adjusting video frame quality and using image transformation techniques, Mez is able to simultaneously satisfy latency and application accuracy requirements. Additionally, experimental evaluation shows that Mez can tolerate latency variations and maintain application accuracy in IoT Edge systems.

IEEE ACCESS (2021)

Article Health Policy & Services

Primary care physicians and cancer care in Pakistan: A short narrative

Muhammad Mohsin Ali et al.

JOURNAL OF CANCER POLICY (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Distributed Middleware for Edge Vision Systems

Anjus George et al.

2019 IEEE 16TH INTERNATIONAL CONFERENCE ON SMART CITIES: IMPROVING QUALITY OF LIFE USING ICT, IOT AND AI (IEEE HONET-ICT 2019) (2019)

Article Multidisciplinary Sciences

SVM and SVM Ensembles in Breast Cancer Prediction

Min-Wei Huang et al.

PLOS ONE (2017)

Article Computer Science, Artificial Intelligence

Breast cancer diagnosis using Genetically Optimized Neural Network model

Arpit Bhardwaj et al.

EXPERT SYSTEMS WITH APPLICATIONS (2015)

Article Computer Science, Information Systems

Feature selection with SVD entropy: Some modification and extension

Monami Banerjee et al.

INFORMATION SCIENCES (2014)

Article Computer Science, Artificial Intelligence

A support vector machine classifier with rough set-based feature selection for breast cancer diagnosis

Hui-Ling Chen et al.

EXPERT SYSTEMS WITH APPLICATIONS (2011)

Article Computer Science, Artificial Intelligence

An expert system for detection of breast cancer based on association rules and neural network

Murat Karabatak et al.

EXPERT SYSTEMS WITH APPLICATIONS (2009)

Review Computer Science, Artificial Intelligence

Learning from Imbalanced Data

Haibo He et al.

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (2009)

Article Computer Science, Artificial Intelligence

An intelligent system for automated breast cancer diagnosis and prognosis using SVM based classifiers

Ilias Maglogiannis et al.

APPLIED INTELLIGENCE (2009)

Article Computer Science, Artificial Intelligence

Web page classification based on a support vector machine using a weighted vote schema

Rung-Ching Chen et al.

EXPERT SYSTEMS WITH APPLICATIONS (2006)

Article Biochemistry & Molecular Biology

Predicting protein structural class with AdaBoost learner

Bing Niu et al.

PROTEIN AND PEPTIDE LETTERS (2006)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)