Involvement of machine learning for breast cancer image classification: a survey

AA Nahid, Y Kong - Computational and mathematical methods …, 2017 - Wiley Online Library
Breast cancer is one of the largest causes of women's death in the world today. Advance
engineering of natural image classification techniques and Artificial Intelligence methods …

Screening for cardiac contractile dysfunction using an artificial intelligence–enabled electrocardiogram

ZI Attia, S Kapa, F Lopez-Jimenez, PM McKie… - Nature medicine, 2019 - nature.com
Asymptomatic left ventricular dysfunction (ALVD) is present in 3–6% of the general
population, is associated with reduced quality of life and longevity, and is treatable when …

Development and validation of a deep-learning model to screen for hyperkalemia from the electrocardiogram

CD Galloway, AV Valys, JB Shreibati… - JAMA …, 2019 - jamanetwork.com
Importance For patients with chronic kidney disease (CKD), hyperkalemia is common,
associated with fatal arrhythmias, and often asymptomatic, while guideline-directed …

Machine learning phenotyping of scarred myocardium from cine in hypertrophic cardiomyopathy

J Mancio, F Pashakhanloo… - European Heart …, 2022 - academic.oup.com
Aims Cardiovascular magnetic resonance (CMR) with late-gadolinium enhancement (LGE)
is increasingly being used in hypertrophic cardiomyopathy (HCM) for diagnosis, risk …

[图书][B] Real-Time Data Acquisition in Human Physiology: Real-Time Acquisition, Processing, and Interpretation—A MATLAB-Based Approach

D Bansal - 2021 - books.google.com
Real-Time Data Acquisition in Human Physiology: Real-Time Acquisition, Processing, and
Interpretation—A MATLAB-Based Approach focuses on the design and development of a …

Local Binary Patterns Descriptor Based on Sparse Curvelet Coefficients for False‐Positive Reduction in Mammograms

MM Pawar, SN Talbar… - Journal of healthcare …, 2018 - Wiley Online Library
Breast Cancer is the most prevalent cancer among women across the globe. Automatic
detection of breast cancer using Computer Aided Diagnosis (CAD) system suffers from false …

Mammogram image preprocessing using intensity range based partitioned cumulative distribution function

D Senguttuvan, S Pichai - The Journal of Analysis, 2023 - Springer
Timely Diagnosis of breast cancer plays a crucial role in reducing the mortality rate of the
victims. Mammography is a proven imaging modality to detect the presence or on-set of …

Background preserved and feature-oriented contrast improvement using weighted cumulative distribution function for digital mammograms

S Dhamodharan, S Pichai - International Conference on mathematical …, 2021 - Springer
Digital mammography is an inevitable source for the early detection of breast cancer. The
limitations of this imaging modality tend to impede the contrast and brightness of digital …

A survey of approaches in Deep Learning techniques for the detection and classification of mammography abnormalities

CGR Flores, JCP Ortega… - 2022 19th …, 2022 - ieeexplore.ieee.org
Mammography is currently the most widely used laboratory study for the early detection of
precursor abnormalities of breast cancer, which is one of the main causes of mortality …

Novel approach to locate region of interest in mammograms for Breast cancer

BV Divyashree, GH Kumar - arXiv preprint arXiv:1811.07818, 2018 - arxiv.org
Locating region of interest for breast cancer masses in the mammographic image is a
challenging problem in medical image processing. In this research work, the keen idea is to …