On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Performance analysis for COVID-19 diagnosis using custom and state-of-the-art deep learning models
The modern scientific world continuously endeavors to battle and devise solutions for newly
arising pandemics. One such pandemic which has turned the world's accustomed routine …
arising pandemics. One such pandemic which has turned the world's accustomed routine …
[HTML][HTML] Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study
Background Cardiac arrest (CA) is one of the leading causes of death among patients in the
intensive care unit (ICU). Although many CA prediction models with high sensitivity have …
intensive care unit (ICU). Although many CA prediction models with high sensitivity have …
[HTML][HTML] Learning from Imbalanced Data: Integration of Advanced Resampling Techniques and Machine Learning Models for Enhanced Cancer Diagnosis and …
Simple Summary This research focuses on improving cancer diagnosis and prognosis by
addressing a common problem in data analysis known as class imbalance, where some …
addressing a common problem in data analysis known as class imbalance, where some …
SELF: a stacked-based ensemble learning framework for breast cancer classification
Nowadays, breast cancer is the most prevalent and jeopardous disease in women after lung
cancer. During the past few decades, a substantial amount of cancer cases have been …
cancer. During the past few decades, a substantial amount of cancer cases have been …
Breaking barriers: a statistical and machine learning-based hybrid system for predicting dementia
Introduction: Dementia is a condition (a collection of related signs and symptoms) that
causes a continuing deterioration in cognitive function, and millions of people are impacted …
causes a continuing deterioration in cognitive function, and millions of people are impacted …
A systematic review of breast cancer detection using machine learning and deep learning
Cancer develops when few cells in the body develop abnormally propagate across different
regions within the body. Cancer in breast occurs because certain cells in the breast expand …
regions within the body. Cancer in breast occurs because certain cells in the breast expand …
Identifying environmental information disclosure manipulation behavior via machine learning
X Cai, J Wan, YY Jiang, N Zhou, L Wang… - Environment …, 2024 - Springer
Corporate environmental information disclosure manipulation (EIDM) has a high level of
concealment, which brings great challenges to the identification and judgment of …
concealment, which brings great challenges to the identification and judgment of …
[HTML][HTML] Developing an LSTM model to identify surgical site infections using electronic healthcare records
Recently, hospitals and healthcare providers have made efforts to reduce surgical site
infections as they are a major cause of surgical complications, a prominent reason for …
infections as they are a major cause of surgical complications, a prominent reason for …
Auxiliary Diagnosis of Breast Cancer Based on Machine Learning and Hybrid Strategy
H Chen, K Mei, Y Zhou, N Wang, G Cai - IEEE Access, 2023 - ieeexplore.ieee.org
Breast cancer has replaced lung cancer as the number one cancer among women
worldwide. In this paper, we take breast cancer as the research object, and pioneer a hybrid …
worldwide. In this paper, we take breast cancer as the research object, and pioneer a hybrid …