[HTML][HTML] An ensemble approach for classification and prediction of diabetes mellitus using soft voting classifier

S Kumari, D Kumar, M Mittal - International Journal of Cognitive Computing …, 2021 - Elsevier
Diabetes is a dreadful disease identified by escalated levels of glucose in the blood.
Machine learning algorithms help in identification and prediction of diabetes at an early …

Application of deep learning in histopathology images of breast cancer: a review

Y Zhao, J Zhang, D Hu, H Qu, Y Tian, X Cui - Micromachines, 2022 - mdpi.com
With the development of artificial intelligence technology and computer hardware functions,
deep learning algorithms have become a powerful auxiliary tool for medical image analysis …

An integrated approach for monitoring social distancing and face mask detection using stacked ResNet-50 and YOLOv5

IS Walia, D Kumar, K Sharma, JD Hemanth… - Electronics, 2021 - mdpi.com
SARS-CoV-19 is one of the deadliest pandemics the world has witnessed, taking around
5,049,374 lives till now across worldwide and 459,873 in India. To limit its spread numerous …

A Histopathological Image Classification Method Based on Model Fusion in the Weight Space

G Zhang, ZF Lai, YQ Chen, HT Liu, WJ Sun - Applied Sciences, 2023 - mdpi.com
Automatic classification of histopathological images plays an important role in computer-
aided diagnosis systems. The automatic classification model of histopathological images …

Impact of ensemble-based models on cancer classification, its development, and challenges

B Sahu, S Sahu, OP Jena - Machine Learning and Deep Learning …, 2022 - taylorfrancis.com
Ensemble models use numerous learning algorithms in the area of statics and machine
learning to produce more significant predictions that can be accomplished by either of the …

Stock price prediction using bidirectional LSTM with attention

S Biswas - 2022 1st International Conference on AI in …, 2022 - ieeexplore.ieee.org
The stock market is one of the most important topics of today's economy due to its fluctuating
nature and far-reaching impact. Despite the difficulty of mathematical modeling of time …

[PDF][PDF] Breast invasive ductal carcinoma diagnosis using machine learning models and Gabor filter method of histology images

RR Kadhim, MY Kamil - International Journal of Reconfigurable …, 2023 - researchgate.net
Breast cancer is the most common type of cancer in women and the leading cause of death
from a malignant growth in the world. Machine learning methods have been created to help …

Prediction of IDC Breast Cancer by the Application of Transfer Learning with an Ensemble Method

MI Hossain, A Billa, ME Karim - 2023 International Conference …, 2023 - ieeexplore.ieee.org
Cancer mainly is the result of uncontrollable changes in genes. Hence breast cancer is a
result of the unstoppable growth of breast cells. A common type of breast cancer is Invasive …

Automated carcinoma classification using efficient nuclei-based patch selection and deep learning techniques

S Dhivya, S Mohanavalli… - Journal of Intelligent & …, 2023 - content.iospress.com
Breast cancer can be successfully treated if diagnosed at its earliest, though it is considered
as a fatal disease among women. The histopathology slide turned images are the gold …

Various Skin Cancer Classification & Detection using Deep learning

N Tiwari, A Sethia, A Raj… - 2024 10th …, 2024 - ieeexplore.ieee.org
Doctors have previously detected skin cancers and infections with their unaided eyes. But,
since humans make errors, this often ends in inaccurate detection. Even specialists find it …