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A comparative analysis of classical machine learning and deep learning techniques for predicting lung cancer survivability
Lung cancer, one of the deadliest forms of cancer, can significantly improve patient survival
rates by 60–70% if detected in its early stages. The prediction of lung cancer patient survival …
rates by 60–70% if detected in its early stages. The prediction of lung cancer patient survival …
Monkeypox recognition and prediction from visuals using deep transfer learning-based neural networks
As the globe struggles to recover from COVID-19, the monkeypox virus has emerged as a
new global pandemic threat. Monkeypox cases are still being reported daily from different …
new global pandemic threat. Monkeypox cases are still being reported daily from different …
Fuzzy clustering algorithm for university students' psychological fitness and performance detection
H Han - Heliyon, 2023 - cell.com
Students' psychological fitness is unavoidable, hindering personal development, social
interactions, peer influence, and adolescence. Academic stress may be the most dominant …
interactions, peer influence, and adolescence. Academic stress may be the most dominant …
Forecasting of sea surface temperature in eastern tropical pacific by a hybrid multiscale spatial–temporal model combining error correction map
G Gao, B Yao, Z Li, D Duan… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Sea surface temperature (SST) is one of the most important parameters in the global ocean-
atmosphere system. Predicting SST can help to analyze and identify extreme weather and …
atmosphere system. Predicting SST can help to analyze and identify extreme weather and …
Deep learning-based model using DensNet201 for mobile user interface evaluation
M Soui, Z Haddad - International Journal of Human–Computer …, 2023 - Taylor & Francis
Human-centered AI plays a vital role in ensuring that human capabilities and ideas are
tailored to meet efficiently the data requirements. The main idea is focusing on making …
tailored to meet efficiently the data requirements. The main idea is focusing on making …
Accurate and robust ammonia level forecasting of aeration tanks using long short-term memory ensembles: A comparative study of Adaboost and Bagging …
H Shi, A Wei, Y Zhu, K Tang, H Hu, N Li - Journal of Environmental …, 2024 - Elsevier
As wastewater treatment aeration systems are embracing innovative solutions to data
management for operational sustainability, deep learning approaches like long short-term …
management for operational sustainability, deep learning approaches like long short-term …
Comparison of the performance of machine learning techniques in the prediction of employee
Human Resources' purpose is to assign the best people to the right job at the right time, train
and qualify them, and provide evaluation methods to track their performance and safeguard …
and qualify them, and provide evaluation methods to track their performance and safeguard …
An improved bagging ensemble in predicting mental disorder using hybridized random forest-artificial neural network model
Abstract Machine Learning majorly provides the process of collecting, identifying, pre-
processing, training, validating and visualization of data. This study identifies the problem of …
processing, training, validating and visualization of data. This study identifies the problem of …
AESRSA: a new cryptography key for electronic health record security
When compared to old paper record systems, privacy concerns are likely the most significant
impediment to the adoption of electronic health record (EHR) systems, which are regarded …
impediment to the adoption of electronic health record (EHR) systems, which are regarded …
An improved expeditious meta-heuristic clustering method for classifying student psychological issues with homogeneous characteristics
MS Shaikh, X Dong, G Zheng, C Wang, Y Lin - Mathematics, 2024 - mdpi.com
Nowadays, cluster analyses are widely used in mental health research to categorize student
stress levels. However, conventional clustering methods experience challenges with large …
stress levels. However, conventional clustering methods experience challenges with large …