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 …
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 …
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 …
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 …
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 …
Mapping the neurodevelopmental predictors of psychopathology
Neuroimaging research has uncovered a multitude of neural abnormalities associated with
psychopathology, but few prediction-based studies have been conducted during …
psychopathology, but few prediction-based studies have been conducted during …
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 …
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 …
Digital psychiatry in Nigeria: A scoping review
JU Onu, TC Onyeka - South African Journal of Psychiatry, 2024 - journals.co.za
Background Mental healthcare workforce shortage in Nigeria poses a major obstacle to
mental health services scale-up. Digital psychiatry may provide a veritable platform to bridge …
mental health services scale-up. Digital psychiatry may provide a veritable platform to bridge …