Enhancing the early detection of chronic kidney disease: a robust machine learning model

MS Arif, A Mukheimer, D Asif - Big Data and Cognitive Computing, 2023 - mdpi.com
Clinical decision-making in chronic disorder prognosis is often hampered by high variance,
leading to uncertainty and negative outcomes, especially in cases such as chronic kidney …

Enhancing crop recommendation systems with explainable artificial intelligence: a study on agricultural decision-making

MY Shams, SA Gamel, FM Talaat - Neural Computing and Applications, 2024 - Springer
Abstract Crop Recommendation Systems are invaluable tools for farmers, assisting them in
making informed decisions about crop selection to optimize yields. These systems leverage …

Enhancing coffee bean classification: a comparative analysis of pre-trained deep learning models

E Hassan - Neural Computing and Applications, 2024 - Springer
Coffee bean production can encounter challenges due to fluctuations in global coffee prices,
impacting the economic stability of some countries that heavily depend on coffee production …

QSAR Modeling for Predicting Beta-Secretase 1 Inhibitory Activity in Alzheimer's Disease with Support Vector Regression

TR Noviandy, GM Idroes, TE Tallei… - Malacca …, 2024 - heca-analitika.com
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive
decline, with the accumulation of β-amyloid (Aβ) plaques playing a key role in its …

Optimization Techniques for Asthma Exacerbation Prediction Models: A Systematic Literature Review

DA Aliyu, EAP Akhir, Y Saidu, S Adamu, KI Umar… - IEEE …, 2024 - ieeexplore.ieee.org
Asthma exacerbations pose a significant global health concern, necessitating effective
predictive models to anticipate and manage these events. This systematic literature review …

Deepfake detection using convolutional vision transformers and convolutional neural networks

AH Soudy, O Sayed, H Tag-Elser, R Ragab… - Neural Computing and …, 2024 - Springer
Deepfake technology has rapidly advanced in recent years, creating highly realistic fake
videos that can be difficult to distinguish from real ones. The rise of social media platforms …

An explainable multi-model stacked classifier approach for predicting hepatitis C drug candidates

TR Noviandy, A Maulana, GM Idroes, R Suhendra… - Sci, 2024 - search.proquest.com
Hepatitis C virus (HCV) infection affects over 71 million people worldwide, leading to severe
liver diseases, including cirrhosis and hepatocellular carcinoma. The virus's high mutation …

Enhanced heart disease prediction through hybrid CNN-TLBO-GA optimization: a comparative study with conventional CNN and optimized CNN using FPO algorithm

RP Ram Kumar, S Raju, E Annapoorna… - Cogent …, 2024 - Taylor & Francis
Cardiovascular diseases (CD), or heart diseases (HD), lead to approximately 17.9 million
deaths each year, constituting 32% of global fatalities. Early detection and appropriate …

Investigations on cardiovascular diseases and predicting using machine learning algorithms

RP Ram Kumar, S Polepaka, V Manasa… - Cogent …, 2024 - Taylor & Francis
Detection of heart diseases (HD) at an early stage diminishes the mortality rate. However,
handling huge data is cumbersome for physicians. Hence, there is a need for a tool …

ANN-based deep collocation method for natural convection in porous media

S Kumar, BVR Kumar, SK Murthy - Neural Computing and Applications, 2024 - Springer
A deep collocation method (DCM) is proposed for studying the natural convection
phenomenon in the porous media (NCPM). The buoyancy-driven convection analysis inside …