Supervised machine learning models for liver disease risk prediction
The liver constitutes the largest gland in the human body and performs many different
functions. It processes what a person eats and drinks and converts food into nutrients that …
functions. It processes what a person eats and drinks and converts food into nutrients that …
Machine learning techniques for increasing efficiency of the robot's sensor and control information processing
Real-time systems are widely used in industry, including technological process control
systems, industrial automation systems, SCADA systems, testing, and measuring equipment …
systems, industrial automation systems, SCADA systems, testing, and measuring equipment …
Liver disease classification using histogram-based gradient boosting classification tree with feature selection algorithm
P Theerthagiri - Biomedical Signal Processing and Control, 2025 - Elsevier
Healthcare is the key for everyone to run daily life, and health diagnosing techniques should
be accessible easily. Indeed, the early identification of liver disease will be supportive for …
be accessible easily. Indeed, the early identification of liver disease will be supportive for …
Machine learning methods in predicting patients with suspected myocardial infarction based on short-time HRV data
D Chumachenko, M Butkevych, D Lode, M Frohme… - Sensors, 2022 - mdpi.com
Diagnosis of cardiovascular diseases is an urgent task because they are the main cause of
death for 32% of the world's population. Particularly relevant are automated diagnostics …
death for 32% of the world's population. Particularly relevant are automated diagnostics …
The recognition of speech defects using convolutional neural network
O Pronina, O Piatykop - CTE Workshop Proceedings, 2023 - acnsci.org
The paper proposes a solution to improve the efficiency of recognition of speech defects in
children by processing the sound data of the spectrogram based on convolutional neural …
children by processing the sound data of the spectrogram based on convolutional neural …
Maize crop disease detection using NPNet-19 convolutional neural network
M Nagaraju, P Chawla - Neural Computing and Applications, 2023 - Springer
Convolutional neural network, a strong deep learning technique, is used to detect diseases
and perform image processing, recognition, and disease classification. The neural network …
and perform image processing, recognition, and disease classification. The neural network …
Comparative study of linear regression and SIR models of COVID-19 propagation in Ukraine before vaccination
The global COVID-19 pandemic began in December 2019 and spread rapidly around the
world. Worldwide, more than 230 million people fell ill, 4.75 million cases were fatal. In …
world. Worldwide, more than 230 million people fell ill, 4.75 million cases were fatal. In …
[HTML][HTML] Enhancing cardiovascular risk assessment with advanced data balancing and domain knowledge-driven explainability
F Yang, Y Qiao, P Hajek, MZ Abedin - Expert Systems with Applications, 2024 - Elsevier
In medical risk prediction, such as predicting heart disease, machine learning (ML)
classifiers must achieve high accuracy, precision, and recall to minimize the chances of …
classifiers must achieve high accuracy, precision, and recall to minimize the chances of …
A Machine Learning‐Based Framework for Accurate and Early Diagnosis of Liver Diseases: A Comprehensive Study on Feature Selection, Data Imbalance, and …
The liver is the largest organ of the human body with more than 500 vital functions. In recent
decades, a large number of liver patients have been reported with diseases such as …
decades, a large number of liver patients have been reported with diseases such as …
[PDF][PDF] Neural Technologies for Objects Classification with Mobile Applications
I Sidenko, G Kondratenko… - Journal of Mobile …, 2024 - journals.riverpublishers.com
This paper is related to the study of the features of the neural technologies' application, in
particular, ResNet neural networks for the classification of objects in photographs. The work …
particular, ResNet neural networks for the classification of objects in photographs. The work …