Machine learning and integrative analysis of biomedical big data
Recent developments in high-throughput technologies have accelerated the accumulation
of massive amounts of omics data from multiple sources: genome, epigenome …
of massive amounts of omics data from multiple sources: genome, epigenome …
LightGBM empowered by whale optimization for thyroid disease detection
Thyroid disorder is a significant source of formulation in medical classification and
prognosis, with onset being a challenging assumption in medical study. The thyroid gland is …
prognosis, with onset being a challenging assumption in medical study. The thyroid gland is …
A multiple multilayer perceptron neural network with an adaptive learning algorithm for thyroid disease diagnosis in the internet of medical things
Medical information systems such as Internet of Medical Things (IoMT) are gained special
attention over recent years. X-ray and MRI images are important sources of information to be …
attention over recent years. X-ray and MRI images are important sources of information to be …
Wind power prediction based on outlier correction, ensemble reinforcement learning, and residual correction
Wind power prediction contributes to clean energy utilization and grid dispatching. In this
study, a wind power prediction model based on outlier correction, ensemble reinforcement …
study, a wind power prediction model based on outlier correction, ensemble reinforcement …
Manifold learning methods for the diagnosis of ovarian cancer
Early detection of ovarian cancer is crucial for a good outlook. Different machine learning
methods have already proven useful to that effect, but using many features and samples …
methods have already proven useful to that effect, but using many features and samples …
A electric power optimal scheduling study of hybrid energy storage system integrated load prediction technology considering ageing mechanism
J Ji, M Zhou, R Guo, J Tang, J Su, H Huang, N Sun… - Renewable Energy, 2023 - Elsevier
This paper proposes a hybrid energy storage system model adapted to industrial
enterprises. The operation of the hybrid energy storage system is optimized during the …
enterprises. The operation of the hybrid energy storage system is optimized during the …
Towards accurate diagnosis of skin lesions using feedforward back propagation neural networks
In the automatic detection framework, there have been many attempts to develop models for
real-time melanoma detection. To effectively discriminate benign and malign skin lesions …
real-time melanoma detection. To effectively discriminate benign and malign skin lesions …
Prediction of ground vibration intensity in mine blasting using the novel hybrid MARS–PSO–MLP model
The present paper's primary goal is to propose a novel hybrid model with high reliability to
predict peak particle velocity (PPV)—a ground vibration evaluation unit in mine blasting …
predict peak particle velocity (PPV)—a ground vibration evaluation unit in mine blasting …
[HTML][HTML] Logistic regression paradigm for training a single-hidden layer feedforward neural network. Application to gene expression datasets for cancer research
S Belciug - Journal of Biomedical Informatics, 2020 - Elsevier
Objective The speed of the diagnosis process is vital in pursuing the trial of curing cancer.
During the last decade, precision medicine evolved by detecting different types of cancer …
During the last decade, precision medicine evolved by detecting different types of cancer …
Parallel versus cascaded logistic regression trained single-hidden feedforward neural network for medical data
S Belciug - Expert Systems with Applications, 2021 - Elsevier
Objective An important step towards a better healthcare system is fast and accurate
diagnosis. In the last decade, the application of intelligent systems in healthcare has led to …
diagnosis. In the last decade, the application of intelligent systems in healthcare has led to …