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BC-QNet: A quantum-infused ELM model for breast cancer diagnosis
The timely and accurate diagnosis of breast cancer is pivotal for effective treatment, but
current automated mammography classification methods have their constraints. In this study …
current automated mammography classification methods have their constraints. In this study …
Innovations in stroke identification: A machine learning-based diagnostic model using neuroimages
Cerebrovascular diseases such as stroke are among the most common causes of death and
disability worldwide and are preventable and treatable. Early detection of strokes and their …
disability worldwide and are preventable and treatable. Early detection of strokes and their …
Prediction of Solar PV Power Using Deep Learning With Correlation-Based Signal Synthesis
Enhancement of the dispatching capacity and grid management efficiency requires
knowledge of photovoltaic power generation beforehand. Intrinsically, photovoltaic power …
knowledge of photovoltaic power generation beforehand. Intrinsically, photovoltaic power …
A transfer learning approach for facial paralysis severity detection
Facial paralysis is a debilitating condition that weakens or damages facial muscles resulting
in asymmetric or abnormal facial movements. To aid in the diagnosis and rehabilitation of …
in asymmetric or abnormal facial movements. To aid in the diagnosis and rehabilitation of …
Toward Holistic Energy Management by Electricity Load and Price Forecasting: A Comprehensive Survey
Electricity load and price data pose formidable challenges for forecasting due to their
intricate characteristics, marked by high volatility and non-linearity. Machine learning (ML) …
intricate characteristics, marked by high volatility and non-linearity. Machine learning (ML) …
Lightweight CNN for Detecting Microcalcifications Clusters in Digital Mammograms
Digital mammogram plays a key role in breast cancer screening, with microcalcifications
being an important indicator of an early stage. However, these injuries are difficult to detect …
being an important indicator of an early stage. However, these injuries are difficult to detect …
Residual shallow convolutional neural network to classify microcalcifications clusters in digital mammograms
We introduce a residual shallow Convolutional Neural Network (CNN) designed for
classifying the presence or absence of Microcalcification Clusters (MCCs) in digital …
classifying the presence or absence of Microcalcification Clusters (MCCs) in digital …