INTRODUCTION: Many researchers used machine learning (ML) to predict the prognosis of breast cancer (BC) patients and noticed that the ML model had good individualized prediction performance.
Microscopic analysis of breast cancer images is the primary task in diagnosing cancer malignancy. Recent attempts to automate this task have employed deep learning models whose success has depended on large volumes of data, while acquiring annotated ...
Computer methods and programs in biomedicine
Jan 20, 2023
BACKGROUND AND OBJECTIVE: Deep learning models (DLMs) have been successfully applied in biomedicine primarily using supervised learning with large, annotated databases. However, scarce training resources limit the potential of DLMs for electrocardiog...
Convolutional Neural Networks (CNN) have received a large share of research in mammography image analysis due to their capability of extracting hierarchical features directly from raw data. Recently, Vision Transformers are emerging as viable alterna...
Recognition of handwritten Uchen Tibetan characters input has been considered an efficient way of acquiring mass data in the digital era. However, it still faces considerable challenges due to seriously touching letters and various morphological feat...
Computer methods and programs in biomedicine
Jan 13, 2023
BACKGROUND AND OBJECTIVE: Evaluation of human cognitive workload (CW) helps improve the user experience of human-centered systems. To provide a continuous estimation of the CW, we built a CW recognizer that maps human electroencephalograms (EEGs) to ...
BACKGROUND: Medication errors account for a large proportion of all medical errors. In most homes, patients take a variety of medications for a long period. However, medication errors frequently occur because patients often throw away the containers ...
Data-independent acquisition (DIA) of tandem mass spectrometry spectra has emerged as a promising technology to improve coverage and quantification of proteins in complex mixtures. The success of DIA experiments is dependent on the quality of spectra...
Journal of chemical information and modeling
Jan 3, 2023
Electrophilicity () is one of the most important parameters to understand the reactivity of an organic molecule. Although the theoretical electrophilicity index (ω) has been associated with in a small homologous series, the use of to predict in a ...