Feature extraction has been extensively studied in the machine learning field as it plays a critical role in the success of various practical applications. To uncover compact low-dimensional feature representations with strong generalization and disc...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 16, 2025
Efficient, accurate, and early identification of plant pathogens is crucial for reducing disease spread and ensuring food security. The development of rapid diagnostic methods based on Raman spectroscopy (RS) coupled with machine learning (ML) holds ...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Jul 16, 2025
Carotid ultrasound image segmentation and classification are crucial in assessing the severity of carotid plaques which serve as a major cause of ischemic stroke. Although many methods are employed for carotid plaque segmentation and classification, ...
INTRODUCTION: Heart Disease (HD) stands as the foremost reason for mortality all over the world for both men and women. Millions of people are affected worldwide every year, resulting in numerous fatalities. Timely and precise detection is essential ...
BACKGROUND: The practice of medicine has evolved significantly during the past decade, with the emergence of Machine Learning (ML) that offers the opportunity of personalized patient-tailored care. However, ML models still face some challenges when c...
BACKGROUND: Inferring Gene Regulatory Networks (GRNs) from gene expression data is a pivotal challenge in systems biology. Most existing methods fail to consider the skewed degree distribution of genes, complicating the application of directed graph ...
Mathematical models are conventionally used to understand the of tumor behaviors, but they generally lack in precisely correlating drug efficacy with tumor response. Artificial intelligence (AI) has forged a new avenue in cancer management, but requi...
With human guidance, computers now use machine learning (ML) in artificial intelligence (AI) to learn from data, detect trends, and make predictions. Software can adapt and improve with new information. Imaging scans leverage pattern recognition to p...
To develop a high-performance convolutional neural network (CNN) model for plant image classification automatically, we propose a neural architecture search (NAS) method tailored to multifunctional cells (MFC), termed MFC-NAS. Initially, a search spa...
Microscopic-Diffraction Imaging Flow Cytometry (MDIFC) is a high-throughput, stain-free technology that captures paired microscopic and diffraction images of cellular events, utilizing machine learning for the classification of cell subpopulations. H...
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