Mitochondrial morphology and function are intrinsically linked, indicating the opportunity to predict functions by analyzing morphological features in live-cell imaging. Herein, we introduce MoDL, a deep learning algorithm for mitochondrial image seg...
BACKGROUND: Breast cancer screening plays a pivotal role in early detection and subsequent effective management of the disease, impacting patient outcomes and survival rates.
BACKGROUND: The two most commonly used methods to identify frailty are the frailty phenotype and the frailty index. However, both methods have limitations in clinical application. In addition, methods for measuring frailty have not yet been standardi...
BACKGROUND: The use of natural language processing (NLP) in mental health research is increasing, with a wide range of applications and datasets being investigated.
BACKGROUND: Artificial intelligence advancements have enabled large language models to significantly impact radiology education and diagnostic accuracy.
BACKGROUND: Complete Cytoreduction (CC) in ovarian cancer (OC) has been associated with better outcomes. Outcomes after CC have a multifactorial and interrelated cause that may not be predictable by conventional statistical methods. Artificial intell...
Journal of educational evaluation for health professions
Jan 16, 2025
The peer review process ensures the integrity of scientific research. This is particularly important in the medical field, where research findings directly impact patient care. However, the rapid growth of publications has strained reviewers, causing...
SIGNIFICANCE: Machine learning models for the direct extraction of tissue parameters from hyperspectral images have been extensively researched recently, as they represent a faster alternative to the well-known iterative methods such as inverse Monte...
The identification of significant predictors with higher model performance is the key objective in classification domain. A machine learning-based variable selection technique termed as CARS-Logistic model is proposed by coupling competitive adaptive...
Industry 4.0 has transformed manufacturing with the integration of cutting-edge technology, posing crucial issues in the efficient task assignment to multi-tasking robots within smart factories. The paper outlines a unique method of decentralizing au...
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