BACKGROUND: Graduate students face higher depression rates worldwide, which were further exacerbated during the COVID-19 pandemic. This study employed a machine learning approach to predict depressive symptoms using academic-related stressors.
AIMS: To develop a model capable of distinguishing carcinoma ex-pleomorphic adenoma from pleomorphic adenoma using a convolutional neural network architecture.
BACKGROUND: Studies of cardiovascular disease risk prediction by machine learning algorithms often do not assess their ability to generalize to other populations and few of them include an analysis of the interpretability of individual predictions. T...
Few studies have effectively shown how to use satellites that gather optical data to monitor plastic debris in the marine environment. For the first time, floating macro-plastics distinguishable from seaweed are identified in optical data from the Eu...
BACKGROUND: Hepatocellular carcinoma (HCC) is a prevalent tumor with high mortality rates. Computed tomography (CT) is crucial in the non-invasive diagnosis of HCC. Recent advancements in artificial intelligence (AI) have shown significant potential ...
BACKGROUND: The effectiveness of dengue control interventions depends on an effective integrated surveillance system that involves analysis of multiple variables associated with the natural history and transmission dynamics of this arbovirus. Entomol...
Artificial intelligence (AI) and machine learning (ML) offer objective solutions in the elaboration of taxonomic keys, such as the processing of large numbers of samples, aiding in the species identification, and optimizing the time required for this...
American journal of infection control
Sep 21, 2024
BACKGROUND: Hospital-acquired infections (HAIs) increase morbidity, mortality, and health care costs. Effective hand hygiene (HH) is crucial for prevention, but achieving high compliance remains challenge. This study explores using machine learning t...
OBJECTIVE: To develop and validate a predictive model utilizing machine-learning techniques for estimating the length of hospital stay among patients who underwent coronary artery bypass grafting.
Smart indoor tourist attractions, such as smart museums and aquariums, require a significant investment in indoor localization devices. The use of Global Positioning Systems on smartphones is unsuitable for scenarios where dense materials such as con...
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