Otolaryngologic clinics of North America
Jun 4, 2024
To fuel artificial intelligence (AI) potential in clinical practice in otolaryngology, researchers must understand its epistemic limitations, which are tightly linked to ethical dilemmas requiring careful consideration. AI tools are fundamentally opa...
Otolaryngologic clinics of North America
Jun 4, 2024
Successful artificial intelligence (AI) implementation is predicated on the trust of clinicians and patients, and is achieved through a culture of responsible use, focusing on regulations, standards, and education. Otolaryngologists can overcome barr...
BACKGROUND: This study aims to develop an artificial neural network (ANN) prediction model incorporating random forest (RF) screening ability for predicting the risk of depression in adolescents and identifies key risk factors to provide a new approa...
BACKGROUND: Depression and suicidal ideation often co-occur in children and adolescents, yet they possess distinct characteristics. This study sought to identify the different related factors associated with depression and suicidal ideation.
Biochemical and biophysical research communications
Jun 4, 2024
Data acquisition for transcriptomic studies used to be the bottleneck in the transcriptomic analytical pipeline. However, recent developments in transcriptome profiling technologies have increased researchers' ability to obtain data, resulting in a s...
Computer methods and programs in biomedicine
Jun 4, 2024
BACKGROUND AND OBJECTIVE: Time series data plays a crucial role in the realm of the Internet of Things Medical (IoMT). Through machine learning (ML) algorithms, online time series classification in IoMT systems enables reliable real-time disease dete...
BACKGROUND: Pneumonia is one of the most common complications after spontaneous intracerebral hemorrhage (sICH), i.e., stroke-associated pneumonia (SAP). Timely identification of targeted patients is beneficial to reduce poor prognosis. So far, there...
BACKGROUND: Machine learning algorithms as a research tool, including traditional machine learning and deep learning, are increasingly applied to the field of urodynamics. However, no studies have evaluated how to select appropriate algorithm models ...
BACKGROUND AND OBJECTIVES: This study aims to develop and evaluate NeuNN, a system based on convolutional neural networks (CNN) and generative adversarial networks (GAN) for the automatic identification of normal neutrophils and those containing seve...
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