BACKGROUND: The escalating global scarcity of skilled health care professionals is a critical concern, further exacerbated by rising stress levels and clinician burnout rates. Artificial intelligence (AI) has surfaced as a potential resource to allev...
BACKGROUND: The pathophysiology of obstructive sleep apnea (OSA) and diabetes mellitus (DM) is still unknown, despite clinical reports linking the two conditions. After investigating potential roles for DM-related genes in the pathophysiology of OSA,...
Advancements in reproductive technology are now approaching an unprecedented frontier: the pregnancy robot, a potential artificial womb capable of carrying a fetus from fertilization to birth. This innovation, by simulating the natural uterine enviro...
OBJECTIVES: To investigate the performance of a deep learning (DL) model for segmenting cone-beam computed tomography (CBCT) scans taken before and after mandibular horizontal guided bone regeneration (GBR) to evaluate hard tissue changes.
The present study analyzed the impact of age on the causes of death (CODs) in patients with nasopharyngeal carcinoma (NPC) undergoing chemoradiotherapy (CRT) using machine learning approaches. A total of 2841 patients (1037 classified as older, ≥ 60 ...
Drug-target interactions (DTIs) are pivotal in drug discovery and development, and their accurate identification can significantly expedite the process. Numerous DTI prediction methods have emerged, yet many fail to fully harness the feature informat...
Extensive research has confirmed the widespread presence of microorganisms in the human body and their crucial impact on human health, with drugs being an effective method of regulation. Hence it is essential to identify potential microbe-drug associ...
Journal of X-ray science and technology
Jan 13, 2025
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative disorder. There are no drugs and methods for the treatment of AD, but early intervention can delay the deterioration of the disease. Therefore, the early diagnosis of AD and mild cognitive i...
PURPOSE: Drug-induced liver injury (DILI) is one of the most common and serious adverse drug reactions related to first-line anti-tuberculosis drugs in pediatric tuberculosis patients. This study aims to develop an automatic machine learning (AutoML)...
BACKGROUND: Convolutional neural networks have excellent modeling abilities to complex large-scale datasets and have been applied to genomics. It requires converting genotype data to image format when employing convolutional neural networks to genome...
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