BACKGROUND: Detecting malignant transformation of sinonasal inverted papilloma (SIP) into squamous cell carcinoma (SIP-SCC) before surgery is a clinical need. We aimed to explore the value of deep learning (DL) that leverages nasal endoscopy and T2-w...
European journal of trauma and emergency surgery : official publication of the European Trauma Society
Jul 21, 2025
PURPOSE: Convolutional Neural Networks (CNNs) have shown promise in fracture detection, but their ability to improve surgeons' inconsistent fracture classification remains unstudied. Therefore, our aim was create and (externally) validate the perform...
Patient identification for national registries often relies upon clinician recognition of cases or retrospective searches using potentially inaccurate clinical codes, leading to incomplete data capture and inefficiencies. Natural Language Processing ...
The study aimed to establish and validate a nomogram model to predict postoperative delirium (POD) among esophageal cancer resection patients. Clinical data of 396 patients with esophageal cancer who underwent esophagectomy from November 2020 to June...
BACKGROUND: Child malnutrition represents a critical global public health issue and it is characterised by high prevalence and severe long-term consequences for growth and development. A better understanding of its contributory factors is essential t...
BACKGROUND: Hospitals and health care systems may benefit from artificial intelligence (AI) and big data to analyse clinical information combined with external sources. Machine learning, a subset of AI, uses algorithms trained on data to generate pre...
Closed-loop brain-computer interfaces can be used to bridge, modulate, or repair damaged connections within the brain to restore functional deficits. Towards this goal, we demonstrate that small artificial spiking neural networks can be bidirectional...
The internet is one of the essential tools today, and its impact is particularly felt among university students. Internet addiction (IA) has become a serious public health issue worldwide. This multi-class classification study aimed to identify the p...
This study employed state-of-the-art machine learning to evaluate the mortality effects of alpha-emitting radionuclides (241Am, 249Cf, 252Cf, 238Pu, 239Pu, 224Ra, 226Ra, 228Th) on 2,576 dogs, factoring in radioactivity levels, composition, administra...
Chloride channel accessory 1 (CLCA1) is considered a potential prognostic biomarker for colon adenocarcinoma (COAD). The objective of this research was to develop two pathomics models to predict CLCA1 expression from hematoxylin-eosin (H&E) stained p...
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