AIMC Topic: Humans

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Students' perception of the use of artificial intelligence (AI) in pharmacy school.

Currents in pharmacy teaching & learning
INTRODUCTION: The increasing adoption of artificial intelligence (AI) among college students, particularly in pharmacy education, raises ethical concerns and prompts debates on responsible usage. The promise of the potential to reduce workload is met...

Internal Medicine Year in Review 2023.

Internal medicine (Tokyo, Japan)
The year 2023 marked a significant change for Internal Medicine, as the number of submissions related to the novel coronavirus infection (COVID-19) declined significantly and interest shifted to other disease fields and research areas. Our journal pu...

A Contrastive-Learning-Based Deep Neural Network for Cancer Subtyping by Integrating Multi-Omics Data.

Interdisciplinary sciences, computational life sciences
BACKGROUND: Accurate identification of cancer subtypes is crucial for disease prognosis evaluation and personalized patient management. Recent advances in computational methods have demonstrated that multi-omics data provides valuable insights into t...

The accuracy of deep learning models for diagnosing maxillary fungal ball rhinosinusitis.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
PURPOSE: To assess the accuracy of deep learning models for the diagnosis of maxillary fungal ball rhinosinusitis (MFB) and to compare the accuracy, sensitivity, specificity, precision, and F1-score with a rhinologist.

Harnessing AI for precision tonsillitis diagnosis: a revolutionary approach in endoscopic analysis.

European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
BACKGROUND: Diagnosing and treating tonsillitis pose no significant challenge for otolaryngologists; however, it can increase the infection risk for healthcare professionals amidst the coronavirus pandemic. In recent years, with the advancement of ar...

Biomedical event causal relation extraction with deep knowledge fusion and Roberta-based data augmentation.

Methods (San Diego, Calif.)
Biomedical event causal relation extraction (BECRE), as a subtask of biomedical information extraction, aims to extract event causal relation facts from unstructured biomedical texts and plays an essential role in many downstream tasks. The existing ...

Artificial intelligence with mass spectrometry-based multimodal molecular profiling methods for advancing therapeutic discovery of infectious diseases.

Pharmacology & therapeutics
Infectious diseases, driven by a diverse array of pathogens, can swiftly undermine public health systems. Accurate diagnosis and treatment of infectious diseases-centered around the identification of biomarkers and the elucidation of disease mechanis...

Exploring the benefits and challenges of AI-driven large language models in gastroenterology: Think out of the box.

Biomedical papers of the Medical Faculty of the University Palacky, Olomouc, Czechoslovakia
Artificial Intelligence (AI) has evolved significantly over the past decades, from its early concepts in the 1950s to the present era of deep learning and natural language processing. Advanced large language models (LLMs), such as Chatbot Generative ...

Prospective Evaluation of Artificial Intelligence Triage of Intracranial Hemorrhage on Noncontrast Head CT Examinations.

AJR. American journal of roentgenology
Retrospective studies evaluating artificial intelligence (AI) algorithms for intracranial hemorrhage (ICH) detection on noncontrast CT (NCCT) have shown promising results but lack prospective validation. The purpose of this article was to evaluate ...