AIMC Topic: Humans

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Multimodal deep learning: tumor and visceral fat impact on colorectal cancer occult peritoneal metastasis.

European radiology
OBJECTIVES: This study proposes a multimodal deep learning (DL) approach to investigate the impact of tumors and visceral fat on occult peritoneal metastasis in colorectal cancer (CRC) patients.

Unveiling Disparities in Patient Rights Awareness and Practice: Insights From Artificial Neural Networks.

Journal of patient safety
BACKGROUND: High-quality universal health care coverage for all patients is the common theme in patient rights. However, pertinent investigations on this topic within the context of Jordanian health care are absent. This systematic review, coupled wi...

Redefining prostate cancer care: innovations and future directions in active surveillance.

Current opinion in urology
PURPOSE OF REVIEW: This review provides a critical analysis of recent advancements in active surveillance (AS), emphasizing updates from major international guidelines and their implications for clinical practice.

Rapid wall shear stress prediction for aortic aneurysms using deep learning: a fast alternative to CFD.

Medical & biological engineering & computing
Aortic aneurysms pose a significant risk of rupture. Previous research has shown that areas exposed to low wall shear stress (WSS) are more prone to rupture. Therefore, precise WSS determination on the aneurysm is crucial for rupture risk assessment....

Comparative performance of PD-L1 scoring by pathologists and AI algorithms.

Histopathology
AIM: This study evaluates the comparative effectiveness of pathologists versus artificial intelligence (AI) algorithms in scoring PD-L1 expression in non-small cell lung carcinoma (NSCLC). Immune-checkpoint inhibitors have revolutionized NSCLC treatm...

Artificial intelligence for the diagnosis of pediatric appendicitis: A systematic review.

The American journal of emergency medicine
BACKGROUND: While acute appendicitis is the most frequent surgical emergency in children, its diagnosis remains complex. Artificial intelligence (AI) and machine learning (ML) tools have been employed to improve the accuracy of various diagnoses, inc...

ZS-MNET: A zero-shot learning based approach to multimodal named entity typing.

Neural networks : the official journal of the International Neural Network Society
The task of named entity typing (NET) on social platforms is significant as it involves identifying the various types of named entities within unstructured text. The existing methods for NET only utilize the text modality to classify the types of nam...

MVGNCDA: Identifying Potential circRNA-Disease Associations Based on Multi-view Graph Convolutional Networks and Network Embeddings.

Interdisciplinary sciences, computational life sciences
Increasing evidences have indicated that circular RNAs play a crucial role in the onset and progression of various diseases. However, exploring potential disease-associated circRNAs using conventional experimental techniques remains both time-intensi...

Artificial intelligence in otorhinolaryngology: current trends and application areas.

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: This study aims to perform a bibliometric analysis of scientific research on the use of artificial intelligence (AI) in the field of Otorhinolaryngology (ORL), with a specific focus on identifying emerging AI trend topics within this discipl...