AIMC Topic: Humans

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Generalization limits of Graph Neural Networks in identity effects learning.

Neural networks : the official journal of the International Neural Network Society
Graph Neural Networks (GNNs) have emerged as a powerful tool for data-driven learning on various graph domains. They are usually based on a message-passing mechanism and have gained increasing popularity for their intuitive formulation, which is clos...

GSSCL: A framework for Graph Self-Supervised Curriculum Learning based on clustering label smoothing.

Neural networks : the official journal of the International Neural Network Society
Graph self-supervised learning is an effective technique for learning common knowledge from unlabeled graph data through pretext tasks. To capture the interrelationships between nodes and their essential roles globally, existing methods use clusterin...

Utilizing echocardiography and unsupervised machine learning for heart failure risk identification.

International journal of cardiology
BACKGROUND: Global longitudinal strain (GLS) is recognized as a powerful predictor of heart failure (HF). However, the entire strain curve may entail important prognostic information regarding HF risk that might be undiscovered by only focusing on th...

Exploring the Efficacy of Artificial Intelligence: A Comprehensive Analysis of CHAT-GPT's Accuracy and Completeness in Addressing Urinary Incontinence Queries.

Neurourology and urodynamics
BACKGROUND: Artificial intelligence models are increasingly gaining popularity among patients and healthcare professionals. While it is impossible to restrict patient's access to different sources of information on the Internet, healthcare profession...

Drug-target prediction through self supervised learning with dual task ensemble approach.

Computational biology and chemistry
Drug-Target interaction (DTI) prediction, a transformative approach in pharmaceutical research, seeks novel therapeutic applications for computational method based virtual screening, existing drugs to address untreated diseases and discovery of exist...

An anthropomorphic diagnosis system of pulmonary nodules using weak annotation-based deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The accurate categorization of lung nodules in CT scans is an essential aspect in the prompt detection and diagnosis of lung cancer. The categorization of grade and texture for nodules is particularly significant since it can aid radiologists and cli...

Smart monitoring solution for dengue infection control: A digital twin-inspired approach.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In the realm of smart healthcare, precise monitoring and prediction services are crucial for mitigating the impact of infectious diseases. This study introduces an innovative digital twin technology-inspired monitoring archi...

Assessing the impact of ultrasound image standardization in deep learning-based segmentation of carotid plaque types.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Carotid B-mode ultrasound (CBUS) imaging is often used to detect and assess atherosclerotic plaques. Doctors often need to segment plaques in the CBUS images to further examine them. Multiple studies have proposed two-dimens...

Real-World evaluation of an AI triaging system for chest X-rays: A prospective clinical study.

European journal of radiology
Chest X-rays (CXRs) are crucial for diagnosing and managing lung conditions. While CXR is a common and cost-effective diagnostic tool, interpreting the high volume of CXRs is challenging due to workforce limitations. Artificial intelligence (AI) offe...

Integration of 3D-QSAR, molecular docking, and machine learning techniques for rational design of nicotinamide-based SIRT2 inhibitors.

Computational biology and chemistry
Selective inhibitors of sirtuin-2 (SIRT2) are increasingly recognized as potential therapeutics for cancer and neurodegenerative diseases. Derivatives of 5-((3-amidobenzyl)oxy)nicotinamides have been identified as some of the most potent and selectiv...