AIMC Topic: Humans

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Revisiting low-homophily for graph-based fraud detection.

Neural networks : the official journal of the International Neural Network Society
The openness of Internet stimulates a large number of fraud behaviors which have become a huge threat. Graph-based fraud detectors have attracted extensive interest since the abundant structure information of graph data has proved effective. Conventi...

SpineMamba: Enhancing 3D spinal segmentation in clinical imaging through residual visual Mamba layers and shape priors.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate segmentation of three-dimensional (3D) clinical medical images is critical for the diagnosis and treatment of spinal diseases. However, the complexity of spinal anatomy and the inherent uncertainties of current imaging technologies pose sign...

Class balancing diversity multimodal ensemble for Alzheimer's disease diagnosis and early detection.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Alzheimer's disease (AD) poses significant global health challenges due to its increasing prevalence and associated societal costs. Early detection and diagnosis of AD are critical for delaying progression and improving patient outcomes. Traditional ...

A longitudinal observational study with ecological momentary assessment and deep learning to predict non-prescribed opioid use, treatment retention, and medication nonadherence among persons receiving medication treatment for opioid use disorder.

Journal of substance use and addiction treatment
BACKGROUND: Despite effective treatments for opioid use disorder (OUD), relapse and treatment drop-out diminish their efficacy, increasing the risks of adverse outcomes, including death. Predicting important outcomes, including non-prescribed opioid ...

Evaluating the prognostic significance of artificial intelligence-delineated gross tumor volume and prostate volume measurements for prostate radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Artificial intelligence (AI) may extract prognostic information from MRI for localized prostate cancer. We evaluate whether AI-derived prostate and gross tumor volume (GTV) are associated with toxicity and oncologic outcomes a...

Critical scenarios adversarial generation method for intelligent vehicles testing based on hierarchical reinforcement architecture.

Accident; analysis and prevention
The widespread deployment of intelligent vehicles necessitates comprehensive testing across diverse driving scenarios. A significant challenge is generating critical testing scenarios to accurately evaluate vehicle performance. To overcome the limita...

Pharmacy faculty and students perceptions of artificial intelligence: A National Survey.

Currents in pharmacy teaching & learning
INTRODUCTION: This study explores the perceptions, familiarity, and utilization of artificial intelligence (AI) among pharmacy faculty and students across the United States. By identifying key gaps in AI education and training, it highlights the need...

Beyond traditional orthopaedic data analysis: AI, multimodal models and continuous monitoring.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Multimodal artificial intelligence (AI) has the potential to revolutionise healthcare by enabling the simultaneous processing and integration of various data types, including medical imaging, electronic health records, genomic information and real-ti...

Letters to the editor generated by AI in neuroscience: The role of neuroethics.

Neuroscience
The letter to the editor (LTE) is a correspondence forum that allows a journal's readers to comment on published research and also publish data and arguments in a brief way. The LTE has vital functions as an accessible comment forum, including holdin...