AIMC Topic: Humans

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Multimodal data-based human motion intention prediction using adaptive hybrid deep learning network for movement challenged person.

Scientific reports
Recently, social demands for a good quality of life have increased among the elderly and disabled people. So, biomedical engineers and robotic researchers aimed to fuse these techniques in a novel rehabilitation system. Moreover, these models utilize...

Impact of Artificial Intelligence-Generated Content Labels On Perceived Accuracy, Message Credibility, and Sharing Intentions for Misinformation: Web-Based, Randomized, Controlled Experiment.

JMIR formative research
BACKGROUND: The proliferation of generative artificial intelligence (AI), such as ChatGPT, has added complexity and richness to the virtual environment by increasing the presence of AI-generated content (AIGC). Although social media platforms such as...

Embedded Ethics in Practice: A Toolbox for Integrating the Analysis of Ethical and Social Issues into Healthcare AI Research.

Science and engineering ethics
Integrating artificial intelligence (AI) into critical domains such as healthcare holds immense promise. Nevertheless, significant challenges must be addressed to avoid harm, promote the well-being of individuals and societies, and ensure ethically s...

Geochemical evolution, geostatistical mapping and machine learning predictive modeling of groundwater fluoride: a case study of western Balochistan, Quetta.

Environmental geochemistry and health
Around 2.6 billion people are at risk of tooth carries and fluorosis worldwide. Quetta is the worst affected district in Balochistan plateau. Endemic abnormal groundwater fluoride ( ) lacks spatiotemporal studies. This research integrates geospatial...

Fusion-driven semi-supervised learning-based lung nodules classification with dual-discriminator and dual-generator generative adversarial network.

BMC medical informatics and decision making
BACKGROUND: The detection and classification of lung nodules are crucial in medical imaging, as they significantly impact patient outcomes related to lung cancer diagnosis and treatment. However, existing models often suffer from mode collapse and po...

A comprehensive and bias-free machine learning approach for risk prediction of preeclampsia with severe features in a nulliparous study cohort.

BMC pregnancy and childbirth
Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after pregnancy. Because of its diverse clinical presentation, preeclampsia is an adverse pregnancy outcome that is uniquely challenging to predict and mana...

Objective approach to diagnosing attention deficit hyperactivity disorder by using pixel subtraction and machine learning classification of outpatient consultation videos.

Journal of neurodevelopmental disorders
BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common childhood neurodevelopmental disorder, affecting between 5% and 7% of school-age children. ADHD is typically characterized by persistent patterns of inattention or hyperactivity-...

Longitudinal interpretability of deep learning based breast cancer risk prediction.

Physics in medicine and biology
Deep-learning-based models have achieved state-of-the-art breast cancer risk (BCR) prediction performance. However, these models are highly complex, and the underlying mechanisms of BCR prediction are not fully understood. Key questions include wheth...

Automated treatment planning with deep reinforcement learning for head-and-neck (HN) cancer intensity modulated radiation therapy (IMRT).

Physics in medicine and biology
To develop a deep reinforcement learning (DRL) agent to self-interact with the treatment planning system to automatically generate intensity modulated radiation therapy (IMRT) treatment plans for head-and-neck (HN) cancer with consistent organ-at-ris...

Nonlinear relationship between serum Klotho and chronic kidney disease in US adults with metabolic syndrome.

Frontiers in endocrinology
BACKGROUND: Current evidence regarding the effects of serum Klotho among patients with metabolic syndrome (MetS) is scarce. This study explored the relationship between serum Klotho levels and the odds of chronic kidney disease (CKD) in middle-aged a...