AIMC Topic: Humans

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An integrated approach for advanced vehicle classification.

PloS one
This study is dedicated to addressing the trade-off between receptive field size and computational efficiency in low-level vision. Conventional neural networks (CNNs) usually expand the receptive field by adding layers or inflation filtering, which o...

Identification of biomarkers in Alzheimer's disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning algorithms.

PloS one
BACKGROUND: Since its emergence in 2019, COVID-19 has become a global epidemic. Several studies have suggested a link between Alzheimer's disease (AD) and COVID-19. However, there is little research into the mechanisms underlying these phenomena. The...

Multi-agent deep reinforcement learning-based robotic arm assembly research.

PloS one
Due to the complexity and variability of application scenarios and the increasing demands for assembly, single-agent algorithms often face challenges in convergence and exhibit poor performance in robotic arm assembly processes. To address these issu...

Development and validation of interpretable machine learning models for triage patients admitted to the intensive care unit.

PloS one
OBJECTIVES: Developing and validating interpretable machine learning (ML) models for predicting whether triaged patients need to be admitted to the intensive care unit (ICU).

Unsupervised neural network-based image stitching method for bladder endoscopy.

PloS one
Bladder endoscopy enables the observation of intravesical lesion characteristics, making it an essential tool in urology. Image stitching techniques are commonly employed to expand the field of view of bladder endoscopy. Traditional image stitching m...

Artificial intelligence in orthopedic research assistance: a resident's perspective.

Musculoskeletal surgery
Artificial intelligence (AI) is transforming orthopedic research by optimizing academic workflows, improving evidence synthesis, and expanding access to advanced data analysis tools. Generative AI models such as ChatGPT and GPT-4, alongside specializ...

Integration of transcriptome and Mendelian randomization analyses in exploring the extracellular vesicle-related biomarkers of diabetic kidney disease.

Renal failure
BACKGROUND: Diabetic Kidney Disease (DKD) is a common complication in patients with diabetes, and its pathogenesis remains incompletely understood. Recent studies have suggested that extracellular vesicles (EVs) may play a significant role in the ini...

Computational models suggest that human memory judgments exhibit interference due to the use of overlapping representations.

Psychological review
Episodic memory is a core function that allows us to remember the events of our lives. Given that many events in our life contain overlapping elements (e.g., similar people and places), it is critical to understand how well we can remember the specif...

Artificial Intelligence in Videofluoroscopy Swallow Study Analysis: A Comprehensive Review.

Dysphagia
Videofluoroscopic Swallowing Study (VFSS) is considered the gold standard for diagnosing swallowing disorders, or dysphagia. However, the interpretation of VFSS is susceptible to human bias and subjectivity, resulting in significant inter- and intra-...

How Artificial Intelligence, Virtual Reality, and Other Digital Technologies Are Changing the Field of Pediatric Neurogastroenterology.

Gastroenterology clinics of North America
Digital technology development is accelerating, with extended reality, artificial intelligence, and methods for information sharing leading the charge in broad medical specialties including pediatric neurogastroenterology. This rapid advancement must...