AIMC Topic: Humans

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Less postoperative pain and shorter length of stay after robot-assisted retrorectus hernia repair (rRetrorectus) compared with laparoscopic intraperitoneal onlay mesh repair (IPOM) for small or medium-sized ventral hernias.

Surgical endoscopy
BACKGROUND: The optimal repair of ventral hernia remains unknown. We aimed to evaluate the results after robotic-assisted laparoscopic transabdominal repair with retrorectus mesh placement (rRetrorectus) compared with laparoscopic intraperitoneal onl...

Usefulness of deep learning-based noise reduction for 1.5 T MRI brain images.

Clinical radiology
AIM: To evaluate 1.5 T magnetic resonance imaging (MRI) brain images with denoising procedures using deep learning-based reconstruction (dDLR) relative to the original 1.5 and 3 T images.

Interpretable machine learning framework reveals microbiome features of oral disease.

Microbiological research
BACKGROUND: Although the oral microbiome plays an important role in the progression of oral diseases, the microbes closely related to these diseases remain largely uncharacterized.

The hiatus between organism and machine evolution: Contrasting mixed microbial communities with robots.

Bio Systems
Mixed microbial communities, usually composed of various bacterial and fungal species, are fundamental in a plethora of environments, from soil to human gut and skin. Their evolution is a paradigmatic example of intertwined dynamics, where not just t...

Singapore radiographers' perceptions and expectations of artificial intelligence - A qualitative study.

Journal of medical imaging and radiation sciences
INTRODUCTION: With the emergence of artificial intelligence (AI) in medical imaging, radiographers are likely to be at the forefront of this technological advancement. Studies have therefore been conducted recently to understand radiographers' opinio...

Vessel and tissue recognition during third-space endoscopy using a deep learning algorithm.

Gut
In this study, we aimed to develop an artificial intelligence clinical decision support solution to mitigate operator-dependent limitations during complex endoscopic procedures such as endoscopic submucosal dissection and peroral endoscopic myotomy, ...

Mammogram classification based on a novel convolutional neural network with efficient channel attention.

Computers in biology and medicine
Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosis (CAD) systems have achieved significant results in recent years, precise diagnosis of lesions in m...

Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks.

NeuroImage
Forming transformation-tolerant object representations is critical to high-level primate vision. Despite its significance, many details of tolerance in the human brain remain unknown. Likewise, despite the ability of convolutional neural networks (CN...