AIMC Topic: Adult

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AI-based CT assessment of 3117 vertebrae reveals significant sex-specific vertebral height differences.

Scientific reports
Predicting vertebral height is complex due to individual factors. AI-based medical imaging analysis offers new opportunities for vertebral assessment. Thereby, these novel methods may contribute to sex-adapted nomograms and vertebral height predictio...

A novel UHPLC-HRMS method for simultaneous determination of 20 amino metabolites and proteins in lymphoma patients' cells and serum.

Scientific reports
Highly sensitive and selective monitoring of amino metabolites such as glutamine, arginine, tryptophan and related proteins played significant roles in early diagnosis and warning of lymphoma. But those limited abundance and lacked chromophore group ...

Radiomics analysis based on dynamic contrast-enhanced MRI for predicting early recurrence after hepatectomy in hepatocellular carcinoma patients.

Scientific reports
This study aimed to develop a machine learning model based on Magnetic Resonance Imaging (MRI) radiomics for predicting early recurrence after curative surgery in patients with hepatocellular carcinoma (HCC).A retrospective analysis was conducted on ...

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.

Scientific reports
Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elevate mortality rates. Consequently, early prevention and identification of this condition are crucial...

Mitochondrial haplogroup A2 is associated with increased COVID-19 mortality in an admixed Brazilian population.

Scientific reports
Mitochondria play a crucial role in cellular respiration and immune responses. Mitochondrial DNA (mtDNA) haplogroups and variants have been associated with various diseases, including COVID-19. This study analyzed complete mtDNA sequences from 467 Br...

Improved convolutional neural network for precise exercise posture recognition and intelligent health indicator prediction.

Scientific reports
This paper presents a novel framework for accurate exercise posture recognition and health indicator prediction based on improved convolutional neural networks. We propose a multi-scale feature fusion architecture incorporating spatiotemporal attenti...

A publicly available benchmark for assessing large language models' ability to predict how humans balance self-interest and the interest of others.

Scientific reports
Large language models (LLMs) hold enormous potential to assist humans in decision-making processes, from everyday to high-stake scenarios. However, as many human decisions carry social implications, for LLMs to be reliable assistants a necessary prer...

A novel feature extractor based on constrained cross network for detecting sleep state.

Scientific reports
With increasing awareness of healthy living and social pressure, more and more people have begun to pay attention to their sleep state. Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or tradition...

Predicting car accident severity in Northwest Ethiopia: a machine learning approach leveraging driver, environmental, and road conditions.

Scientific reports
Road traffic accidents (RTAs) in Northwest Ethiopia, a region with a fatality rate of 32.2 per 100,000 residents, pose a critical public health challenge exacerbated by infrastructural deficits and environmental hazards. This study leverages machine ...

Single pulse electrical stimulation of the medial thalamic surface induces narrower high gamma band activities in the sensorimotor cortex.

Scientific reports
The human thalamus projects nerve fibers to all cortical regions and propagates epileptic activity. However, opportunities to directly record thalamic and cortical neural activities simultaneously are extremely limited and their electrophysiological ...