AIMC Topic: Humans

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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...

Mitigating data bias and ensuring reliable evaluation of AI models with shortcut hull learning.

Nature communications
Shortcut learning poses a significant challenge to both the interpretability and robustness of artificial intelligence, arising from dataset biases that lead models to exploit unintended correlations, or shortcuts, which undermine performance evaluat...

An ultralight, tiny, flexible six-axis force/torque sensor enables dexterous fingertip manipulations.

Nature communications
Multi-dimensional mechanoreceptors are crucial for both humans and robots, providing omnidirectional force/torque senses to ensure dexterous and precise manipulations. Current six-axis force/torque sensors are bulky, heavy, and rigid with complicated...

Enrichment of extracellular vesicles using Mag-Net for the analysis of the plasma proteome.

Nature communications
Extracellular vesicles (EVs) in plasma are composed of exosomes, microvesicles, and apoptotic bodies. We report a plasma EV enrichment strategy using magnetic beads called Mag-Net. Proteomic interrogation of this plasma EV fraction enables the detect...

Stable recurrent dynamics in heterogeneous neuromorphic computing systems using excitatory and inhibitory plasticity.

Nature communications
Many neural computations emerge from self-sustained patterns of activity in recurrent neural circuits, which rely on balanced excitation and inhibition. Neuromorphic electronic circuits represent a promising approach for implementing the brain's comp...

Deep learning quantifies pathologists' visual patterns for whole slide image diagnosis.

Nature communications
Based on the expertise of pathologists, the pixelwise manual annotation has provided substantial support for training deep learning models of whole slide images (WSI)-assisted diagnostic. However, the collection of pixelwise annotation demands massiv...

MS-EmoBoost: a novel strategy for enhancing self-supervised speech emotion representations.

Scientific reports
Extracting richer emotional representations from raw speech is one of the key approaches to improving the accuracy of Speech Emotion Recognition (SER). In recent years, there has been a trend in utilizing self-supervised learning (SSL) for extracting...