AIMC Topic: Humans

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Anti-senescent drug screening by deep learning-based morphology senescence scoring.

Nature communications
Advances in deep learning technology have enabled complex task solutions. The accuracy of image classification tasks has improved owing to the establishment of convolutional neural networks (CNN). Cellular senescence is a hallmark of ageing and is im...

Hard for humans, hard for machines: predicting readmission after psychiatric hospitalization using narrative notes.

Translational psychiatry
Machine learning has been suggested as a means of identifying individuals at greatest risk for hospital readmission, including psychiatric readmission. We sought to compare the performance of predictive models that use interpretable representations d...

Behavioral and neurophysiological effects of an intensified robot-assisted therapy in subacute stroke: a case control study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Physical training is able to induce changes at neurophysiological and behavioral level associated with performance changes for the trained movements. The current study explores the effects of an additional intense robot-assisted upper ext...

A 9 mRNAs-based diagnostic signature for rheumatoid arthritis by integrating bioinformatic analysis and machine-learning.

Journal of orthopaedic surgery and research
BACKGROUND: Rheumatoid arthritis (RA) is an autoimmune rheumatic disease that carries a substantial burden for both patients and society. Early diagnosis of RA is essential to prevent disease progression and select an optimal therapeutic strategy. Ho...

A deep learning model for diagnosing dystrophinopathies on thigh muscle MRI images.

BMC neurology
BACKGROUND: Dystrophinopathies are the most common type of inherited muscular diseases. Muscle biopsy and genetic tests are effective to diagnose the disease but cost much more than primary hospitals can reach. The more available muscle MRI is promis...

Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence.

Computational and mathematical methods in medicine
Intestinal obstruction is a common surgical emergency in children. However, it is challenging to seek appropriate treatment for childhood ileus since many diagnostic measures suitable for adults are not applicable to children. The rapid development o...

Multi-Domain Adversarial Feature Generalization for Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
With the assistance of sophisticated training methods applied to single labeled datasets, the performance of fully-supervised person re-identification (Person Re-ID) has been improved significantly in recent years. However, these models trained on a ...

Few-Shot Human-Object Interaction Recognition With Semantic-Guided Attentive Prototypes Network.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Extreme instance imbalance among categories and combinatorial explosion make the recognition of Human-Object Interaction (HOI) a challenging task. Few studies have addressed both challenges directly. Motivated by the success of few-shot learning that...

Additional value of deep learning computed tomographic angiography-based fractional flow reserve in detecting coronary stenosis and predicting outcomes.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Deep learning (DL) has achieved great success in medical imaging and could be utilized for the non-invasive calculation of fractional flow reserve (FFR) from coronary computed tomographic angiography (CCTA) (CT-FFR).

Screening of sleep apnea based on heart rate variability and long short-term memory.

Sleep & breathing = Schlaf & Atmung
PURPOSE: Sleep apnea syndrome (SAS) is a prevalent sleep disorder in which apnea and hypopnea occur frequently during sleep and result in increase of the risk of lifestyle-related disease development as well as daytime sleepiness. Although SAS is a c...