AIMC Topic: Humans

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Predicting brain structural network using functional connectivity.

Medical image analysis
Uncovering the non-trivial brain structure-function relationship is fundamentally important for revealing organizational principles of human brain. However, it is challenging to infer a reliable relationship between individual brain structure and fun...

TOD-CNN: An effective convolutional neural network for tiny object detection in sperm videos.

Computers in biology and medicine
The detection of tiny objects in microscopic videos is a problematic point, especially in large-scale experiments. For tiny objects (such as sperms) in microscopic videos, current detection methods face challenges in fuzzy, irregular, and precise pos...

Study on transfer learning capabilities for pneumonia classification in chest-x-rays images.

Computer methods and programs in biomedicine
BACKGROUND: over the last year, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and its variants have highlighted the importance of screening tools with high diagnostic accuracy for new illnesses such as COVID-19. In that regard, dee...

Stretchable Temperature-Responsive Multimodal Neuromorphic Electronic Skin with Spontaneous Synaptic Plasticity Recovery.

ACS nano
Multimodal electronic skin devices capable of detecting multimodal signals provide the possibility for health monitoring. Sensing and memory for temperature and deformation by human skin are of great significance for the perception and monitoring of ...

Self-Powered Force Sensors for Multidimensional Tactile Sensing.

ACS applied materials & interfaces
A tactile sensor is the centerpiece in human-machine interfaces, enabling robotics or prosthetics to manipulate objects dexterously. Specifically, it is crucial to endow the sensor with the ability to detect and distinguish normal and shear forces in...

Machine Learning, Deep Learning, and Mathematical Models to Analyze Forecasting and Epidemiology of COVID-19: A Systematic Literature Review.

International journal of environmental research and public health
COVID-19 is a disease caused by SARS-CoV-2 and has been declared a worldwide pandemic by the World Health Organization due to its rapid spread. Since the first case was identified in Wuhan, China, the battle against this deadly disease started and ha...

Machine learning to predict pregnancy outcomes: a systematic review, synthesizing framework and future research agenda.

BMC pregnancy and childbirth
Machine Learning (ML) has been widely used in predicting the mode of childbirth and assessing the potential maternal risks during pregnancy. The primary aim of this review study is to explore current research and development perspectives that utilize...

Numerical learning of deep features from drug-exposed cell images to calculate IC50 without staining.

Scientific reports
To facilitate rapid determination of cellular viability caused by the inhibitory effect of drugs, numerical deep learning algorithms was used for unlabeled cell culture images captured by a light microscope as input. In this study, A549, HEK293, and ...

Settings matter: a scoping review on parameters in robot-assisted gait therapy identifies the importance of reporting standards.

Journal of neuroengineering and rehabilitation
BACKGROUND: Lokomat therapy for gait rehabilitation has become increasingly popular. Most evidence suggests that Lokomat therapy is equally effective as but not superior to standard therapy approaches. One reason might be that the Lokomat parameters ...

Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.

BMC medical informatics and decision making
BACKGROUND: Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are unclear. There is a critical need to develop methods to identify children at high-risk for future e...