AIMC Topic: Humans

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Fully automated mouse echocardiography analysis using deep convolutional neural networks.

American journal of physiology. Heart and circulatory physiology
Echocardiography (echo) is a translationally relevant ultrasound imaging modality widely used to assess cardiac structure and function in preclinical models of heart failure (HF) during research and drug development. Although echo is a very valuable ...

Imbalanced prediction of emergency department admission using natural language processing and deep neural network.

Journal of biomedical informatics
The emergency department (ED) plays a very significant role in the hospital. Owing to the rising number of ED visits, medical service points, and ED market, overcrowding of EDs has become serious worldwide. Overcrowding has long been recognized as a ...

A Continuum Robotic Cannula With Tip Following Capability and Distal Dexterity for Intracerebral Hemorrhage Evacuation.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper aims to investigate a new continuum robot design and its motion implementation methods appropriate for a minimally invasive intracerebral hemorrhage (ICH) evacuation.

Simulating Ideal Assistive Strategies to Reduce the Metabolic Cost of Walking in the Elderly.

IEEE transactions on bio-medical engineering
OBJECTIVE: Development of walking assist exoskeletons is a growing area of study, offering a solution to restore, maintain, and enhance mobility. However, applying this technology to the elderly is challenging and there is currently no consensus as t...

Affordable Artificial Intelligence-Assisted Machine Supervision System for the Small and Medium-Sized Manufacturers.

Sensors (Basel, Switzerland)
With the rapid concurrent advance of artificial intelligence (AI) and Internet of Things (IoT) technology, manufacturing environments are being upgraded or equipped with a smart and connected infrastructure that empowers workers and supervisors to op...

Swin-MFA: A Multi-Modal Fusion Attention Network Based on Swin-Transformer for Low-Light Image Human Segmentation.

Sensors (Basel, Switzerland)
In recent years, image segmentation based on deep learning has been widely used in medical imaging, automatic driving, monitoring and security. In the fields of monitoring and security, the specific location of a person is detected by image segmentat...

Initial experience of a deep learning application for the differentiation of Kikuchi-Fujimoto's disease from tuberculous lymphadenitis on neck CECT.

Scientific reports
Neck contrast-enhanced CT (CECT) is a routine tool used to evaluate patients with cervical lymphadenopathy. This study aimed to evaluate the ability of convolutional neural networks (CNNs) to classify Kikuchi-Fujimoto's disease (KD) and cervical tube...

Radiomics and deep learning methods for the prediction of 2-year overall survival in LUNG1 dataset.

Scientific reports
In this study, we tested and compared radiomics and deep learning-based approaches on the public LUNG1 dataset, for the prediction of 2-year overall survival (OS) in non-small cell lung cancer patients. Radiomic features were extracted from the gross...

CNN-XGBoost fusion-based affective state recognition using EEG spectrogram image analysis.

Scientific reports
Recognizing emotional state of human using brain signal is an active research domain with several open challenges. In this research, we propose a signal spectrogram image based CNN-XGBoost fusion method for recognising three dimensions of emotion, na...

Prediction of mortality risk of health checkup participants using machine learning-based models: the J-SHC study.

Scientific reports
Early detection and treatment of diseases through health checkups are effective in improving life expectancy. In this study, we compared the predictive ability for 5-year mortality between two machine learning-based models (gradient boosting decision...