AIMC Topic: Humans

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Brain-Controlled 2D Navigation Robot Based on a Spatial Gradient Controller and Predictive Environmental Coordinator.

IEEE journal of biomedical and health informatics
OBJECTIVE: Brain-computer interfaces (BCIs) have been used in two-dimensional (2D) navigation robotic devices, such as brain-controlled wheelchairs and brain-controlled vehicles. However, contemporary BCI systems are driven by binary selective contro...

A Unified Multi-Phase CT Synthesis and Classification Framework for Kidney Cancer Diagnosis With Incomplete Data.

IEEE journal of biomedical and health informatics
Multi-phase computed tomography (CT) is widely adopted for the diagnosis of kidney cancer due to the complementary information among phases. However, the complete set of multi-phase CT is often not available in practical clinical applications. In rec...

Plasma cell subtypes analyzed using artificial intelligence algorithm for predicting biochemical recurrence, immune escape potential, and immunotherapy response of prostate cancer.

Frontiers in immunology
BACKGROUND: Plasma cells as an important component of immune microenvironment plays a crucial role in immune escape and are closely related to immune therapy response. However, its role for prostate cancer is rarely understood. In this study, we inte...

OnAI-Comp: An Online AI Experts Competing Framework for Early Sepsis Detection.

IEEE/ACM transactions on computational biology and bioinformatics
Sepsis is a major public concern due to its high mortality, morbidity, and financial cost. There are many existing works of early sepsis prediction using different machine learning models to mitigate the outcomes brought by sepsis. In the practical s...

Accurate Prediction of Human Essential Proteins Using Ensemble Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics
Essential proteins are considered the foundation of life as they are indispensable for the survival of living organisms. Computational methods for essential protein discovery provide a fast way to identify essential proteins. But most of them heavily...

IGNSCDA: Predicting CircRNA-Disease Associations Based on Improved Graph Convolutional Network and Negative Sampling.

IEEE/ACM transactions on computational biology and bioinformatics
Accumulating evidences have shown that circRNA plays an important role in human diseases. It can be used as potential biomarker for diagnose and treatment of disease. Although some computational methods have been proposed to predict circRNA-disease a...

An Educational Graphical User Interface to Construct Convolutional Neural Networks for Teaching Artificial Intelligence in Radiology.

Canadian Association of Radiologists journal = Journal l'Association canadienne des radiologistes
Deep learning techniques using convolutional neural networks (CNNs) have been successfully developed for various medical image analysis tasks. However, the skills to understand and develop deep learning models are not usually taught during radiology ...

Telerobotic Sonography for Remote Diagnostic Imaging.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine

Validity and reliability of a mobile digital imaging analysis trained by a four-compartment model.

Journal of human nutrition and dietetics : the official journal of the British Dietetic Association
BACKGROUND: Digital imaging analysis (DIA) estimates collected from mobile applications comprise a novel technique that can collect body composition estimates remotely without the inherent restrictions of other research-grade devices. However, the ac...

Deep learning-based noise reduction for coronary CT angiography: using four-dimensional noise-reduction images as the ground truth.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: To assess low-contrast areas such as plaque and coronary artery stenosis, coronary computed tomography angiography (CCTA) needs to provide images with lower noise without increasing radiation doses.