AIMC Topic: Humans

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Characterisation of Cognitive Load Using Machine Learning Classifiers of Electroencephalogram Data.

Sensors (Basel, Switzerland)
A high cognitive load can overload a person, potentially resulting in catastrophic accidents. It is therefore important to ensure the level of cognitive load associated with safety-critical tasks (such as driving a vehicle) remains manageable for dri...

Deep learning based on susceptibility-weighted MR sequence for detecting cerebral microbleeds and classifying cerebral small vessel disease.

Biomedical engineering online
BACKGROUND: Cerebral microbleeds (CMBs) serve as neuroimaging biomarkers to assess risk of intracerebral hemorrhage and diagnose cerebral small vessel disease (CSVD). Therefore, detecting CMBs can evaluate the risk of intracerebral hemorrhage and use...

An artificial intelligence study: automatic description of anatomic landmarks on panoramic radiographs in the pediatric population.

BMC oral health
BACKGROUND: Panoramic radiographs, in which anatomic landmarks can be observed, are used to detect cases closely related to pediatric dentistry. The purpose of the study is to investigate the success and reliability of the detection of maxillary and ...

A novel deep learning-based algorithm combining histopathological features with tissue areas to predict colorectal cancer survival from whole-slide images.

Journal of translational medicine
BACKGROUND: Many methodologies for selecting histopathological images, such as sample image patches or segment histology from regions of interest (ROIs) or whole-slide images (WSIs), have been utilized to develop survival models. With gigapixel WSIs ...

Development of immersive learning framework (ILF) in achieving the goals of higher education: measuring the impact using a pre-post design.

Scientific reports
Emerging technological tools like Artificial Intelligence-based Chatbots, digital educational alternatives and market-driven educational systems pose a challenge to the fundamental aim of the higher education system; comprehensive education for well-...

Deep-LASI: deep-learning assisted, single-molecule imaging analysis of multi-color DNA origami structures.

Nature communications
Single-molecule experiments have changed the way we explore the physical world, yet data analysis remains time-consuming and prone to human bias. Here, we introduce Deep-LASI (Deep-Learning Assisted Single-molecule Imaging analysis), a software suite...

Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study.

Journal of medical Internet research
BACKGROUND: Influenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often struggle to predict influenza outbreaks in an accurate and timely manner. Big data and modern technology h...

Integrated convolutional neural network for skin cancer classification with hair and noise restoration.

Turkish journal of medical sciences
BACKGROUND/AIM: Skin lesions are commonly diagnosed and classified using dermoscopic images. There are many artifacts visible in dermoscopic images, including hair strands, noise, bubbles, blood vessels, poor illumination, and moles. These artifacts ...