AIMC Topic: Humans

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Pre-hospital prediction of adverse outcomes in patients with suspected COVID-19: Development, application and comparison of machine learning and deep learning methods.

Computers in biology and medicine
BACKGROUND: COVID-19 infected millions of people and increased mortality worldwide. Patients with suspected COVID-19 utilised emergency medical services (EMS) and attended emergency departments, resulting in increased pressures and waiting times. Rap...

Human-computer interaction based health diagnostics using ResNet34 for tongue image classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Tongue diagnosis is one of the characteristics of traditional Chinese medicine (TCM), but traditional tongue diagnosis is affected by many factors, and its differential diagnosis results are not widely recognized. The appear...

Enhancing MR image segmentation with realistic adversarial data augmentation.

Medical image analysis
The success of neural networks on medical image segmentation tasks typically relies on large labeled datasets for model training. However, acquiring and manually labeling a large medical image set is resource-intensive, expensive, and sometimes impra...

Young children with autism show atypical prefrontal cortical responses to humanoid robots: An fNIRS study.

International journal of psychophysiology : official journal of the International Organization of Psychophysiology
BACKGROUND: Previous behavioral studies have found that children with autism spectrum disorder (ASD) show greater interest in humanoid robots than in humans. However, the neural mechanism underlying this is not clear. This study compared brain activa...

Visualizing biomarkers and their association with clinical outcomes: A machine learning approach.

Computers in biology and medicine
INTRODUCTION: Clinical investigators often seek to identify biomarkers that are associated with clinical outcomes. The challenge is that biomarkers tend to be numerous, often inter-correlated, and with varying degrees of association with the clinical...

ResNet-50 based technique for EEG image characterization due to varying environmental stimuli.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Emotion is an important factor affecting a person's physical and mental health, but there are few ways to detect a patient's emotions in daily life. Negative emotions not only affect recovery after treatment, but also cause ...

PPsNet: An improved deep learning model for microsatellite instability high prediction in colorectal cancer from whole slide images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Recent studies have shown that colorectal cancer (CRC) patients with microsatellite instability high (MSI-H) are more likely to benefit from immunotherapy. However, current MSI testing methods are not available for all patie...

Dual-level diagnostic feature learning with recurrent neural networks for treatment sequence recommendation.

Journal of biomedical informatics
In recent years, the massive electronic medical records (EMRs) have supported the development of intelligent medical services such as treatment recommendations. However, existing treatment recommendations usually follow the traditional sequential rec...

Automated filtering of genome-wide large deletions through an ensemble deep learning framework.

Methods (San Diego, Calif.)
Computational methods based on whole genome linked-reads and short-reads have been successful in genome assembly and detection of structural variants (SVs). Numerous variant callers that rely on linked-reads and short reads can detect genetic variati...

Deep learning-based virtual noncalcium imaging in multiple myeloma using dual-energy CT.

Medical physics
BACKGROUND: Dual-energy CT with virtual noncalcium (VNCa) images allows the evaluation of focal intramedullary bone marrow involvement in patients with multiple myeloma. However, current commercial VNCa techniques suffer from excessive image noise an...