AIMC Topic: Humans

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Deep learning-based diagnosis from endobronchial ultrasonography images of pulmonary lesions.

Scientific reports
Endobronchial ultrasonography with a guide sheath (EBUS-GS) improves the accuracy of bronchoscopy. The possibility of differentiating benign from malignant lesions based on EBUS findings may be useful in making the correct diagnosis. The convolutiona...

Deep learning methods to predict amyotrophic lateral sclerosis disease progression.

Scientific reports
Amyotrophic lateral sclerosis (ALS) is a highly complex and heterogeneous neurodegenerative disease that affects motor neurons. Since life expectancy is relatively low, it is essential to promptly understand the course of the disease to better target...

Distance and similarity measures for normal wiggly dual hesitant fuzzy sets and their application in medical diagnosis.

Scientific reports
The normal wiggly dual hesitant fuzzy set (NWDHFS) is a modern mathematical tool that can be used to express the deep ideas of membership and non-membership information hidden in the thought-level of decision-makers (DMs). To enhance and expand the a...

Deep learning for quality assessment of optical coherence tomography angiography images.

Scientific reports
Optical coherence tomography angiography (OCTA) is an emerging non-invasive technique for imaging the retinal vasculature. While there are many promising clinical applications for OCTA, determination of image quality remains a challenge. We developed...

Development of deep learning chest X-ray model for cardiac dose prediction in left-sided breast cancer radiotherapy.

Scientific reports
Deep inspiration breath-hold (DIBH) is widely used to reduce the cardiac dose in left-sided breast cancer radiotherapy. This study aimed to develop a deep learning chest X-ray model for cardiac dose prediction to select patients with a potentially hi...

Visualization deep learning model for automatic arrhythmias classification.

Physiological measurement
With the improvement of living standards, heart disease has become one of the common diseases that threaten human health. Electrocardiography (ECG) is an effective way of diagnosing cardiovascular diseases. With the rapid growth of ECG examinations a...

A systematic review of deep learning methods for modeling electrocardiograms during sleep.

Physiological measurement
Sleep is one of the most important human physiological activities, and plays an essential role in human health. Polysomnography (PSG) is the gold standard for measuring sleep quality and disorders, but it is time-consuming, labor-intensive, and prone...

De novo spatiotemporal modelling of cell-type signatures in the developmental human heart using graph convolutional neural networks.

PLoS computational biology
With the emergence of high throughput single cell techniques, the understanding of the molecular and cellular diversity of mammalian organs have rapidly increased. In order to understand the spatial organization of this diversity, single cell data is...

Scoping review of the current landscape of AI-based applications in clinical trials.

Frontiers in public health
BACKGROUND: Clinical trials are essential for bringing new drugs, technologies and procedures to the market and clinical practice. Considering the design and the four-phase development, only 10% of them complete the entire process, partly due to the ...

Pneumonia Detection in Chest X-Ray Images Using Enhanced Restricted Boltzmann Machine.

Journal of healthcare engineering
The process of pneumonia detection has been the focus of researchers as it has proved itself to be one of the most dangerous and life-threatening disorders. In recent years, many machine learning and deep learning algorithms have been applied in an a...