AIMC Topic: Humans

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Realistic CT data augmentation for accurate deep-learning based segmentation of head and neck tumors in kV images acquired during radiation therapy.

Medical physics
BACKGROUND: Using radiation therapy (RT) to treat head and neck (H&N) cancers requires precise targeting of the tumor to avoid damaging the surrounding healthy organs. Immobilisation masks and planning target volume margins are used to attempt to mit...

Digital Histopathology by Infrared Spectroscopic Imaging.

Annual review of analytical chemistry (Palo Alto, Calif.)
Infrared (IR) spectroscopic imaging records spatially resolved molecular vibrational spectra, enabling a comprehensive measurement of the chemical makeup and heterogeneity of biological tissues. Combining this novel contrast mechanism in microscopy w...

Rema-Net: An efficient multi-attention convolutional neural network for rapid skin lesion segmentation.

Computers in biology and medicine
For clinical treatment, the accurate segmentation of lesions from dermoscopic images is extremely valuable. Convolutional neural networks (such as U-Net and its numerous variants) have become the main methods for skin lesion segmentation in recent ye...

An automatic fresh rib fracture detection and positioning system using deep learning.

The British journal of radiology
OBJECTIVE: To evaluate the performance and robustness of a deep learning-based automatic fresh rib fracture detection and positioning system (FRF-DPS).

Inference of chronic obstructive pulmonary disease with deep learning on raw spirograms identifies new genetic loci and improves risk models.

Nature genetics
Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is highly heritable. While COPD is clinically defined by applying thresholds to summary measures of lung function, a quantitative liability score has more power...

Fuzzy Adaptive Passive Control Strategy Design for Upper-Limb End-Effector Rehabilitation Robot.

Sensors (Basel, Switzerland)
Robot-assisted rehabilitation therapy has been proven to effectively improve upper-limb motor function in stroke patients. However, most current rehabilitation robotic controllers will provide too much assistance force and focus only on the patient's...

Facilitating deep learning through preprocessing of optical coherence tomography images.

BMC ophthalmology
BACKGROUND: While deep learning has delivered promising results in the field of ophthalmology, the hurdle to complete a deep learning study is high. In this study, we aim to facilitate small scale model trainings by exploring the role of preprocessin...

Value of handcrafted and deep radiomic features towards training robust machine learning classifiers for prediction of prostate cancer disease aggressiveness.

Scientific reports
There is a growing piece of evidence that artificial intelligence may be helpful in the entire prostate cancer disease continuum. However, building machine learning algorithms robust to inter- and intra-radiologist segmentation variability is still a...

An investigation into epidemiological situations of COVID-19 with fuzzy K-means and K-prototype clustering methods.

Scientific reports
The ten countries with the highest population during the pandemic were analyzed for clustering based on the quantitative numbers of COVID-19 and policy plans. The Fuzzy K-Means (FKM) and K-prototype algorithms were used for clustering, and various pe...

A convolutional attention mapping deep neural network for classification and localization of cardiomegaly on chest X-rays.

Scientific reports
Building a reliable and precise model for disease classification and identifying abnormal sites can provide physicians assistance in their decision-making process. Deep learning based image analysis is a promising technique for enriching the decision...