AIMC Topic: Humans

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Perceptions of Canadian radiation oncologists, radiation physicists, radiation therapists and radiation trainees about the impact of artificial intelligence in radiation oncology - national survey.

Journal of medical imaging and radiation sciences
BACKGROUND: Artificial Intelligence (AI) is making a continuous progression into the field of Radiation Oncology in Canada and globally. While this field continues to evolve, there is no clear understanding about how radiation oncologists, radiation ...

Weight-bearing CT in foot and ankle pathology.

Orthopaedics & traumatology, surgery & research : OTSR
Cone-beam scanners (CBCT) enable CT to be performed under weight-bearing - notably for the foot and ankle. The technology is not new: it has been used since 1996 in dental surgery, where it has come to replace panoramic X-ray. What is new is placing ...

Quantitative analysis of brain herniation from non-contrast CT images using deep learning.

Journal of neuroscience methods
BACKGROUND: Brain herniation is one of the fatal outcomes of increased intracranial pressure (ICP). It is caused due to the presence of hematoma or tumor mass in the brain. Ideal midline (iML) divides the healthy brain into two (right and left) nearl...

Whole and Part Adaptive Fusion Graph Convolutional Networks for Skeleton-Based Action Recognition.

Sensors (Basel, Switzerland)
Spatiotemporal graph convolution has made significant progress in skeleton-based action recognition in recent years. Most of the existing graph convolution methods take all the joints of the human skeleton as the overall modeling graph, ignoring the ...

Towards Deep Neural Network Models for the Prediction of the Blood-Brain Barrier Permeability for Diverse Organic Compounds.

Molecules (Basel, Switzerland)
Permeation through the blood-brain barrier (BBB) is among the most important processes controlling the pharmacokinetic properties of drugs and other bioactive compounds. Using the fragmental (substructural) descriptors representing the occurrence num...

Classification of Biodegradable Substances Using Balanced Random Trees and Boosted C5.0 Decision Trees.

International journal of environmental research and public health
Substances that do not degrade over time have proven to be harmful to the environment and are dangerous to living organisms. Being able to predict the biodegradability of substances without costly experiments is useful. Recently, the quantitative str...

Aligning text mining and machine learning algorithms with best practices for study selection in systematic literature reviews.

Systematic reviews
BACKGROUND: Despite existing research on text mining and machine learning for title and abstract screening, the role of machine learning within systematic literature reviews (SLRs) for health technology assessment (HTA) remains unclear given lack of ...

Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy.

Physics in medicine and biology
To study radiotherapy-related adverse effects, detailed dose information (3D distribution) is needed for accurate dose-effect modeling. For childhood cancer survivors who underwent radiotherapy in the pre-CT era, only 2D radiographs were acquired, th...