AIMC Topic: Humans

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Prior information-based high-resolution tomography image reconstruction from a single digitally reconstructed radiograph.

Physics in medicine and biology
Tomography images are essential for clinical diagnosis and trauma surgery, allowing doctors to understand the internal information of patients in more detail. Since the large amount of x-ray radiation from the continuous imaging during the process of...

Multi-Task Fusion for Improving Mammography Screening Data Classification.

IEEE transactions on medical imaging
Machine learning and deep learning methods have become essential for computer-assisted prediction in medicine, with a growing number of applications also in the field of mammography. Typically these algorithms are trained for a specific task, e.g., t...

Two-Stream Graph Convolutional Network for Intra-Oral Scanner Image Segmentation.

IEEE transactions on medical imaging
Precise segmentation of teeth from intra-oral scanner images is an essential task in computer-aided orthodontic surgical planning. The state-of-the-art deep learning-based methods often simply concatenate the raw geometric attributes (i.e., coordinat...

Research on Multiplayer Posture Estimation Technology of Sports Competition Video Based on Graph Neural Network Algorithm.

Computational intelligence and neuroscience
With the explosive growth of the number of sports videos, the traditional sports video analysis method based on manual annotation has been difficult to meet the growing demand because of its high cost and many limitations. The traditional model is us...

Robotically applied hemostatic clamping for care-under-fire: harnessing bomb robots for hemorrhage control.

Canadian journal of surgery. Journal canadien de chirurgie
BACKGROUND: Early hemorrhage control after interpersonal violence is the most urgent requirement to preserve life and is now recognized as a responsibility of law enforcement. Although earlier entry of first responders is advocated, many shooting sce...

Predicting the Survival of Cancer Patients With Multimodal Graph Neural Network.

IEEE/ACM transactions on computational biology and bioinformatics
In recent years, cancer patients survival prediction holds important significance for worldwide health problems, and has gained many researchers attention in medical information communities. Cancer patients survival prediction can be seen the classif...

Identifying Protein Subcellular Locations With Embeddings-Based node2loc.

IEEE/ACM transactions on computational biology and bioinformatics
Identifying protein subcellular locations is an important topic in protein function prediction. Interacting proteins may share similar locations. Thus, it is imperative to infer protein subcellular locations by taking protein-protein interactions (PP...

Unit-Vise: Deep Shallow Unit-Vise Residual Neural Networks With Transition Layer For Expert Level Skin Cancer Classification.

IEEE/ACM transactions on computational biology and bioinformatics
Many modern neural network architectures with over parameterized regime have been used for identification of skin cancer. Recent work showed that network, where the hidden units are polynomially smaller in size, showed better performance than overpar...

Multi-Modal Classification for Human Breast Cancer Prognosis Prediction: Proposal of Deep-Learning Based Stacked Ensemble Model.

IEEE/ACM transactions on computational biology and bioinformatics
Breast Cancer is a highly aggressive type of cancer generally formed in the cells of the breast. Despite significant advances in the treatment of primary breast cancer in the last decade, there is a dire need to attempt of an accurate predictive mode...

Factors associated with COVID-19 lethality in a hospital in the Cajamarca region in Peru.

Revista peruana de medicina experimental y salud publica
OBJECTIVE.: To identify the clinical and epidemiological characteristics related to lethality in patients hospitalized for COVID-19 at the Simón Bolívar Hospital in Cajamarca, during June-August 2020.