AI Medical Compendium Topic:
Models, Biological

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Inter-foetus Membrane Segmentation for TTTS Using Adversarial Networks.

Annals of biomedical engineering
Twin-to-Twin Transfusion Syndrome is commonly treated with minimally invasive laser surgery in fetoscopy. The inter-foetal membrane is used as a reference to find abnormal anastomoses. Membrane identification is a challenging task due to small field ...

Location of sources in reaction-diffusion equations using support vector machines.

PloS one
The reaction-diffusion equation serves to model systems in the diffusion regime with sources. Specific applications include diffusion processes in chemical reactions, as well as the propagation of species, diseases, and populations in general. In som...

Behavioural analysis of single-cell aneural ciliate, using machine learning approaches.

Journal of the Royal Society, Interface
There is still a significant gap between our understanding of neural circuits and the behaviours they compute-i.e. the computations performed by these neural networks (Carandini 2012 , 507-509. (doi:10.1038/nn.3043)). Cellular decision-making process...

Evaluation of colorectal cancer subtypes and cell lines using deep learning.

Life science alliance
Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniques have been used to better understand the variability between tumors and disease models such as cel...

Soft Ring-Shaped Cellu-Robots with Simultaneous Locomotion in Batches.

Advanced materials (Deerfield Beach, Fla.)
Untethered mini-robots can move single cells or aggregates to build complex constructs in confined spaces and may enable various biomedical applications such as regenerative repair in medicine and biosensing in bioengineering. However, a significant ...

Machine Learning Approaches for the Prioritization of Genomic Variants Impacting Pre-mRNA Splicing.

Cells
Defects in pre-mRNA splicing are frequently a cause of Mendelian disease. Despite the advent of next-generation sequencing, allowing a deeper insight into a patient's variant landscape, the ability to characterize variants causing splicing defects ha...

Gene expression based survival prediction for cancer patients-A topic modeling approach.

PloS one
Cancer is one of the leading cause of death, worldwide. Many believe that genomic data will enable us to better predict the survival time of these patients, which will lead to better, more personalized treatment options and patient care. As standard ...

Predicting O-Water PET cerebral blood flow maps from multi-contrast MRI using a deep convolutional neural network with evaluation of training cohort bias.

Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism
To improve the quality of MRI-based cerebral blood flow (CBF) measurements, a deep convolutional neural network (dCNN) was trained to combine single- and multi-delay arterial spin labeling (ASL) and structural images to predict gold-standard O-water ...

Cancer Modeling-on-a-Chip with Future Artificial Intelligence Integration.

Small (Weinheim an der Bergstrasse, Germany)
Cancer is one of the leading causes of death worldwide, despite the large efforts to improve the understanding of cancer biology and development of treatments. The attempts to improve cancer treatment are limited by the complexity of the local milieu...

Early and Late Fusion Machine Learning on Multi-Frequency Electrical Impedance Data to Improve Radiofrequency Ablation Monitoring.

IEEE journal of biomedical and health informatics
Radiofrequency ablation (RFA) is a popular modality for tumor treatment. However, inexpensive real-time monitoring of RFA within multiple tissue types is still an ongoing research topic. The objective of this study is to utilize multi-frequency elect...