AI Medical Compendium Topic:
Computer Simulation

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Fostering discoveries in the era of exascale computing: How the next generation of supercomputers empowers computational and experimental biophysics alike.

Biophysical journal
Over a century ago, physicists started broadly relying on theoretical models to guide new experiments. Soon thereafter, chemists began doing the same. Now, biological research enters a new era when experiment and theory walk hand in hand. Novel softw...

Simulation-based inference for non-parametric statistical comparison of biomolecule dynamics.

PLoS computational biology
Numerous models have been developed to account for the complex properties of the random walks of biomolecules. However, when analysing experimental data, conditions are rarely met to ensure model identification. The dynamics may simultaneously be inf...

Improving Generalization by Learning Geometry-Dependent and Physics-Based Reconstruction of Image Sequences.

IEEE transactions on medical imaging
Deep neural networks have shown promise in image reconstruction tasks, although often on the premise of large amounts of training data. In this paper, we present a new approach to exploit the geometry and physics underlying electrocardiographic imagi...

Simulation of Postoperative Facial Appearances via Geometric Deep Learning for Efficient Orthognathic Surgical Planning.

IEEE transactions on medical imaging
Orthognathic surgery corrects jaw deformities to improve aesthetics and functions. Due to the complexity of the craniomaxillofacial (CMF) anatomy, orthognathic surgery requires precise surgical planning, which involves predicting postoperative change...

Asynchronous dissipative stabilization for stochastic Markov-switching neural networks with completely- and incompletely-known transition rates.

Neural networks : the official journal of the International Neural Network Society
The asynchronous dissipative stabilization for stochastic Markov-switching neural networks (SMSNNs) is investigated. The aim is to design an output-feedback controller with inconsistent mode switching to ensure that the SMSNN is stochastically stable...

Machine learning assisted hepta band THz metamaterial absorber for biomedical applications.

Scientific reports
A hepta-band terahertz metamaterial absorber (MMA) with modified dual T-shaped resonators deposited on polyimide is presented for sensing applications. The proposed polarization sensitive MMA is ultra-thin (0.061 λ) and compact (0.21 λ) at its lowest...

Simulation-to-real generalization for deep-learning-based refraction-corrected ultrasound tomography image reconstruction.

Physics in medicine and biology
. The image reconstruction of ultrasound computed tomography is computationally expensive with conventional iterative methods. The fully learned direct deep learning reconstruction is promising to speed up image reconstruction significantly. However,...

A hybrid intelligent model for early validation of infectious diseases: An explorative study of machine learning approaches.

Microscopy research and technique
Literature reports several infectious diseases news validation approaches, but none is economically effective for collecting and classifying information on different infectious diseases. This work presents a hybrid machine-learning model that could p...

Detector shifting and deep learning based ring artifact correction method for low-dose CT.

Medical physics
BACKGROUND: In x-ray computed tomography (CT), the gain inconsistency of detector units leads to ring artifacts in the reconstructed images, seriously destroys the image structure, and is not conducive to image recognition. In addition, to reduce rad...

Prediction of human thermal comfort preference based on supervised learning.

Journal of thermal biology
Human thermal comfort is relevant to human life comfort and plays a pivotal role in occupational health and thermal safety. To ensure that intelligent temperature-controlled equipment can deliver a sense of cosiness to people while improving its ener...