AI Medical Compendium Topic:
Computer Simulation

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Predicting transcriptional outcomes of novel multigene perturbations with GEARS.

Nature biotechnology
Understanding cellular responses to genetic perturbation is central to numerous biomedical applications, from identifying genetic interactions involved in cancer to developing methods for regenerative medicine. However, the combinatorial explosion in...

Evaluation of Spiking Neural Nets-Based Image Classification Using the Runtime Simulator RAVSim.

International journal of neural systems
Spiking Neural Networks (SNNs) help achieve brain-like efficiency and functionality by building neurons and synapses that mimic the human brain's transmission of electrical signals. However, optimal SNN implementation requires a precise balance of pa...

Cohort profile for development of machine learning models to predict healthcare-related adverse events (Demeter): clinical objectives, data requirements for modelling and overview of data set for 2016-2018.

BMJ open
PURPOSE: In-hospital health-related adverse events (HAEs) are a major concern for hospitals worldwide. In high-income countries, approximately 1 in 10 patients experience HAEs associated with their hospital stay. Estimating the risk of an HAE at the ...

SWsnn: A Novel Simulator for Spiking Neural Networks.

Journal of computational biology : a journal of computational molecular cell biology
Spiking neural network (SNN) simulators play an important role in neural system modeling and brain function research. They can help scientists reproduce and explore neuronal activities in brain regions, neuroscience, brain-like computing, and other f...

Enhanced wave overtopping simulation at vertical breakwaters using machine learning algorithms.

PloS one
Accurate prediction of wave overtopping at sea defences remains central to the protection of lives, livelihoods, and infrastructural assets in coastal zones. In addressing the increased risks of rising sea levels and more frequent storm surges, robus...

Advancing algorithmic drug product development: Recommendations for machine learning approaches in drug formulation.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Artificial intelligence is a rapidly expanding area of research, with the disruptive potential to transform traditional approaches in the pharmaceutical industry, from drug discovery and development to clinical practice. Machine learning, a subfield ...

Developing machine learning approaches to identify candidate persistent, mobile and toxic (PMT) and very persistent and very mobile (vPvM) substances based on molecular structure.

Water research
Determining which substances on the global market could be classified as persistent, mobile and toxic (PMT) substances or very persistent, very mobile (vPvM) substances is essential to prevent or reduce drinking water contamination from them. This st...

Modelling and robust controller design for an underactuated self-balancing robot with uncertain parameter estimation.

PloS one
A comprehensive literature review of self-balancing robot (SBR) provides an insight to the strengths and limitations of the available control techniques for different applications. Most of the researchers have not included the payload and its variati...

Improving drug discovery with a hybrid deep generative model using reinforcement learning trained on a Bayesian docking approximation.

Journal of computer-aided molecular design
Generative approaches to molecular design are an area of intense study in recent years as a method to generate new pharmaceuticals with desired properties. Often though, these types of efforts are constrained by limited experimental activity data, re...

Deep learning model fusion improves lung tumor segmentation accuracy across variable training-to-test dataset ratios.

Physical and engineering sciences in medicine
This study aimed to investigate the robustness of a deep learning (DL) fusion model for low training-to-test ratio (TTR) datasets in the segmentation of gross tumor volumes (GTVs) in three-dimensional planning computed tomography (CT) images for lung...