AI Medical Compendium Topic

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Markov Chains

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Neural parameter calibration and uncertainty quantification for epidemic forecasting.

PloS one
The recent COVID-19 pandemic has thrown the importance of accurately forecasting contagion dynamics and learning infection parameters into sharp focus. At the same time, effective policy-making requires knowledge of the uncertainty on such prediction...

Enhanced Sampling of Biomolecular Slow Conformational Transitions Using Adaptive Sampling and Machine Learning.

Journal of chemical theory and computation
Biomolecular simulations often suffer from the "time scale problem", hindering the study of rare events occurring over extended time scales. Enhanced sampling techniques aim to alleviate this issue by accelerating conformational transitions, yet they...

Optimization control for mean square synchronization of stochastic semi-Markov jump neural networks with non-fragile hidden information and actuator saturation.

Neural networks : the official journal of the International Neural Network Society
This paper studies the asynchronous output feedback control and H synchronization problems for a class of continuous-time stochastic hidden semi-Markov jump neural networks (SMJNNs) affected by actuator saturation. Initially, a novel neural networks ...

Tiberius: end-to-end deep learning with an HMM for gene prediction.

Bioinformatics (Oxford, England)
MOTIVATION: For more than 25 years, learning-based eukaryotic gene predictors were driven by hidden Markov models (HMMs), which were directly inputted a DNA sequence. Recently, Holst et al. demonstrated with their program Helixer that the accuracy of...

Comparing machine learning and deep learning models to predict cognition progression in Parkinson's disease.

Clinical and translational science
Cognitive decline in Parkinson's disease (PD) varies widely. While models to predict cognitive progression exist, comparing traditional probabilistic models to deep learning methods remains understudied. This study compares sequential modeling techni...

Cost-effectiveness and cost-utility of community-based blinding fundus diseases screening with artificial intelligence: A modelling study from Shanghai, China.

Computers in biology and medicine
BACKGROUND: With application of artificial intelligence (AI) in the disease screening, process reengineering occurred simultaneously. Whether process reengineering deserves special emphasis in AI implementation in the community-based blinding fundus ...

Reinforced Metapath Optimization in Heterogeneous Information Networks for Drug-Target Interaction Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Graph neural networks offer an effective avenue for predicting drug-target interactions. In this domain, researchers have found that constructing heterogeneous information networks based on metapaths using diverse biological datasets enhances predict...

Mitigating epidemic spread in complex networks based on deep reinforcement learning.

Chaos (Woodbury, N.Y.)
Complex networks are susceptible to contagious cascades, underscoring the urgency for effective epidemic mitigation strategies. While physical quarantine is a proven mitigation measure for mitigation, it can lead to substantial economic repercussions...

Flow Matching for Optimal Reaction Coordinates of Biomolecular Systems.

Journal of chemical theory and computation
We present flow matching for reaction coordinates (FMRC), a novel deep learning algorithm designed to identify optimal reaction coordinates (RC) in biomolecular reversible dynamics. FMRC is based on the mathematical principles of lumpability and deco...

Cost-effectiveness of a machine learning risk prediction model (LungFlag) in the selection of high-risk individuals for non-small cell lung cancer screening in Spain.

Journal of medical economics
OBJECTIVE: The LungFlag risk prediction model uses individualized clinical variables to identify individuals at high-risk of non-small cell lung cancer (NSCLC) for screening with low-dose computed tomography (LDCT). This study evaluates the cost-effe...