AI Medical Compendium Topic

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A novel trajectory learning method for robotic arms based on Gaussian Mixture Model and k-value selection algorithm.

PloS one
In the field of robotic arm trajectory imitation learning, Gaussian Mixture Models are widely used for their ability to capture the characteristics of complex trajectories. However, one major challenge in utilizing these models lies in the initializa...

Uncertainty modeling for inductive knowledge graph embedding.

Neural networks : the official journal of the International Neural Network Society
In the process of refining Knowledge Graphs (KGs), new entities emerge, and old entities evolve, which usually updates their attribute information and neighborhood structures. This results in a distribution shift problem for entity features in the em...

Active learning and Gaussian processes for the development of dissolution models: An AI-based data-efficient approach.

Journal of controlled release : official journal of the Controlled Release Society
In vitro dissolution testing plays a key role in controlling the quality and optimizing the formulation of solid dosage pharmaceutical products. Data-driven dissolution models can improve the efficiency of testing: their predictions can act as surrog...

Dataset-free weight-initialization on restricted Boltzmann machine.

Neural networks : the official journal of the International Neural Network Society
In feed-forward neural networks, dataset-free weight-initialization methods such as LeCun, Xavier (or Glorot), and He initializations have been developed. These methods randomly determine the initial values of weight parameters based on specific dist...

GeM: Gaussian embeddings with Multi-hop graph transfer for next POI recommendation.

Neural networks : the official journal of the International Neural Network Society
Next Point-of-Interest (POI) recommendation is crucial in location-based applications, analyzing user behavior patterns from historical trajectories. Existing studies usually use graph structures and attention mechanisms for sequential prediction wit...

Applying Gaussian Process Machine Learning and Modern Probabilistic Programming to Satellite Data to Infer CO Emissions.

Environmental science & technology
Satellite data provides essential insights into the spatiotemporal distribution of CO concentrations. However, many atmospheric inverse models fail to adequately incorporate the spatial and temporal correlations inherent in satellite observations and...

Linear regressive weighted Gaussian kernel liquid neural network for brain tumor disease prediction using time series data.

Scientific reports
A brain tumor is an abnormal growth of cells within the brain or surrounding tissues, which can be either benign or malignant. Brain tumors develop in various regions of the brain, each affecting different functions such as movement, speech, and visi...

Enhancing interdisciplinary image segmentation through a Gaussian-based modified local consensus spatial fuzzy approach.

Computers in biology and medicine
This study aims to introduce a generic fuzzy-based approach tailored explicitly for classifying images originating from an array of diverse sources, having varying degrees of spectral and spatial resolutions, inhomogeneity, artifacts, and entirely di...

Enhancing brain age estimation under uncertainty: A spectral-normalized neural gaussian process approach utilizing 2.5D slicing.

NeuroImage
Brain age gap, the difference between estimated brain age and chronological age via magnetic resonance imaging, has emerged as a pivotal biomarker in the detection of brain abnormalities. While deep learning is accurate in estimating brain age, the a...

Addressing model discrepancy in a clinical model of the oxygen dissociation curve.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Many mathematical models suffer from model discrepancy, posing a significant challenge to their use in clinical decision-making. In this article, we consider methods for addressing this issue. In the first approach, a mathematical model is treated as...