AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Markov Chains

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Neurocognitive Graphs of First-Episode Schizophrenia and Major Depression Based on Cognitive Features.

Neuroscience bulletin
Neurocognitive deficits are frequently observed in patients with schizophrenia and major depressive disorder (MDD). The relations between cognitive features may be represented by neurocognitive graphs based on cognitive features, modeled as Gaussian ...

A segmentation of brain MRI images utilizing intensity and contextual information by Markov random field.

Computer assisted surgery (Abingdon, England)
BACKGROUND AND OBJECTIVE: Image segmentation is a preliminary and fundamental step in computer aided magnetic resonance imaging (MRI) images analysis. But the performance of most current image segmentation methods is easily depreciated by noise in MR...

A New Approach to Predict user Mobility Using Semantic Analysis and Machine Learning.

Journal of medical systems
Mobility prediction is a technique in which the future location of a user is identified in a given network. Mobility prediction provides solutions to many day-to-day life problems. It helps in seamless handovers in wireless networks to provide better...

Music viewed by its entropy content: A novel window for comparative analysis.

PloS one
Polyphonic music files were analyzed using the set of symbols that produced the Minimal Entropy Description, which we call the Fundamental Scale. This allowed us to create a novel space to represent music pieces by developing: (a) a method to adjust ...

Unsupervised Segmentation of 5D Hyperpolarized Carbon-13 MRI Data Using a Fuzzy Markov Random Field Model.

IEEE transactions on medical imaging
Hyperpolarized MRI with C-labelled compounds is an emerging clinical technique allowing in vivo metabolic processes to be characterized non-invasively. Accurate quantification of C data, both for clinical and research purposes, typically relies on th...

Hidden Markov modeling of frequency-following responses to Mandarin lexical tones.

Journal of neuroscience methods
BACKGROUND: The frequency-following response (FFR) is a scalp-recorded electrophysiological potential reflecting phase-locked activity from neural ensembles in the auditory system. The FFR is often used to assess the robustness of subcortical pitch p...

Developmental Approach for Behavior Learning Using Primitive Motion Skills.

International journal of neural systems
Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet t...

DropConnected neural networks trained on time-frequency and inter-beat features for classifying heart sounds.

Physiological measurement
OBJECTIVE: Automatic heart sound analysis has the potential to improve the diagnosis of valvular heart diseases in the primary care phase, as well as in countries where there is neither the expertise nor the equipment to perform echocardiograms. An a...

Employing decomposable partially observable Markov decision processes to control gene regulatory networks.

Artificial intelligence in medicine
OBJECTIVE: Formulate the induction and control of gene regulatory networks (GRNs) from gene expression data using Partially Observable Markov Decision Processes (POMDPs).

Defining and characterizing the critical transition state prior to the type 2 diabetes disease.

PloS one
BACKGROUND: Type 2 diabetes mellitus (T2DM), with increased risk of serious long-term complications, currently represents 8.3% of the adult population. We hypothesized that a critical transition state prior to the new onset T2DM can be revealed throu...