AI Medical Compendium Topic

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

Gyrus Cinguli

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Machine Learning of Functional Magnetic Resonance Imaging Network Connectivity Predicts Substance Abuse Treatment Completion.

Biological psychiatry. Cognitive neuroscience and neuroimaging
BACKGROUND: Successfully treating illicit drug use has become paramount, yet elusive. Devising specialized treatment interventions could increase positive outcomes, but it is necessary to identify risk factors of poor long-term outcomes to develop sp...

[A sketch of the overlap in the neural circuitry underlying psychological- and physical-pain].

Sheng li xue bao : [Acta physiologica Sinica]
From the phenomenological point of view, pain can be classified into psychological-pain and physical-pain. Emerging evidence has shown that the psychological- and physical-pain recruit overlapping neural activity in regions associated with the affect...

Distributed representations of action sequences in anterior cingulate cortex: A recurrent neural network approach.

Psychonomic bulletin & review
Anterior cingulate cortex (ACC) has been the subject of intense debate over the past 2 decades, but its specific computational function remains controversial. Here we present a simple computational model of ACC that incorporates distributed represent...

Abnormal Low-Frequency Oscillations Reflect Trait-Like Pain Ratings in Chronic Pain Patients Revealed through a Machine Learning Approach.

The Journal of neuroscience : the official journal of the Society for Neuroscience
Measures of moment-to-moment fluctuations in brain activity of an individual at rest have been shown to be a sensitive and reliable metric for studying pathological brain mechanisms across various chronic pain patient populations. However, the relati...

Resting-state anticorrelated networks in Schizophrenia.

Psychiatry research. Neuroimaging
Converging evidences from different lines of research suggest abnormalities in functional brain connectivity in schizophrenia. While positively correlated brain networks have been well researched, anticorrelated functional connectivity remains under ...

Machine learning approach to identify a resting-state functional connectivity pattern serving as an endophenotype of autism spectrum disorder.

Brain imaging and behavior
Endophenotype refers to a measurable and heritable component between genetics and diagnosis, and the same endophenotype is present in both individuals with a diagnosis and their unaffected siblings. Determination of the neural correlates of an endoph...

Discriminating stress from rest based on resting-state connectivity of the human brain: A supervised machine learning study.

Human brain mapping
Acute stress induces large-scale neural reorganization with relevance to stress-related psychopathology. Here, we applied a novel supervised machine learning method, combining the strengths of a priori theoretical insights with a data-driven approach...

Evidence for distinct neuro-metabolic phenotypes in humans.

NeuroImage
Advances in magnetic resonance imaging have shown how individual differences in the structure and function of the human brain relate to health and cognition. The relationship between individual differences and the levels of neuro-metabolites, however...

Intelligent classification of major depressive disorder using rs-fMRI of the posterior cingulate cortex.

Journal of affective disorders
Major Depressive Disorder (MDD) is a widespread psychiatric condition that affects a significant portion of the global population. The classification and diagnosis of MDD is crucial for effective treatment. Traditional methods, based on clinical asse...