AIMC Topic: Magnetic Resonance Imaging

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Brain Age in Early Stages of Bipolar Disorders or Schizophrenia.

Schizophrenia bulletin
BACKGROUND: The greater presence of neurodevelopmental antecedants may differentiate schizophrenia from bipolar disorders (BD). Machine learning/pattern recognition allows us to estimate the biological age of the brain from structural magnetic resona...

[An artificial neural network model for glioma grading using image information].

Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences
To explore the feasibility and efficacy of artificial neural network for differentiating high-grade glioma and low-grade glioma using image information.
 Methods: A total of 130 glioma patients with confirmed pathological diagnosis were selected retr...

Large Cell Neuroendocrine Carcinoma of the Extrahepatic Bile Duct.

The Korean journal of gastroenterology = Taehan Sohwagi Hakhoe chi
Primary neuroendocrine tumors originating from the extrahepatic bile duct are rare. Among these tumors, large cell neuroendocrine carcinomas (NECs) are extremely rare. A 59-year-old man was admitted to Sanggye Paik Hospital with jaundice that started...

Quantifying Differences Between Passive and Task-Evoked Intrinsic Functional Connectivity in a Large-Scale Brain Simulation.

Brain connectivity
Establishing a connection between intrinsic and task-evoked brain activities is critical because it would provide a way to map task-related brain regions in patients unable to comply with such tasks. A crucial question within this realm is to what ex...

Neural mechanisms supporting the relationship between dispositional mindfulness and pain.

Pain
Interindividual differences in pain sensitivity vary as a function of interactions between sensory, cognitive-affective, and dispositional factors. Trait mindfulness, characterized as the innate capacity to nonreactively sustain attention to the pres...

Axillary Lymph Node Evaluation Utilizing Convolutional Neural Networks Using MRI Dataset.

Journal of digital imaging
The aim of this study is to evaluate the role of convolutional neural network (CNN) in predicting axillary lymph node metastasis, using a breast MRI dataset. An institutional review board (IRB)-approved retrospective review of our database from 1/201...

Neural Encoding and Decoding with Deep Learning for Dynamic Natural Vision.

Cerebral cortex (New York, N.Y. : 1991)
Convolutional neural network (CNN) driven by image recognition has been shown to be able to explain cortical responses to static pictures at ventral-stream areas. Here, we further showed that such CNN could reliably predict and decode functional magn...

From Machine Learning to Artificial Intelligence Applications in Cardiac Care.

Circulation
Artificial intelligence offers the potential for transformational advancement in cardiovascular care delivery, yet practical applications of this technology have yet to be embedded in clinical workflows and systems. Recent advances in machine learnin...

Machine learning analyses can differentiate meningioma grade by features on magnetic resonance imaging.

Neurosurgical focus
OBJECTIVEPrognostication and surgical planning for WHO grade I versus grade II meningioma requires thoughtful decision-making based on radiographic evidence, among other factors. Although conventional statistical models such as logistic regression ar...

Clinical Evaluation of a Multiparametric Deep Learning Model for Glioblastoma Segmentation Using Heterogeneous Magnetic Resonance Imaging Data From Clinical Routine.

Investigative radiology
OBJECTIVES: The aims of this study were, first, to evaluate a deep learning-based, automatic glioblastoma (GB) tumor segmentation algorithm on clinical routine data from multiple centers and compare the results to a ground truth, manual expert segmen...