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Chromosome-wide gene dosage rebalance may benefit tumor progression.

Molecular genetics and genomics : MGG
The high-risk of tumor initiation in patients with Turner syndrome (TS) characterized by X chromosome monosomy in women has been well established and aneuploidy, defined as an abnormal number of chromosomes, is a common feature in human cancer. Howev...

Electroencephalographic derived network differences in Lewy body dementia compared to Alzheimer's disease patients.

Scientific reports
Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) require differential management despite presenting with symptomatic overlap. Currently, there is a need of inexpensive DLB biomarkers which can be fulfilled by electroencephalography (EEG)....

Detecting and classifying lesions in mammograms with Deep Learning.

Scientific reports
In the last two decades, Computer Aided Detection (CAD) systems were developed to help radiologists analyse screening mammograms, however benefits of current CAD technologies appear to be contradictory, therefore they should be improved to be ultimat...

Dynamic functional network connectivity discriminates mild traumatic brain injury through machine learning.

NeuroImage. Clinical
Mild traumatic brain injury (mTBI) can result in symptoms that affect a person's cognitive and social abilities. Improvements in diagnostic methodologies are necessary given that current clinical techniques have limited accuracy and are solely based ...

Automatically measuring brain ventricular volume within PACS using artificial intelligence.

PloS one
The picture archiving and communications system (PACS) is currently the standard platform to manage medical images but lacks analytical capabilities. Staying within PACS, the authors have developed an automatic method to retrieve the medical data and...

Prediction of cardiac death after adenosine myocardial perfusion SPECT based on machine learning.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
BACKGROUND: We developed machine-learning (ML) models to estimate a patient's risk of cardiac death based on adenosine myocardial perfusion SPECT (MPS) and associated clinical data, and compared their performance to baseline logistic regression (LR)....

Predicting Treatment Response to Intra-arterial Therapies for Hepatocellular Carcinoma with the Use of Supervised Machine Learning-An Artificial Intelligence Concept.

Journal of vascular and interventional radiology : JVIR
PURPOSE: To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques.

Predictors of firearm violence in urban communities: A machine-learning approach.

Health & place
Interpersonal firearm violence is a leading cause of death and injuries in the United States. Identifying community characteristics associated with firearm violence is important to improve confounder selection and control in health research, to bette...