AIMC Topic: Machine Learning

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Brain tissues have single-voxel signatures in multi-spectral MRI.

NeuroImage
Since the seminal works by Brodmann and contemporaries, it is well-known that different brain regions exhibit unique cytoarchitectonic and myeloarchitectonic features. Transferring the approach of classifying brain tissues - and other tissues - based...

A first perturbome of Pseudomonas aeruginosa: Identification of core genes related to multiple perturbations by a machine learning approach.

Bio Systems
Tolerance to stress conditions is vital for organismal survival, including bacteria under specific environmental conditions, antibiotics, and other perturbations. Some studies have described common modulation and shared genes during stress response t...

CiwGAN and fiwGAN: Encoding information in acoustic data to model lexical learning with Generative Adversarial Networks.

Neural networks : the official journal of the International Neural Network Society
How can deep neural networks encode information that corresponds to words in human speech into raw acoustic data? This paper proposes two neural network architectures for modeling unsupervised lexical learning from raw acoustic inputs: ciwGAN (Catego...

Brain age prediction: A comparison between machine learning models using region- and voxel-based morphometric data.

Human brain mapping
Brain morphology varies across the ageing trajectory and the prediction of a person's age using brain features can aid the detection of abnormalities in the ageing process. Existing studies on such "brain age prediction" vary widely in terms of their...

Automatic phenotyping of electronical health record: PheVis algorithm.

Journal of biomedical informatics
Electronic Health Records (EHRs) often lack reliable annotation of patient medical conditions. Phenorm, an automated unsupervised algorithm to identify patient medical conditions from EHR data, has been developed. PheVis extends PheNorm at the visit ...

Image processing and machine learning for telehealth craniosynostosis screening in newborns.

Journal of neurosurgery. Pediatrics
OBJECTIVE: The authors sought to evaluate the accuracy of a novel telehealth-compatible diagnostic software system for identifying craniosynostosis within a newborn (< 1 year old) population. Agreement with gold standard craniometric diagnostics was ...

Exploration of natural red-shifted rhodopsins using a machine learning-based Bayesian experimental design.

Communications biology
Microbial rhodopsins are photoreceptive membrane proteins, which are used as molecular tools in optogenetics. Here, a machine learning (ML)-based experimental design method is introduced for screening rhodopsins that are likely to be red-shifted from...

Machine Learning for Prediction and Risk Stratification of Lupus Nephritis Renal Flare.

American journal of nephrology
BACKGROUND: Renal flare of lupus nephritis (LN) is strongly associated with poor kidney outcomes, and predicting renal flare and stratifying its risk are important for clinical decision-making and individualized management to reduce LN flare.