AIMC Topic: Reproducibility of Results

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Revisiting Warfarin Dosing Using Machine Learning Techniques.

Computational and mathematical methods in medicine
Determining the appropriate dosage of warfarin is an important yet challenging task. Several prediction models have been proposed to estimate a therapeutic dose for patients. The models are either clinical models which contain clinical and demographi...

A Markov random field approach to group-wise registration/mosaicing with application to ultrasound.

Medical image analysis
In this paper we present a group-wise non-rigid registration/mosaicing algorithm based on block-matching, which is developed within a probabilistic framework. The discrete form of its energy functional is linked to a Markov Random Field (MRF) contain...

The rate of mucosal healing by azathioprine therapy and prediction by artificial systems.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
BACKGROUND/AIMS: We aimed to assess the effect of azathioprine on mucosal healing in patients with inflammatory bowel diseases (IBD). Artificial neural networks were applied to IBD data for predicting mucosal remission.

Control of a Wheelchair in an Indoor Environment Based on a Brain-Computer Interface and Automated Navigation.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The concept of controlling a wheelchair using brain signals is promising. However, the continuous control of a wheelchair based on unstable and noisy electroencephalogram signals is unreliable and generates a significant mental burden for the user. A...

Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest.

Medical image analysis
Cardiac computed tomography angiography (CTA) is a non-invasive method for anatomic evaluation of coronary artery stenoses. However, CTA is prone to artifacts that reduce the diagnostic accuracy to identify stenoses. Further, CTA does not allow for d...

Combined unsupervised-supervised classification of multiparametric PET/MRI data: application to prostate cancer.

NMR in biomedicine
Multiparametric medical imaging data can be large and are often complex. Machine learning algorithms can assist in image interpretation when reliable training data exist. In most cases, however, knowledge about ground truth (e.g. histology) and thus ...

Impact of relationships between test and training animals and among training animals on reliability of genomic prediction.

Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie
One of the factors affecting the reliability of genomic prediction is the relationship among the animals of interest. This study investigated the reliability of genomic prediction in various scenarios with regard to the relationship between test and ...

Identifying synonymy between relational phrases using word embeddings.

Journal of biomedical informatics
Many text mining applications in the biomedical domain benefit from automatic clustering of relational phrases into synonymous groups, since it alleviates the problem of spurious mismatches caused by the diversity of natural language expressions. Mos...

Non-parametric temporal modeling of the hemodynamic response function via a liquid state machine.

Neural networks : the official journal of the International Neural Network Society
Standard methods for the analysis of functional MRI data strongly rely on prior implicit and explicit hypotheses made to simplify the analysis. In this work the attention is focused on two such commonly accepted hypotheses: (i) the hemodynamic respon...

Echocardiogram enhancement using supervised manifold denoising.

Medical image analysis
This paper presents data-driven methods for echocardiogram enhancement. Existing denoising algorithms typically rely on a single noise model, and do not generalize to the composite noise sources typically found in real-world echocardiograms. Our meth...