AIMC Topic: Machine Learning

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Learning clinically useful information from images: Past, present and future.

Medical image analysis
Over the last decade, research in medical imaging has made significant progress in addressing challenging tasks such as image registration and image segmentation. In particular, the use of model-based approaches has been key in numerous, successful a...

Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

Database : the journal of biological databases and curation
Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources...

Seizure Forecasting and the Preictal State in Canine Epilepsy.

International journal of neural systems
The ability to predict seizures may enable patients with epilepsy to better manage their medications and activities, potentially reducing side effects and improving quality of life. Forecasting epileptic seizures remains a challenging problem, but ma...

A machine-learning approach for predicting palmitoylation sites from integrated sequence-based features.

Journal of bioinformatics and computational biology
Palmitoylation is the covalent attachment of lipids to amino acid residues in proteins. As an important form of protein posttranslational modification, it increases the hydrophobicity of proteins, which contributes to the protein transportation, orga...

Non-invasive hypoglycemia monitoring system using extreme learning machine for Type 1 diabetes.

ISA transactions
Hypoglycemia is a very common in type 1 diabetic persons and can occur at any age. It is always threatening to the well-being of patients with Type 1 diabetes mellitus (T1DM) since hypoglycemia leads to seizures or loss of consciousness and the possi...

Topic detection using paragraph vectors to support active learning in systematic reviews.

Journal of biomedical informatics
Systematic reviews require expert reviewers to manually screen thousands of citations in order to identify all relevant articles to the review. Active learning text classification is a supervised machine learning approach that has been shown to signi...

TaggerOne: joint named entity recognition and normalization with semi-Markov Models.

Bioinformatics (Oxford, England)
MOTIVATION: Text mining is increasingly used to manage the accelerating pace of the biomedical literature. Many text mining applications depend on accurate named entity recognition (NER) and normalization (grounding). While high performing machine le...

Protease Inhibitors in View of Peptide Substrate Databases.

Journal of chemical information and modeling
Protease substrate profiling has nowadays almost become a routine task for experimentalists, and the knowledge on protease peptide substrates is easily accessible via the MEROPS database. We present a shape-based virtual screening workflow using vROC...

Forecast Modelling via Variations in Binary Image-Encoded Information Exploited by Deep Learning Neural Networks.

PloS one
Traditional forecasting models fit a function approximation from dependent invariables to independent variables. However, they usually get into trouble when date are presented in various formats, such as text, voice and image. This study proposes a n...

ATLAAS: an automatic decision tree-based learning algorithm for advanced image segmentation in positron emission tomography.

Physics in medicine and biology
Accurate and reliable tumour delineation on positron emission tomography (PET) is crucial for radiotherapy treatment planning. PET automatic segmentation (PET-AS) eliminates intra- and interobserver variability, but there is currently no consensus on...