AIMC Topic: Software

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genoDraw: A Web Tool for Developing Pedigree Diagrams Using the Standardized Human Pedigree Nomenclature Integrated with Biomedical Vocabularies.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The integration of genetic information in current clinical routine has raised a need for tools to exploit family genetic knowledge. On the clinical side, an application for managing and visualizing pedigree diagrams could provide genetics specialists...

SOMprocessor: A high throughput FPGA-based architecture for implementing Self-Organizing Maps and its application to video processing.

Neural networks : the official journal of the International Neural Network Society
The design of neuromorphic chips aims to develop electronic circuits dedicated to executing artificial neural networks, mainly by exploring parallel processing. Unsupervised learning models, such as Self-organizing Maps (SOM), may benefit from massiv...

CVSnet: A machine learning approach for automated central vein sign assessment in multiple sclerosis.

NMR in biomedicine
The central vein sign (CVS) is an efficient imaging biomarker for multiple sclerosis (MS) diagnosis, but its application in clinical routine is limited by inter-rater variability and the expenditure of time associated with manual assessment. We descr...

Comparing machine and human reviewers to evaluate the risk of bias in randomized controlled trials.

Research synthesis methods
BACKGROUND: Evidence from new health technologies is growing, along with demands for evidence to inform policy decisions, creating challenges in completing health technology assessments (HTAs)/systematic reviews (SRs) in a timely manner. Software can...

The hunt for sORFs: A multidisciplinary strategy.

Experimental cell research
Growing evidence illustrates the shortcomings on the current understanding of the full complexity of the proteome. Previously overlooked small open reading frames (sORFs) and their encoded microproteins have filled important gaps, exerting their func...

Software-assisted decision support in digital histopathology.

The Journal of pathology
Tissue diagnostics is the world of pathologists, and it is increasingly becoming digitalised to leverage the enormous potential of personalised medicine and of stratifying patients, enabling the administration of modern therapies. Therefore, the dail...

Exploring the Consistency of the Quality Scores with Machine Learning for Next-Generation Sequencing Experiments.

BioMed research international
BACKGROUND: Next-generation sequencing enables massively parallel processing, allowing lower cost than the other sequencing technologies. In the subsequent analysis with the NGS data, one of the major concerns is the reliability of variant calls. Alt...

A Comprehensive Machine-Learning-Based Software Pipeline to Classify EEG Signals: A Case Study on PNES vs. Control Subjects.

Sensors (Basel, Switzerland)
The diagnosis of psychogenic nonepileptic seizures (PNES) by means of electroencephalography (EEG) is not a trivial task during clinical practice for neurologists. No clear PNES electrophysiological biomarker has yet been found, and the only tool ava...

GenEpi: gene-based epistasis discovery using machine learning.

BMC bioinformatics
BACKGROUND: Genome-wide association studies (GWAS) provide a powerful means to identify associations between genetic variants and phenotypes. However, GWAS techniques for detecting epistasis, the interactions between genetic variants associated with ...

Machine learning helps identifying volume-confounding effects in radiomics.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Highlighting the risk of biases in radiomics-based models will help improve their quality and increase usage as decision support systems in the clinic. In this study we use machine learning-based methods to identify the presence of volume-confounding...