AI Medical Compendium Journal:
GigaScience

Showing 41 to 50 of 69 articles

Preventing dataset shift from breaking machine-learning biomarkers.

GigaScience
Machine learning brings the hope of finding new biomarkers extracted from cohorts with rich biomedical measurements. A good biomarker is one that gives reliable detection of the corresponding condition. However, biomarkers are often extracted from a ...

DeePhage: distinguishing virulent and temperate phage-derived sequences in metavirome data with a deep learning approach.

GigaScience
BACKGROUND: Prokaryotic viruses referred to as phages can be divided into virulent and temperate phages. Distinguishing virulent and temperate phage-derived sequences in metavirome data is important for elucidating their different roles in interactio...

RNAProt: an efficient and feature-rich RNA binding protein binding site predictor.

GigaScience
BACKGROUND: Cross-linking and immunoprecipitation followed by next-generation sequencing (CLIP-seq) is the state-of-the-art technique used to experimentally determine transcriptome-wide binding sites of RNA-binding proteins (RBPs). However, it relies...

ChronoRoot: High-throughput phenotyping by deep segmentation networks reveals novel temporal parameters of plant root system architecture.

GigaScience
BACKGROUND: Deep learning methods have outperformed previous techniques in most computer vision tasks, including image-based plant phenotyping. However, massive data collection of root traits and the development of associated artificial intelligence ...

U-Limb: A multi-modal, multi-center database on arm motion control in healthy and post-stroke conditions.

GigaScience
BACKGROUND: Shedding light on the neuroscientific mechanisms of human upper limb motor control, in both healthy and disease conditions (e.g., after a stroke), can help to devise effective tools for a quantitative evaluation of the impaired conditions...

Multi-stage malaria parasite recognition by deep learning.

GigaScience
MOTIVATION: Malaria, a mosquito-borne infectious disease affecting humans and other animals, is widespread in tropical and subtropical regions. Microscopy is the most common method for diagnosing the malaria parasite from stained blood smear samples....

Driftage: a multi-agent system framework for concept drift detection.

GigaScience
BACKGROUND: The amount of data and behavior changes in society happens at a swift pace in this interconnected world. Consequently, machine learning algorithms lose accuracy because they do not know these new patterns. This change in the data pattern ...

Fluorescence microscopy datasets for training deep neural networks.

GigaScience
BACKGROUND: Fluorescence microscopy is an important technique in many areas of biological research. Two factors that limit the usefulness and performance of fluorescence microscopy are photobleaching of fluorescent probes during imaging and, when ima...

MB-GAN: Microbiome Simulation via Generative Adversarial Network.

GigaScience
BACKGROUND: Trillions of microbes inhabit the human body and have a profound effect on human health. The recent development of metagenome-wide association studies and other quantitative analysis methods accelerate the discovery of the associations be...

Lilikoi V2.0: a deep learning-enabled, personalized pathway-based R package for diagnosis and prognosis predictions using metabolomics data.

GigaScience
BACKGROUND: previously we developed Lilikoi, a personalized pathway-based method to classify diseases using metabolomics data. Given the new trends of computation in the metabolomics field, it is important to update Lilikoi software.