AIMC Topic: Reproducibility of Results

Clear Filters Showing 3871 to 3880 of 5908 articles

A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data.

Nature genetics
Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is required as a final step after automated processing. However, manual variant refinement is time-consumin...

ProvCaRe: Characterizing scientific reproducibility of biomedical research studies using semantic provenance metadata.

International journal of medical informatics
OBJECTIVE: Reproducibility of research studies is key to advancing biomedical science by building on sound results and reducing inconsistencies between published results and study data. We propose that the available data from research studies combine...

Automated detection of lung cancer at ultralow dose PET/CT by deep neural networks - Initial results.

Lung cancer (Amsterdam, Netherlands)
OBJECTIVES: We evaluated whether machine learning may be helpful for the detection of lung cancer in FDG-PET imaging in the setting of ultralow dose PET scans.

A novel retinal vessel detection approach based on multiple deep convolution neural networks.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detec...

Toward analyzing and synthesizing previous research in early prediction of cardiac arrest using machine learning based on a multi-layered integrative framework.

Journal of biomedical informatics
BACKGROUND: One of the significant problems in the field of healthcare is the low survival rate of people who have experienced sudden cardiac arrest. Early prediction of cardiac arrest can provide the time required for intervening and preventing its ...

Ground Glass Lesions on Chest Imaging: Evaluation of Reported Incidence in Cancer Patients Using Natural Language Processing.

The Annals of thoracic surgery
BACKGROUND: Ground glass opacities (GGOs) on computed tomography (CT) have gained significant recent attention, with unclear incidence and epidemiologic patterns. Natural language processing (NLP) is a powerful computing tool that collects variables ...

3D regression neural network for the quantification of enlarged perivascular spaces in brain MRI.

Medical image analysis
Enlarged perivascular spaces (EPVS) in the brain are an emerging imaging marker for cerebral small vessel disease, and have been shown to be related to increased risk of various neurological diseases, including stroke and dementia. Automated quantifi...