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Convolutional Neural Network for Histopathological Analysis of Osteosarcoma.

Journal of computational biology : a journal of computational molecular cell biology
Pathologists often deal with high complexity and sometimes disagreement over osteosarcoma tumor classification due to cellular heterogeneity in the dataset. Segmentation and classification of histology tissue in H&E stained tumor image datasets is a ...

Evaluation of genotoxic effects in Brazilian agricultural workers exposed to pesticides and cigarette smoke using machine-learning algorithms.

Environmental science and pollution research international
Monitoring exposure to xenobiotics by biomarker analyses, such as a micronucleus assay, is extremely important for the precocious detection and prevention of diseases, such as oral cancer. The aim of this study was to evaluate genotoxic effects in ru...
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MRI features predict p53 status in lower-grade gliomas via a machine-learning approach.

NeuroImage. Clinical
BACKGROUND: P53 mutation status is a pivotal biomarker for gliomas. Here, we developed a machine-learning model to predict p53 status in lower-grade gliomas based on radiomic features extracted from conventional magnetic resonance (MR) images.

Codebook-based electrooculography data analysis towards cognitive activity recognition.

Computers in biology and medicine
With the advancement in mobile/wearable technology, people started to use a variety of sensing devices to track their daily activities as well as health and fitness conditions in order to improve the quality of life. This work addresses an idea of ey...

Thread based electrofluidic platform for direct metabolite analysis in complex samples.

Analytica chimica acta
The application of electrophoresis upon commercial threads is investigated for development of low-cost diagnostics assays, designed for the matrix separation and quantification of low abundance metabolites in complex samples - in this work riboflavin...
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Neurobiological support to the diagnosis of ADHD in stimulant-naïve adults: pattern recognition analyses of MRI data.

Acta psychiatrica Scandinavica
OBJECTIVE: In adulthood, the diagnosis of attention-deficit/hyperactivity disorder (ADHD) has been subject of recent controversy. We searched for a neuroanatomical signature associated with ADHD spectrum symptoms in adults by applying, for the first ...

Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.

Medical physics
PURPOSE: Delineation of the clinical target volume (CTV) and organs at risk (OARs) is very important for radiotherapy but is time-consuming and prone to inter-observer variation. Here, we proposed a novel deep dilated convolutional neural network (DD...

Validation of an online risk calculator for the prediction of anastomotic leak after colon cancer surgery and preliminary exploration of artificial intelligence-based analytics.

Techniques in coloproctology
BACKGROUND: Recently published data support the use of a web-based risk calculator ( www.anastomoticleak.com ) for the prediction of anastomotic leak after colectomy. The aim of this study was to externally validate this calculator on a larger datase...

Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis.

IEEE journal of biomedical and health informatics
The past decade has seen an explosion in the amount of digital information stored in electronic health records (EHRs). While primarily designed for archiving patient information and performing administrative healthcare tasks like billing, many resear...