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Integrative analysis and machine learning on cancer genomics data using the Cancer Systems Biology Database (CancerSysDB).

BMC bioinformatics
BACKGROUND: Recent cancer genome studies on many human cancer types have relied on multiple molecular high-throughput technologies. Given the vast amount of data that has been generated, there are surprisingly few databases which facilitate access to...

Risk Assessment for Parents Who Suspect Their Child Has Autism Spectrum Disorder: Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: Parents are likely to seek Web-based communities to verify their suspicions of autism spectrum disorder markers in their child. Automated tools support human decisions in many domains and could therefore potentially support concerned pare...

A Dynamic Connectome Supports the Emergence of Stable Computational Function of Neural Circuits through Reward-Based Learning.

eNeuro
Synaptic connections between neurons in the brain are dynamic because of continuously ongoing spine dynamics, axonal sprouting, and other processes. In fact, it was recently shown that the spontaneous synapse-autonomous component of spine dynamics is...
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Test-retest reliability of the KINARM end-point robot for assessment of sensory, motor and neurocognitive function in young adult athletes.

PloS one
BACKGROUND: Current assessment tools for sport-related concussion are limited by a reliance on subjective interpretation and patient symptom reporting. Robotic assessments may provide more objective and precise measures of neurological function than ...

An Efficient Mixed-Model for Screening Differentially Expressed Genes of Breast Cancer Based on LR-RF.

IEEE/ACM transactions on computational biology and bioinformatics
To screen differentially expressed genes quickly and efficiently in breast cancer, two gene microarray datasets of breast cancer, GSE15852 and GSE45255, were downloaded from GEO. By combining the Logistic Regression and Random Forest algorithm, this ...

The inhibitory effect of functional lesions on eloquent brain areas: from research bench to operating bed.

The International journal of neuroscience
Functioning, but injured cerebral connections are hypothesized to inhibit cortical plasticity. Study of neural networks can validate this hypothesis, and provide further practical clues for clinical and surgical options to restore function in eloque...

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

Cancer gene therapy
Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key gen...

Artificial intelligence weights the importance of factors predicting complete cytoreduction at secondary cytoreductive surgery for recurrent ovarian cancer.

Journal of gynecologic oncology
OBJECTIVE: Accumulating evidence support that complete cytoreduction (CC) at the time of secondary cytoreductive surgery (SCS) improves survival in patients affected by recurrent ovarian cancer (ROC). Here, we aimed to determine whether artificial in...

3D Randomized Connection Network with Graph-based Label Inference.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In this paper, a novel 3D deep learning network is proposed for brain MR image segmentation with randomized connection, which can decrease the dependency between layers and increase the network capacity. The convolutional LSTM and 3D convolution are ...

Multiple Machine Learning Based-Chemoinformatics Models for Identification of Histone Acetyl Transferase Inhibitors.

Molecular informatics
The histone acetyl transferase (HAT) are involved in acetylation of histones that lead to transcription activation in numerous gene regulatory mechanisms. There are very few GCN5 HAT inhibitors reported despite of their role in cancer progression. In...