AIMC Topic: Humans

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Systems metabolomics: from metabolomic snapshots to design principles.

Current opinion in biotechnology
Metabolomics is a rapidly expanding technology that finds increasing application in a variety of fields, form metabolic disorders to cancer, from nutrition and wellness to design and optimization of cell factories. The integration of metabolic snapsh...

Identification of herbal categories active in pain disorder subtypes by machine learning help reveal novel molecular mechanisms of algesia.

Pharmacological research
Chronic pain is highly prevalent and poorly controlled, of which the accurate underlying mechanisms need be further elucidated. Herbal drugs have been widely used for controlling various pain disorders. The systematic integration of pain herbal data ...

Flaws (and quality) in research today: can artificial intelligence intervene?

Systems biology in reproductive medicine
The existing flaws in both conducting and reporting of research have been outlined and criticized in the past. Weak research design, poor methodology, lack of fresh ideas and poor reporting are the main points to blame. Issues have been continually r...

Deep learning prediction of falls among nursing home residents with Alzheimer's disease.

Geriatrics & gerontology international
AIM: This study aimed to use a convolutional neural network (CNN) to investigate the associations between the time of falling and multiple complicating factors, including age, dementia severity, lower extremity strength and physical function, among n...

Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images.

Medical physics
PURPOSE: Needle-based procedures for diagnosing and treating prostate cancer, such as biopsy and brachytherapy, have incorporated three-dimensional (3D) transrectal ultrasound (TRUS) imaging to improve needle guidance. Using these images effectively ...

Weighted gene co-expression network analysis reveals specific modules and biomarkers in Parkinson's disease.

Neuroscience letters
BACKGROUND: Parkinson's disease (PD) ranks as the second most frequently occurring neurodegenerative disease. The precise pathogenic mechanism of this disease remains unknown. The aim of the present study was to identify the biomarkers in PD and clas...

Enhancing Top-Down Proteomics Data Analysis by Combining Deconvolution Results through a Machine Learning Strategy.

Journal of the American Society for Mass Spectrometry
Top-down mass spectrometry (MS) is a powerful tool for the identification and comprehensive characterization of proteoforms arising from alternative splicing, sequence variation, and post-translational modifications. However, the complex data set gen...

Application of deep learning techniques for heartbeats detection using ECG signals-analysis and review.

Computers in biology and medicine
Deep learning models have become a popular mode to classify electrocardiogram (ECG) data. Investigators have used a variety of deep learning techniques for this application. Herein, a detailed examination of deep learning methods for ECG arrhythmia d...

Dynamic Hand Gesture Recognition Based on a Leap Motion Controller and Two-Layer Bidirectional Recurrent Neural Network.

Sensors (Basel, Switzerland)
Dynamic hand gesture recognition is one of the most significant tools for human-computer interaction. In order to improve the accuracy of the dynamic hand gesture recognition, in this paper, a two-layer Bidirectional Recurrent Neural Network for the ...