AIMC Topic: Humans

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Neuronal differentiation strategies: insights from single-cell sequencing and machine learning.

Development (Cambridge, England)
Neuronal replacement therapies rely on the differentiation of specific cell types from embryonic or induced pluripotent stem cells, or on the direct reprogramming of differentiated adult cells via the expression of transcription factors or signaling...

Addressing taxonomic challenges for Internet Use Disorders in light of changing technologies and diagnostic classifications. •

Journal of behavioral addictions
Drawing a distinction between mobile and non-mobile Internet Use Disorders is an important step to clarify blurred current concepts in the field of behavioral addictions. Similarly, future technological advances related to virtual or augmented realit...

Detection of Hate Speech in COVID-19-Related Tweets in the Arab Region: Deep Learning and Topic Modeling Approach.

Journal of medical Internet research
BACKGROUND: The massive scale of social media platforms requires an automatic solution for detecting hate speech. These automatic solutions will help reduce the need for manual analysis of content. Most previous literature has cast the hate speech de...

A generative spiking neural-network model of goal-directed behaviour and one-step planning.

PLoS computational biology
In mammals, goal-directed and planning processes support flexible behaviour used to face new situations that cannot be tackled through more efficient but rigid habitual behaviours. Within the Bayesian modelling approach of brain and behaviour, models...

Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategy.

PloS one
The accurate segmentation and tracking of cells in microscopy image sequences is an important task in biomedical research, e.g., for studying the development of tissues, organs or entire organisms. However, the segmentation of touching cells in image...

Computerized Classification of Prostate Cancer Gleason Scores from Whole Slide Images.

IEEE/ACM transactions on computational biology and bioinformatics
Histological Gleason grading of tumor patterns is one of the most powerful prognostic predictors in prostate cancer. However, manual analysis and grading performed by pathologists are typically subjective and time-consuming. In this paper, we present...

Predicting MicroRNA Sequence Using CNN and LSTM Stacked in Seq2Seq Architecture.

IEEE/ACM transactions on computational biology and bioinformatics
CNN and LSTM have proven their ability in feature extraction and natural language processing, respectively. So, we tried to use their ability to process the language of RNAs, i.e., predicting sequence of microRNAs using the sequence of mRNA. The idea...

Bioimage-Based Prediction of Protein Subcellular Location in Human Tissue with Ensemble Features and Deep Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Prediction of protein subcellular location has currently become a hot topic because it has been proven to be useful for understanding both the disease mechanisms and novel drug design. With the rapid development of automated microscopic imaging techn...

Deep Learning for Automated Feature Discovery and Classification of Sleep Stages.

IEEE/ACM transactions on computational biology and bioinformatics
Convolutional neural networks (CNN) have demonstrated state-of-the-art classification results in image categorization, but have received comparatively little attention for classification of one-dimensional physiological signals. We design a deep CNN ...

Data-Driven Robust Control for a Closed-Loop Artificial Pancreas.

IEEE/ACM transactions on computational biology and bioinformatics
We present a fully closed-loop design for an artificial pancreas (AP) that regulates the delivery of insulin for the control of Type I diabetes. Our AP controller operates in a fully automated fashion, without requiring any manual interaction with th...