AI Medical Compendium Topic

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Solving infinite-horizon optimalcontrol problems of the time-delayedsystems by a feed forward neural network model.

Network (Bristol, England)
A numerical method using neural network for solving infinite-horizon time-delayed optimal control problems is studied. The problem is first transformed, using a Páde approximation, to one without a time-delayed argument. By a suitable change of varia...

Systematic review of research design and reporting of imaging studies applying convolutional neural networks for radiological cancer diagnosis.

European radiology
OBJECTIVES: To perform a systematic review of design and reporting of imaging studies applying convolutional neural network models for radiological cancer diagnosis.

New Sensor Data Structuring for Deeper Feature Extraction in Human Activity Recognition.

Sensors (Basel, Switzerland)
For the effective application of thriving human-assistive technologies in healthcare services and human-robot collaborative tasks, computing devices must be aware of human movements. Developing a reliable real-time activity recognition method for the...

Machine Learning Applied to Clinical Laboratory Data in Spain for COVID-19 Outcome Prediction: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic is probably the greatest health catastrophe of the modern era. Spain's health care system has been exposed to uncontrollable numbers of patients over a short period, causing the system to collapse. Given that diagnos...

Artificial intelligence to deep learning: machine intelligence approach for drug discovery.

Molecular diversity
Drug designing and development is an important area of research for pharmaceutical companies and chemical scientists. However, low efficacy, off-target delivery, time consumption, and high cost impose a hurdle and challenges that impact drug design a...

Subsentence Extraction from Text Using Coverage-Based Deep Learning Language Models.

Sensors (Basel, Switzerland)
Sentiment prediction remains a challenging and unresolved task in various research fields, including psychology, neuroscience, and computer science. This stems from its high degree of subjectivity and limited input sources that can effectively captur...

Iterative guided machine learning-assisted systematic literature reviews: a diabetes case study.

Systematic reviews
BACKGROUND: Systematic Reviews (SR), studies of studies, use a formal process to evaluate the quality of scientific literature and determine ensuing effectiveness from qualifying articles to establish consensus findings around a hypothesis. Their val...

A novel end-to-end method to predict RNA secondary structure profile based on bidirectional LSTM and residual neural network.

BMC bioinformatics
BACKGROUND: Studies have shown that RNA secondary structure, a planar structure formed by paired bases, plays diverse vital roles in fundamental life activities and complex diseases. RNA secondary structure profile can record whether each base is pai...

Uncovering the structure of clinical EEG signals with self-supervised learning.

Journal of neural engineering
Supervised learning paradigms are often limited by the amount of labeled data that is available. This phenomenon is particularly problematic in clinically-relevant data, such as electroencephalography (EEG), where labeling can be costly in terms of s...

Machine learning for identifying relevant publications in updates of systematic reviews of diagnostic test studies.

Research synthesis methods
Updating systematic reviews is often a time-consuming process that involves a lot of human effort and is therefore not conducted as often as it should be. The aim of our research project was to explore the potential of machine learning methods to red...