Interest in machine-learning applications within medicine has been growing, but few studies have progressed to deployment in patient care. We present a framework, context and ultimately guidelines for accelerating the translation of machine-learning-...
Trichomonas vaginalis (T. vaginalis) detection remains an unsolved problem in using of automated instruments for urinalysis. The study proposes a machine learning (ML)-based strategy to increase the detection rate of T. vaginalis in urine. On the bas...
Machine learning (ML) involves algorithms learning patterns in large, complex datasets to predict and classify. Algorithms include neural networks (NN), logistic regression (LR), and support vector machines (SVM). ML may generate substantial improvem...
Controlling the expression of genes is one of the key challenges of synthetic biology. Until recently fine-tuned control has been out of reach, particularly in eukaryotes owing to their complexity of gene regulation. With advances in machine learning...
Neural networks : the official journal of the International Neural Network Society
Aug 17, 2019
In this paper, we propose a distributed semi-supervised learning (DSSL) algorithm based on the extreme learning machine (ELM) algorithm over communication network using the event-triggered (ET) communication scheme. In DSSL problems, training data co...
To improve the performance of Intensive Care Units (ICUs), the field of bio-statistics has developed scores which try to predict the likelihood of negative outcomes. These help evaluate the effectiveness of treatments and clinical practice, and also ...
Virchows Archiv : an international journal of pathology
Aug 17, 2019
Estimation of risk of recurrence in early-stage oral tongue squamous cell carcinoma (OTSCC) remains a challenge in the field of head and neck oncology. We examined the use of artificial neural networks (ANNs) to predict recurrences in early-stage OTS...
The fast progress in research and development of multifunctional, distributed sensor networks has brought challenges in processing data from a large number of sensors. Using deep learning methods such as convolutional neural networks (CNN), it is pos...
International journal of law and psychiatry
Aug 17, 2019
Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction and psychiatric assessment. This article has two objectives. First, it clarifies which aspects of English Law are relevant in order to regulate the use ...
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