AIMC Topic: Machine Learning

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Machine learning with multiparametric magnetic resonance imaging of the breast for early prediction of response to neoadjuvant chemotherapy.

Breast (Edinburgh, Scotland)
In patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy (NAC), some patients achieve a complete pathologic response (pCR), some achieve a partial response, and some do not respond at all or even progress. Accurate predicti...

Spatiotemporal dynamics of urbanization and cropland in the Nile Delta of Egypt using machine learning and satellite big data: implications for sustainable development.

Environmental monitoring and assessment
The Nile Delta of Egypt is increasingly facing sustainability threats, due to a combination of nature- and human-induced changes in land cover and land use. In this paper, an analysis of big time series data from remotely sensed satellite images and ...

Potential use of machine learning methods in assessment of Fusarium culmorum and Fusariumproliferatum growth and mycotoxin production in treatments with antifungal agents.

Fungal biology
Fusarium-controlling fungicides are necessary to limit crop loss. Little is known about the effect of antifungal formulations at sub-lethal doses, and their interaction with abiotic factors, on Fusarium culmorum and F. proliferatum development and on...

Dimension independent bounds for general shallow networks.

Neural networks : the official journal of the International Neural Network Society
This paper proves an abstract theorem addressing in a unified manner two important problems in function approximation: avoiding curse of dimensionality and estimating the degree of approximation for out-of-sample extension in manifold learning. We co...

Simultaneously learning affinity matrix and data representations for machine fault diagnosis.

Neural networks : the official journal of the International Neural Network Society
Recently, preserving geometry information of data while learning representations have attracted increasing attention in intelligent machine fault diagnosis. Existing geometry preserving methods require to predefine the similarities between data point...

Prediction of lithium response using clinical data.

Acta psychiatrica Scandinavica
OBJECTIVE: Promptly establishing maintenance therapy could reduce morbidity and mortality in patients with bipolar disorder. Using a machine learning approach, we sought to evaluate whether lithium responsiveness (LR) is predictable using clinical ma...

An Overview of Machine Learning and Big Data for Drug Toxicity Evaluation.

Chemical research in toxicology
Drug toxicity evaluation is an essential process of drug development as it is reportedly responsible for the attrition of approximately 30% of drug candidates. The rapid increase in the number and types of large toxicology data sets together with the...

Machine-Learning-Based Predictive Modeling of Glass Transition Temperatures: A Case of Polyhydroxyalkanoate Homopolymers and Copolymers.

Journal of chemical information and modeling
Polyhydroxyalkanoate-based polymers-being ecofriendly, biosynthesizable, and economically viable and possessing a broad range of tunable properties-are currently being actively pursued as promising alternatives for petroleum-based plastics. The vast ...