Virtual population generation is an emerging field in data science with numerous applications in healthcare towards the augmentation of clinical research databases with significant lack of population size. However, the impact of data augmentation on ...
International journal for numerical methods in biomedical engineering
Jun 6, 2021
We propose a method to discover differential equations describing the long-term dynamics of phenomena featuring a multiscale behavior in time, starting from measurements taken at the fast-scale. Our methodology is based on a synergetic combination of...
Despite years of research, the mechanisms governing the onset, relapse, symptomatology, and treatment of schizophrenia (SZ) remain elusive. The lack of appropriate analytic tools to deal with the heterogeneity and complexity of SZ may be one of the r...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jun 5, 2021
A dual-mode microscopic hyperspectral imager (DMHI) combined with a machine learning algorithm for the purpose of classifying origins and varieties of Tetrastigma hemsleyanum (T. hemsleyanum) was developed. By switching the illumination source, the D...
International journal of environmental research and public health
Jun 5, 2021
Artificial Intelligence in healthcare employs machine learning algorithms to emulate human cognition in the analysis of complicated or large sets of data. Specifically, artificial intelligence taps on the ability of computer algorithms and software w...
OBJECTIVE: Assess if deep learning-based artificial intelligence (AI) algorithm improves reader performance for lung cancer detection on chest X-rays (CXRs).
Biological experiments based on organ-on-chips (OOCs) exploit light Time-Lapse Microscopy (TLM) for a direct observation of cell movement that is an observable signature of underlying biological processes. A high spatial resolution is essential to ca...
AIMS: Models predicting mortality in heart failure (HF) patients are often limited with regard to performance and applicability. The aim of this study was to develop a reliable algorithm to compute expected in-hospital mortality rates in HF cohorts o...
Researchers have found that machine learning methods are typically better at prediction than econometric models when the choice environment is stable. We study hospital demand models, and evaluate the relative performance of machine learning algorith...
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