A connected component in a graph is a set of nodes linked to each other by paths. The problem of finding connected components has been applied to diverse graph analysis tasks such as graph partitioning, graph compression, and pattern recognition. Sev...
BACKGROUND: Many mortality prediction models have been developed for patients in intensive care units (ICUs); most are based on data available at ICU admission. We investigated whether machine learning methods using analyses of time-series data impro...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Approximately 60 million people worldwide suffer from epileptic seizures. A key challenge in machine learning ap proaches for epilepsy research is the lack of a data resource of analysis-ready (no additional preprocessing is needed when using the dat...
Chromatin interaction studies can reveal how the genome is organized into spatially confined sub-compartments in the nucleus. However, accurately identifying sub-compartments from chromatin interaction data remains a challenge in computational biolog...
Environmental pollution (Barking, Essex : 1987)
Feb 19, 2020
Mining activities change the chemical composition of the environment and have negative reflection on people's health and there is no single measure to deal with adverse consequences of mining activities, as each case is specific and needs to be under...
BACKGROUND AND OBJECTIVE: Multimodal data analysis and large-scale computational capability is entering medicine in an accelerative fashion and has begun to influence investigational work in a variety of disciplines. It is also informing us of therap...
Clinical pharmacology and therapeutics
Feb 17, 2020
Clinical pharmacology is a multidisciplinary data sciences field that utilizes mathematical and statistical methods to generate maximal knowledge from data. Pharmacometrics (PMX) is a well-recognized tool to characterize disease progression, pharmaco...
Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
Feb 12, 2020
BACKGROUND: Machine learning (ML) allows the analysis of complex and large data sets and has the potential to improve health care. The clinical microbiology laboratory, at the interface of clinical practice and diagnostics, is of special interest for...
'Asthma' is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. Research to understand these phenotypes has previously been based on longitudinal wheeze patterns or hypothesis-driven observational criteria. The aim ...
Determining an optimal decision model is an important but difficult combinatorial task in imbalanced microarray-based cancer classification. Though the multiclass support vector machine (MCSVM) has already made an important contribution in this field...