BACKGROUND: Carbapenem-resistant Klebsiella pneumoniae (CRKP) is emerging as a significant pathogen causing healthcare-associated infections. Matrix-assisted laser desorption/ionisation mass spectrometry time-of-flight mass spectrometry (MALDI-TOF MS...
The service quality and system dependability of real-time communication networks strongly depends on the analysis of monitored data, to identify concrete problems and their causes. Many of these can be described by either their structural or temporal...
IEEE transactions on bio-medical engineering
Feb 5, 2020
OBJECTIVE: Elucidating the role of structural mechanisms in the knee can improve joint surgeries, rehabilitation, and understanding of biped locomotion. Identification of key features, however, is challenging due to limitations in simulation and in-v...
OBJECTIVES: To establish a quantitative MR model that uses clinically relevant features of tumor location and tumor volume to differentiate lower grade glioma (LRGG, grades II and III) and glioblastoma (GBM, grade IV).
OBJECTIVE: To develop a deep learning algorithm that can rule out significant rotator cuff tear based on conventional shoulder radiographs in patients suspected of rotator cuff tear.
Neocortical circuits exhibit a rich dynamic repertoire, and their ability to achieve entrainment (adjustment of their frequency to match the input frequency) is thought to support many cognitive functions and indicate functional flexibility. Although...
International journal of methods in psychiatric research
Feb 5, 2020
OBJECTIVE: Schizophrenia is a chronic and debilitating neuropsychiatric disorder. It has been suggested that impaired brain connectivity underlies the pathophysiology of schizophrenia. Network analysis has thus recently emerged in the field of schizo...
BACKGROUND: Several pro-oncogenic signals, including transforming growth factor beta (TGF-β) signalling from tumour microenvironment, generate intratumoural phenotypic heterogeneity and result in tumour progression and treatment failure. However, the...
IMPORTANCE: The ability to accurately predict in-hospital mortality for patients at the time of admission could improve clinical and operational decision-making and outcomes. Few of the machine learning models that have been developed to predict in-h...
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