Li Y, Wei Y, Li B, Alterovitz G.
Modified Anderson-Darling test-based target detector in non-homogenous environments. Sensors (Basel). 2014;14 (9) :16046-61.
Publisher's VersionAbstractA constant false alarm rate (CFAR) target detector in non-homogenous backgrounds is proposed. Based on K-sample Anderson-Darling (AD) tests, the method re-arranges the reference cells by merging homogenous sub-blocks surrounding the cell under test (CUT) into a new reference window to estimate the background statistics. Double partition test, clutter edge refinement and outlier elimination are used as an anti-clutter processor in the proposed Modified AD (MAD) detector. Simulation results show that the proposed MAD test based detector outperforms cell-averaging (CA) CFAR, greatest of (GO) CFAR, smallest of (SO) CFAR, order-statistic (OS) CFAR, variability index (VI) CFAR, and CUT inclusive (CI) CFAR in most non-homogenous situations.
Villa A, Zollanvari A, Alterovitz G, Cagetti MG, Strohmenger L, Abati S.
Prevalence of halitosis in children considering oral hygiene, gender and age. Int J Dent Hyg. 2014;12 (3) :208-12.
Publisher's VersionAbstractBACKGROUND: To date, few studies have addressed halitosis in the paediatric population. As such, the aim of the present study was to investigate symptoms, signs and risk factors associated with halitosis in healthy children and to present a model based on the clinical data that predicts the presence of halitosis. METHODS: A total of 101 individuals were included. All patients received a questionnaire that queried on sociodemographic characteristics, self-reported halitosis and dental treatment history. Individuals received a thorough intra-oral examination, and the volatile sulphur compounds (VSC) were measured to test the presence of halitosis with a portable sulphide monitor (Halimeter(®); Interscan Co., Chatsworth, CA, USA). The distribution of the sociodemographic characteristics, self-reported halitosis, dental treatment history and other oral features was evaluated. Finally, a statistical model was constructed with the best set of features to predict halitosis in children. RESULTS: The median age was 12.0 years (mean: 11.7 ± SD 2.7) with 54.5% males. Halitosis (VSC > 100 parts per billion, or ppb) was objectively measured in 37.6% of patients. For comparison purposes, Bayesian network was obtained using clinical and demographic data. The model consisted of four variables (sex, age, oral hygiene status and self-reported halitosis) directly related to the presence of halitosis (VSC > 100 ppb). This model achieved 76.4% area under receiver operating characteristics curve (AUROC). Overall, female patients or individuals with dental plaque on more than 25% of the dental surfaces or patients older than 13 year old were more prone to present with halitosis. CONCLUSIONS: The results suggest that halitosis in the paediatric population is related to poor oral hygiene and may be more common in females and older individuals. This specific predictive model may be useful to identify subgroups to target for intervention to treat oral halitosis.
Warner JL, Denny JC, Kreda DA, Alterovitz G.
Seeing the forest through the trees: uncovering phenomic complexity through interactive network visualization. J Am Med Inform Assoc. 2014.
Publisher's VersionAbstractOur aim was to uncover unrecognized phenomic relationships using force-based network visualization methods, based on observed electronic medical record data. A primary phenotype was defined from actual patient profiles in the Multiparameter Intelligent Monitoring in Intensive Care II database. Network visualizations depicting primary relationships were compared to those incorporating secondary adjacencies. Interactivity was enabled through a phenotype visualization software concept: the Phenomics Advisor. Subendocardial infarction with cardiac arrest was demonstrated as a sample phenotype; there were 332 primarily adjacent diagnoses, with 5423 relationships. Primary network visualization suggested a treatment-related complication phenotype and several rare diagnoses; re-clustering by secondary relationships revealed an emergent cluster of smokers with the metabolic syndrome. Network visualization reveals phenotypic patterns that may have remained occult in pairwise correlation analysis. Visualization of complex data, potentially offered as point-of-care tools on mobile devices, may allow clinicians and researchers to quickly generate hypotheses and gain deeper understanding of patient subpopulations.