Introduction: The aim of this study was to apply Bayesian networks to evaluate the relative role and possible causal relationships among various factors affecting the diagnosis and final treatment outcome of impacted maxillary canines.
Methods: A total of 168 patients with infraosseous impacted maxillary canines had a combined surgical-orthodontic approach aimed to guide the impacted tooth to the center of the alveolar ridge. Demographic, orthodontic, and periodontal variables were recorded and analyzed by means of Bayesian network analysis.
Results: All 168 impacted canines were successfully moved and aligned in the dental arches with healthy periodontiums. According to the Bayesian network analysis, bilateral impaction was associated with palatal impaction and longer treatment; the pretreatment alpha-angle was a determinant for the duration of orthodontic traction, also because of the associations between greater angulation of impacted canines with more severe tooth displacement and with greater distance of the impacted canine from the occlusal plane; the posttreatment periodontal outcome was not related to the pretreatment radiographic variables.
Conclusions: Bayesian network analysis was useful to identify possible relationships among the variables considered for diagnosis and treatment of impacted canines.
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http://dx.doi.org/10.1016/j.ajodo.2008.08.028 | DOI Listing |
Wearable Technol
November 2024
Embedded Systems and Robotics Lab, Tezpur University, Tezpur, Assam, India.
Electromyogram (EMG) has been a fundamental approach for prosthetic hand control. However it is limited by the functionality of residual muscles and muscle fatigue. Currently, exploring temporal shifts in brain networks and accurately classifying noninvasive electroencephalogram (EEG) for prosthetic hand control remains challenging.
View Article and Find Full Text PDFPharmacoepidemiol Drug Saf
January 2025
School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada.
Introduction: Masking is a reporting bias where drug safety signals are muffled by elevated reporting of other medications in spontaneous reporting databases. While the impact of masking is often limited, its effect when using restricted designs, such as active comparators, can be consequential.
Methods: We used data from the US Food and Drugs Administration Adverse Event Reporting System (1999Q3-2013Q3) to study masking in a real-world example.
Nat Commun
January 2025
Rudolf Peierls Centre for Theoretical Physics, University of Oxford, Oxford, UK.
The remarkable performance of overparameterized deep neural networks (DNNs) must arise from an interplay between network architecture, training algorithms, and structure in the data. To disentangle these three components for supervised learning, we apply a Bayesian picture based on the functions expressed by a DNN. The prior over functions is determined by the network architecture, which we vary by exploiting a transition between ordered and chaotic regimes.
View Article and Find Full Text PDFEBioMedicine
January 2025
MGH Biostatistics Center, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA. Electronic address:
Background: The ovarian cancer (OC) preclinical detectable phase (PCDP), defined as the interval during which cancer is detectable prior to clinical diagnosis, remains poorly characterised. We report exploratory analyses from the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).
Methods: In UKCTOCS between Apr-2001 and Sep-2005, 101,314 postmenopausal women were randomised to no screening (NS) and 50,625 to annual multimodal screening (MMS) (until Dec-2011) using serum CA-125 interpreted by the Risk of Ovarian Cancer Algorithm (ROCA).
Psychiatr Q
January 2025
Educational psychology, The Hashemite University, Queen Rania Faculty for Childhood, Early Childhood Department, Zarqa, Jordan.
The current paper aimed to estimate the network structure of general psychopathology (internalizing and externalizing symptoms/disorders) among 239 gifted children in Jordan. This cross-sectional study with a convenience sampling method was conducted between September 2023 and October 2024 among gifted children aged 7-12. The Child Behavior Checklist (CBCL) was employed to assess six symptom clusters: conduct problems, attention-deficit/hyperactivity disorder (ADHD), and oppositional defiant problems as externalizing symptoms, and affective problems, anxiety issues, and somatic complaints as internalizing symptoms.
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