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Full-Text Articles in Medicine and Health Sciences
Cancer Incidence And Stage At Diagnosis Among People With Psychotic Disorders: Systematic Review And Meta-Analysis., Jared C Wootten, Joshua C Wiener, Phillip S Blanchette, Kelly K. Anderson
Cancer Incidence And Stage At Diagnosis Among People With Psychotic Disorders: Systematic Review And Meta-Analysis., Jared C Wootten, Joshua C Wiener, Phillip S Blanchette, Kelly K. Anderson
Epidemiology and Biostatistics Publications
Research regarding the incidence of cancer among people with psychotic disorders relative to the general population is equivocal, although the evidence suggests that they have more advanced stage cancer at diagnosis. We conducted a systematic review and meta-analysis to examine the incidence and stage at diagnosis of cancer among people with, relative to those without, psychotic disorders. We searched the MEDLINE, EMBASE, PsycINFO, and CINAHL databases. Articles were included if they reported the incidence and/or stage at diagnosis of cancer in people with psychotic disorders. Random effects meta-analyses were used to determine risk of cancer and odds of advanced stage …
Cancer Incidence And Stage At Diagnosis Among People With Recent-Onset Psychotic Disorders: A Retrospective Cohort Study Using Health Administrative Data From Ontario, Canada., Jared C Wootten, Lucie Richard, Phillip S Blanchette, Joshua C. Wiener, Kelly K. Anderson
Cancer Incidence And Stage At Diagnosis Among People With Recent-Onset Psychotic Disorders: A Retrospective Cohort Study Using Health Administrative Data From Ontario, Canada., Jared C Wootten, Lucie Richard, Phillip S Blanchette, Joshua C. Wiener, Kelly K. Anderson
Epidemiology and Biostatistics Publications
OBJECTIVE: Prior evidence on the relative risk of cancer among people with psychotic disorders is equivocal. The objective of this study was to compare incidence and stage at diagnosis of cancer for people with psychotic disorders relative to the general population.
METHOD: We constructed a retrospective cohort of people with a first diagnosis of non-affective psychotic disorder and a comparison group from the general population using linked health administrative databases in Ontario, Canada. The cohort was followed for incident diagnoses of cancer over a 25-year period. We used Poisson and logistic regression models to compare cancer incidence and stage at …
Foundations Of Plasmas For Medical Applications, T. Von Woedtke, Mounir Laroussi, M. Gherardi
Foundations Of Plasmas For Medical Applications, T. Von Woedtke, Mounir Laroussi, M. Gherardi
Electrical & Computer Engineering Faculty Publications
Plasma medicine refers to the application of nonequilibrium plasmas at approximately body temperature, for therapeutic purposes. Nonequilibrium plasmas are weakly ionized gases which contain charged and neutral species and electric fields, and emit radiation, particularly in the visible and ultraviolet range. Medically-relevant cold atmospheric pressure plasma (CAP) sources and devices are usually dielectric barrier discharges and nonequilibrium atmospheric pressure plasma jets. Plasma diagnostic methods and modelling approaches are used to characterize the densities and fluxes of active plasma species and their interaction with surrounding matter. In addition to the direct application of plasma onto living tissue, the treatment of liquids …
A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun
A Machine Learning Framework For Identifying Molecular Biomarkers From Transcriptomic Cancer Data, Md Abdullah Al Mamun
FIU Electronic Theses and Dissertations
Cancer is a complex molecular process due to abnormal changes in the genome, such as mutation and copy number variation, and epigenetic aberrations such as dysregulations of long non-coding RNA (lncRNA). These abnormal changes are reflected in transcriptome by turning oncogenes on and tumor suppressor genes off, which are considered cancer biomarkers.
However, transcriptomic data is high dimensional, and finding the best subset of genes (features) related to causing cancer is computationally challenging and expensive. Thus, developing a feature selection framework to discover molecular biomarkers for cancer is critical.
Traditional approaches for biomarker discovery calculate the fold change for each …