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Item Advances in Wireless Networks(Hindawi, 2009-04-13) Durresi, Arjan; Denko, Mieso; Computer and Information Science, School of ScienceItem AI on the Edge with CondenseNeXt: An Efficient Deep Neural Network for Devices with Constrained Computational Resources(2021-08) Kalgaonkar, Priyank B.; El-Sharkawy, Mohamed A.; King, Brian S.; Rizkalla, Maher E.Research work presented within this thesis propose a neoteric variant of deep convolutional neural network architecture, CondenseNeXt, designed specifically for ARM-based embedded computing platforms with constrained computational resources. CondenseNeXt is an improved version of CondenseNet, the baseline architecture whose roots can be traced back to ResNet. CondeseNeXt replaces group convolutions in CondenseNet with depthwise separable convolutions and introduces group-wise pruning, a model compression technique, to prune (remove) redundant and insignificant elements that either are irrelevant or do not affect performance of the network upon disposition. Cardinality, a new dimension to the existing spatial dimensions, and class-balanced focal loss function, a weighting factor inversely proportional to the number of samples, has been incorporated in order to relieve the harsh effects of pruning, into the design of CondenseNeXt’s algorithm. Furthermore, extensive analyses of this novel CNN architecture was performed on three benchmarking image datasets: CIFAR-10, CIFAR-100 and ImageNet by deploying the trained weight on to an ARM-based embedded computing platform: NXP BlueBox 2.0, for real-time image classification. The outputs are observed in real-time in RTMaps Remote Studio’s console to verify the correctness of classes being predicted. CondenseNeXt achieves state-of-the-art image classification performance on three benchmark datasets including CIFAR-10 (4.79% top-1 error), CIFAR-100 (21.98% top-1 error) and ImageNet (7.91% single model, single crop top-5 error), and up to 59.98% reduction in forward FLOPs compared to CondenseNet. CondenseNeXt can also achieve a final trained model size of 2.9 MB, however at the cost of 2.26% in accuracy loss. Thus, performing image classification on ARM-Based computing platforms without requiring a CUDA enabled GPU support, with outstanding efficiency.Item Association Between Intrauterine Device Type and Risk of Perforation and Device Expulsion: Results From the APEX-IUD Study(ScienceDirect, 2022) Gatz, Jennifer L.; Armstrong, Mary Anne; Postlethwaite, Debbie; Raine-Bennett, Tina; Chillemi, Giulia; Alabaster, Amy; Merchant, Maqdooda; Reed, Susan D.; Ichikawa, Laura; Getahun, Darios; Fassett, Michael J.; Shi, Jiaxiao M.; Xie, Fagen; Chiu, Vicki Y.; Im, Theresa M.; Takhar, Harpreet S.; Wang, Jinyi; Saltus, Catherine W.; Ritchey, Mary E.; Asiimwe, Alex; Pisa, Federica; Schoendorf, Juliane; Wahdan, Yesmean; Zhou, Xiaolei; Hunter, Shannon; Anthony, Mary S.; Peipert, Jeffrey F.; Medicine, School of MedicineBackground Intrauterine devices, including levonorgestrel-releasing and copper devices, are highly effective long-acting reversible contraceptives. The potential risks associated with intrauterine devices are low and include uterine perforation and device expulsion. Objective This study aimed to evaluate the risk of perforation and expulsion associated with levonorgestrel-releasing devices vs copper devices in clinical practice in the United States. Study Design The Association of Perforation and Expulsion of Intrauterine Devices study was a retrospective cohort study of women aged ≤50 years with an intrauterine device insertion during 2001 to 2018 and information on intrauterine device type and patient and medical characteristics. Of note, 4 research sites with access to electronic health records contributed data for the study: 3 Kaiser Permanente–integrated healthcare systems (Northern California, Southern California, and Washington) and 1 healthcare system using data from a healthcare information exchange in Indiana (Regenstrief Institute). Perforation was classified as any extension of the device into or through the myometrium. Expulsion was classified as complete (not visible in the uterus or abdomen or patient reported) or partial (any portion in the cervix or malpositioned). We estimated the crude incidence rates and crude cumulative incidence by intrauterine device type. The risks of perforation and expulsion associated with levonorgestrel-releasing intrauterine devices vs copper intrauterine devices were estimated using Cox proportional-hazards regression with propensity score overlap weighting to adjust for confounders. Results Among 322,898 women included in this analysis, the incidence rates of perforation per 1000 person-years were 1.64 (95% confidence interval, 1.53–1.76) for levonorgestrel-releasing intrauterine devices and 1.27 (95% confidence interval, 1.08–1.48) for copper intrauterine devices; 1-year and 5-year crude cumulative incidence was 0.22% (95% confidence interval, 0.20–0.24) and 0.63% (95% confidence interval, 0.57–0.68) for levonorgestrel-releasing intrauterine devices and 0.16% (95% confidence interval, 0.13–0.20) and 0.55% (95% confidence interval, 0.44–0.68) for copper intrauterine devices, respectively. The incidence rates of expulsion per 1000 person-years were 13.95 (95% confidence interval, 13.63–14.28) for levonorgestrel-releasing intrauterine devices and 14.08 (95% confidence interval, 13.44–14.75) for copper intrauterine devices; 1-year and 5-year crude cumulative incidence was 2.30% (95% confidence interval, 2.24–2.36) and 4.52% (95% confidence interval, 4.40–4.65) for levonorgestrel-releasing intrauterine devices and 2.30% (95% confidence interval, 2.18–2.44) and 4.82 (95% confidence interval, 4.56–5.10) for copper intrauterine devices, respectively. Comparing levonorgestrel-releasing intrauterine devices with copper intrauterine devices, the adjusted hazard ratios were 1.49 (95% confidence intervals, 1.25–1.78) for perforation and 0.69 (95% confidence intervals, 0.65–0.73) for expulsion. Conclusion After adjusting for potential confounders, levonorgestrel-releasing intrauterine devices were associated with an increased risk of uterine perforation and a decreased risk of expulsion relative to copper intrauterine devices. Given that the absolute numbers of these events are low in both groups, these differences may not be clinically meaningful.Item Association Between Menorrhagia and Risk of Intrauterine Device-Related Uterine Perforation and Device Expulsion: Results from the APEX-IUD Study(ScienceDirect, 2022) Getahun, Darios; Fassett, Michael J.; Gatz, Jennifer; Armstrong, Mary Anne; Peipert, Jeffrey F.; Raine-Bennett, Tina; Reed, Susan D.; Zhou, Xiaolei; Schoendorf, Juliane; Postlethwaite, Debbie; Shi, Jiaxiao M.; Saltus, Catherine W.; Wang, Jinyi; Xie, Fagen; Chiu, Vicki Y.; Merchant, Maqdooda; Alabaster, Amy; Ichikawa, Laura E.; Hunter, Shannon; Im, Theresa M.; Takhar, Harpreet S.; Ritchey, Mary E.; Chillemi, Giulia; Pisa, Federica; Asiimwe, Alex; Anthony, Mary S.; Regenstrief Institute, School of MedicineBackground Intrauterine devices are effective contraception, and one levonorgestrel-releasing device is also indicated for treatment of heavy menstrual bleeding (menorrhagia). Objective To compare the incidence of intrauterine device expulsion and uterine perforation in women with and without a diagnosis of menorrhagia within the 12 months before device insertion. Study Design Retrospective cohort study conducted in 3 integrated healthcare systems (Kaiser Permanente Northern California, Southern California, and Washington) and a healthcare information exchange (Regenstrief Institute) in the United States, using electronic health records. Nonpostpartum women aged ≤50 years with intrauterine device (e.g., levonorgestrel or copper) insertions from 2001–2018 without a delivery in the prior 12 months were studied in this analysis. Recent menorrhagia diagnosis (i.e., recorded ≤12 months before insertion) was ascertained from International Classification of Diseases, Ninth/Tenth Revision, Clinical Modification codes. Study outcomes—device expulsion and device-related uterine perforation (complete or partial)—were ascertained from electronic medical records and validated in data sources. Cumulative incidence and crude incidence rates with 95% confidence intervals were estimated. Cox proportional hazards models estimated crude and adjusted hazard ratios using propensity score overlap weighting (13-16 variables) and 95% confidence intervals. Results Among 228,834 nonpostpartum women, mean age was 33.1 years, 44.4% were White, and 31,600 (13.8%) had a recent menorrhagia diagnosis. Most women had a levonorgestrel-releasing device (96.4% of those with and 78.2% of those without a menorrhagia diagnosis). Women with a menorrhagia diagnosis were likely to be older, obese, and have dysmenorrhea or fibroids. Women with vs. without a menorrhagia diagnosis had a higher intrauterine device expulsion rate (40.01 vs. 10.92 per 1,000 person-years), especially evident in the few months after insertion. Women with a menorrhagia diagnosis had higher cumulative incidence (95% confidence interval) of expulsion (7.00% [6.70%, 7.32%] at 1 year, 12.03% [11.52%, 12.55%] at 5 years) vs. without (1.77% [1.70%, 1.84%] at 1 year, 3.69% [3.56%, 3.83%] at 5 years). Risk of expulsion was increased for women with a menorrhagia diagnosis vs. without (adjusted hazard ratio, 2.84 [95% confidence interval: 2.66, 3.03]). Perforation rate was low overall (<1/1,000 person-years) but higher in women with a diagnosis of menorrhagia vs. without (0.98 vs. 0.63 per 1,000 person-years). Cumulative incidence (95% confidence interval) of uterine perforation was slightly higher for women with a menorrhagia diagnosis (0.09% [0.06%, 0.14%] at 1 year, 0.39% [0.29%, 0.53%] at 5 years) vs. without (0.07% [0.06%, 0.08%], at 1 year, 0.28% [0.24%, 0.33%] at 5 years). Risk of perforation was slightly increased in women with a menorrhagia diagnosis vs. without (adjusted hazard ratio, 1.53; 95% confidence interval, 1.10, 2.13). Conclusion The risk of expulsion is significantly higher in women with a recent diagnosis of menorrhagia. Patient education and counseling regarding potential expulsion risk is recommended at insertion. The absolute risk of perforation for women with a recent diagnosis of menorrhagia is very low. Increased expulsion and perforation rates observed are likely due to causal factors of menorrhagia.Item Implementation of an evidence-based seizure algorithm in intellectual disability nursing: A pilot study(2016) Auberry, Kathy; Cullen, DeborahBased on the results of the Surrogate Decision-Making Self Efficacy Scale (Lopez, 2009), this study sought to determine if nurses working in the field of intellectual disability experience increased confidence when they implemented the “American Association of Neuroscience Nurses Seizure Algorithm” during telephone triage. The results of the study indicated using the AANN Seizure Algorithm increased self-confidence for many of the nurses in guiding care decisions during telephone triage. The treatment effect was statistically significant -3.169, p, .01 for a small sample of study participants. This increase in confidence is clinically essential for two reasons. Many individuals with intellectual disability and epilepsy reside within community based settings. Intellectual disability nurses provide seizure guidance to this population living in community based settings via telephone triage. Nurses improved confidence is clinically essential and has implications for practice. Evidenced-based training tools provide a valuable mechanism by guiding nurses via best practices. Nurses may need to be formally trained for seizure management due to high epilepsy rates in this population.Item The Longest Common Exemplar Subsequence Problem(IEEE, 2018-12) Zhang, Shu; Wang, Ruizhi; Zhu, Daming; Jiang, Haitao; Feng, Haodi; Guo, Jiong; Liu, Xiaowen; BioHealth Informatics, School of Informatics and ComputingIn this paper, we propose to find order conserved subsequences of genomes by finding longest common exemplar subsequences of the genomes. The longest common exemplar subsequence problem is given by two genomes, asks to find a common exemplar subsequence of them, such that the exemplar subsequence length is maximized. We focus on genomes whose genes of the same gene family are in at most s spans. We propose a dynamic programming algorithm with time complexity O(s4 s mn) to find a longest common exemplar subsequence of two genomes with one genome admitting s span genes of the same gene family, where m, n stand for the gene numbers of those two given genomes. Our algorithm can be extended to find longest common exemplar subsequences of more than one genomes.