Classification of lung diseases using deep learning models

Although deep learning-based models show high performance in the medical field, they required large volumes of data which is problematic due to the protection of patient privacy and lack of publically available medical databases. In this thesis, we address the problem of medical data scarcity by considering the task of pulmonary disease detection in chest X-Ray images using small volume datasets (<1000 samples). We implement three deep convolution neural networks pre-trained on the ImageNet dataset (VGG16, ResNet-50, and InveptionV3) and asses them in the lung disease classification tasks transfer learning approach. We created a pipeline that applied segmentation on Chest X-Ray images before classifying them and we compared the performance of our framework with the existing one. We demonstrated that pre-trained models and simple classifiers such as shallow neural networks can compete with the complex systems. We also implemented activation maps for our system. The analysis of class activation maps shows that not only does the segmentation improve results in terms of accuracy but also focuses models on medically relevant areas of lungs. We validated our techniques on the publicly available Shenzhen and Montgomery datasets and compared them to the currently available solutions. Our method was able to reach the same level of accuracy as the best performing models trained on the Montgomery dataset however, the advantage of our approach is a smaller number of trainable parameters. What is more, our InceptionV3 based model almost tied with the best performing solution on the Shenzhen dataset but as previously, it is computationally less expensive

Evaluation of over the counter medication knowledge and literacy in middle school and high school students

Over the counter (OTC) medications are commonly utilized by the public, including adolescents, to self-treat many conditions. Unfortunately, these products can be dangerous if not used safely and appropriately. Adolescents between 13 and 19 years old composed 7.32 percent of the human exposure cases reported to U.S. poison control centers in 2014. Among these cases, there were 53 fatalities involving pharmaceuticals. This is an age range where medication use becomes more independent and the education they receive throughout the school curriculum is unknown. This study was designed to evaluate OTC medication knowledge and literacy among middle and high school students

Controlled-Depth Laser Cutting of Aluminum Sheet for Laminated Object Manufacturing

Replacing paper with metal in laminated object manufacturing would bring improvements in terms of part's longevity, and its mechanical and thermal properties. In fabricating laminated parts, a challenging step is blind cutting of the metal sheet. Challenges to overcome are (1) maintaining consistent depth of cut, (2) achieving good surface quality of the cut groove walls, and (3) minimizing the formation of recast. Results are presented of an experimental investigation into controlled-depth laser cutting of aluminum sheet. Thin (0.12-mm) aluminum sheet specimens were cut with a 10-W Nd:YLF laser while varying scan speed and laser power. To accurately observe the cut profiles, specimens were mounted in resin and sectioned. Special handling procedure was developed to handle thin sheet material while avoiding damage. Relationship between cut profile and process parameters was established and shown to conform to established theoretical models.We gratefully acknowledge the financial support of Centre for Automotive Materials and Manufacturing and Canada Foundation for Innovation.Mechanical Engineerin

Non-linear Real Arithmetic Benchmarks derived from Automated Reasoning in Economics

We consider problems originating in economics that may be solved automatically using mathematical software. We present and make freely available a new benchmark set of such problems. The problems have been shown to fall within the framework of non-linear real arithmetic, and so are in theory soluble via Quantifier Elimination (QE) technology as usually implemented in computer algebra systems. Further, they all can be phrased in prenex normal form with only existential quantifiers and so are also admissible to those Satisfiability Module Theory (SMT) solvers that support the QF_NRA. There is a great body of work considering QE and SMT application in science and engineering, but we demonstrate here that there is potential for this technology also in the social sciences.Comment: To appear in Proc. SC-Square 2018. Dataset described is hosted by Zenodo at: https://doi.org/10.5281/zenodo.1226892 . arXiv admin note: substantial text overlap with arXiv:1804.1003

Exercise-Induced Interleukin-6 and Metabolic Responses in Hot, Temperate, and Cold Conditions

The purpose of this study was to determine the effects of exercise in hot, cold, and temperate environments on plasma interleukin-6 (IL-6). Eleven recreationally trained males (age = 25 ± 4 years, height = 178 ± 5 cm, weight = 79.4 ± 13.5 kg, body fat = 14.7 ± 3.6%, VO2 peak = 54.6 ± 11.5 ml kg-1 min-1) performed a 1 hr cycling bout in hot (33 °C), cold (7 °C), and temperate (20 °C) environments at 60% of Wmax followed by 3 hr of supine recovery in temperate conditions. Expired gases were measured every 15 min during exercise and once every hour during recovery. Heart rate was continuously measured throughout the trials. Blood samples were obtained from the antecubital vein pre-exercise, immediately post-exercise, and 3 hr post-exercise. Blood samples were analyzed for plasma concentrations of IL-6 using a commercial ELISA kit. Plasma IL-6 concentrations were significantly higher immediately post-exercise (14.8 ± 1.6 pg ml-1, p = 0.008) and 3 hr post-exercise (14.8 ± 0.9 pg ml-1, p = 0.018) compared to pre-exercise (11.4 ± 2.4 pg ml-1), across all trials. There were no differences in plasma IL-6 concentrations (p = 0.207) between temperature conditions.Oxygen consumption and heart rate were higher and respiratory exchange ratio was lower in the hot compared to other conditions (p \u3c 0.05). These data indicate that the temperature in which exercise occurs does not affect acute plasma IL-6 response despite differences in metabolic state

Microbial Cycling of C and N in Northern Hardwood Forests Receiving Chronic Atmospheric NO 3 − Deposition

Sugar maple ( Acer saccharum Marsh.)-dominated northern hardwood forests in the upper Lakes States region appear to be particularly sensitive to chronic atmospheric NO 3 − deposition. Experimental NO 3 − deposition (3 g NO 3 − N m −2 y −1 ) has significantly reduced soil respiration and increased the export of DOC/DON and NO 3 − across the region. Here, we evaluate the possibility that diminished microbial activity in mineral soil was responsible for these ecosystem-level responses to NO 3 − deposition. To test this alternative, we measured microbial biomass, respiration, and N transformations in the mineral soil of four northern hardwood stands that have received 9 years of experimental NO 3 − deposition. Microbial biomass, microbial respiration, and daily rates of gross and net N transformations were not changed by NO 3 − deposition. We also observed no effect of NO 3 − deposition on annual rates of net N mineralization. However, NO 3 − deposition significantly increased (27%) annual net nitrification, a response that resulted from rapid microbial NO 3 − assimilation, the subsequent turnover of NH 4 + , and increased substrate availability for this process. Nonetheless, greater rates of net nitrification were insufficient to produce the 10-fold observed increase in NO 3 − export, suggesting that much of the exported NO 3 − resulted directly from the NO 3 − deposition treatment. Results suggest that declines in soil respiration and increases in DOC/DON export cannot be attributed to NO 3 − -induced physiological changes in mineral soil microbial activity. Given the lack of response we have observed in mineral soil, our results point to the potential importance of microbial communities in forest floor, including both saprotrophs and mycorrhizae, in mediating ecosystem-level responses to chronic NO 3 − deposition in Lake States northern hardwood forests.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41375/1/10021_2005_Article_85.pd