4/18/2023 0 Comments Hidata disease![]() ![]() Novacek G, Miehsler W, Wrba F, Ferenci P, Penner E, Vogelsang H (1999) Prevalence and clinical importance of hypertransaminaseaemia in celiac disease. Meloni GF, Tomasi PA, Bertoncelli A, Fanciulli G, Delitala G, Meloni T (2001) Prevalence of silent celiac disease in patients with autoimmune thyroiditis from Northern Sardinia. A molecular and immunobiologic approach to the spectrum o gluten sensitivity('celiac sprue'). Marsh M (1002) Gluten, major histocompatibility complex and the small intestine. J Pediatr Gastroenterol Nutr 19: 691-696. Maggiore G, Ceccarelli M, Colombo Giacomo C De, Virgilis S De, Musumeci S, Ventura A (1994) 141 Hepatic lesions in childhood celiac disease: a multicentric retrospective study. Ludvigsson JF, Elfstrom P, Broome U, Ekbom A, Montgomery SM (2007) Celiac disease and risk of liver disease: a general population-based study. Lindberg T, Berg NO, Borulf S, Jacobson I (1978) Liver damage in coeliac disease or other food intolerance in childhood. Lazar L, Kalter-Leibovici O, Pertzelan A, Weintrob N, Josefsberg Z, Phillip M (2000) Thyrotoxicosis in prepubertal children compared to with pubertal and postpubertal patients, J Clin Endocrinol Metab 85: 3678-3682. ![]() Kim HJ, Kim BH, Han YS, Yang I, Kim KJ, Dong SH, Kim HJ, Chang YW, Lee JI, Chang R (2001) The incidence and clinical characteristics of symptomatic propylthiouracyl-induced hepatic injury in patients with hyperthyroidism: a single-center retrospective study. Jacobson DL, Gange SJ, Rose NR, Graham NM (1997) Epidemiology and estimated population burden of selected autoimmune diseases in the United States. World J Gastroenterol 12: 1503-1508.įrejman HJ, Kwan WC (1994) Occult celiac disease associated with lymphocytic sclerosing cholangitis. Dig Liver Dis 40: 965.įreeman HJ (2006) Hepatobiliary and pancreatic disorders in celiac disease. Arch Dis Child 87: 293-296.ĭiamanti A, Basso MS, Pietrobattista A, Nobili V (2008) Prevalence of celiac disease in children with autoimmune hepatitis. Intern Med 42: 331-333.ĭavison S (2002) Coeliac disease and liver dysfunction. Am J Surg Pathol 19: 1409-1417.Ĭui B, Abe M, Hidata S, Nakanishi S, Matsuura B, Michitaka K, Yamamoto K, Horiike N, Onji M (2003) Autoimmune hepatitis associated with Graves' disease. Hepatology 29: 654-657.īatts KP, Ludwig J (1995) Chronic Hepatitis. The approach could also be employed for mapping and monitoring other forest disturbance issues.Bardella MT, Vecchi M, Conte D, Del Ninno E, Fraquelli M, Pacchetti S, Minola E, Landoni M, Cesana BM, De Franchis R (1999) Chronic unexplained hypertransaminasemia may be caused by the occult celiac disease. Therefore, we proposed a new approach combining the merits of HI and LiDAR data to precisely predict PWD infection stages at the tree level, allowing better PWD monitoring and control. We obtained the following results: (1) The classification accuracies of HI (OA: 66.86%, Kappa: 0.57) were higher than those of LiDAR (OA: 45.56%, Kappa: 0.27) for predicting PWD infection stages, and their combination had the best accuracies (OA: 73.96%, Kappa: 0.66) (2) LiDAR data had higher ability for dead tree identification than HI data and (3) The combined use of HI and LiDAR data for estimation of PWD infection stages showed that LiDAR metrics (e.g., crown volume) were essential in the classification model, although the variables derived from HI data contributed more than those extracted from LiDAR. We estimated the power of the hyperspectral method (HI data only), LiDAR (LiDAR data only), and their combination (HI plus LiDAR data) to predict the infection stages of PWD using the random forest (RF) algorithm. In this paper, PWD infection was divided into five stages (green, early, middle, heavy, and grey), and HI and LiDAR data were integrated to detect PWD. However, few previous studies have used airborne HI and LiDAR to detect PWD and compared the capability for predicting PWD infection stage at the tree level. Unmanned aerial vehicle (UAV)-based hyperspectral imaging (HI) and light detection and ranging (LiDAR) technique is an effective approach for forest health monitoring. Therefore, the establishment of an effective method to accurately monitor and map the infection stage by PWD is imperative. Pine wilt disease (PWD) is a global destructive threat to forests, having caused extreme damage in China.
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