2 research outputs found
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UAV based wilt detection system via convolutional neural networks
YesThe significant role of plants can be observed through the dependency of animals and humans on them. Oxygen, materials, food and the beauty of the world are contributed by plants. Climate change, the decrease in pollinators, and plant diseases are causing a significant decline in both quality and coverage ratio of the plants and crops on a global scale. In developed countries, above 80 percent of rural production is produced by sharecropping. However, due to widespread diseases in plants, yields are reported to have declined by more than a half. These diseases are identified and diagnosed by the agricultural and forestry department. Manual inspection on a large area of fields requires a huge amount of time and effort, thereby reduces the effectiveness significantly. To counter this problem, we propose an automatic disease detection and classification method in radish fields by using a camera attached to an unmanned aerial vehicle (UAV) to capture high quality images from the fields and analyze them by extracting both color and texture features, then we used K-means clustering to filter radish regions and feeds them into a fine-tuned GoogleNet to detect Fusarium wilt of radish efficiently at early stage and allow the authorities to take timely action which ensures the food safety for current and future generations.Supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries(IPET) through Agri-Bio Industry Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs(MAFRA) (316033-04-2-338 SB030)
Risk factors for and clinical outcomes of carbapenem non-susceptible gram negative bacilli bacteremia in patients with acute myelogenous leukemia
Background
Carbapenem is frequently used when gram negative bacilli (GNB) bacteremia is detected especially in neutropenic patients. Consequently, appropriate treatment could be delayed in GNB bacteremia cases involving organisms which are not susceptible to carbapenem (carba-NS), resulting in a poor clinical outcomes. Here, we explored risk factors for carba-NS GNB bacteremia and its clinical outcomes in patients with acute myelogenous leukemia (AML) that underwent chemotherapy.
Methods
We reviewed all GNB bacteremia cases that occurred during induction or consolidation chemotherapy, over a 15-year period, in a tertiary-care hospital.
Results
Among 489 GNB bacteremia cases from 324 patients, 45 (9.2%) were carba-NS and 444 (90.8%) were carbapenem susceptible GNB. Independent risk factors for carba-NS GNB bacteremia were: carbapenem use at bacteremia onset (adjusted odds ratio [aOR]: 91.2; 95% confidence interval [95%CI]: 29.3β284.1; Pβ<β0.001); isolation of carbapenem-resistant Acinetobacter baumannii (aOR: 19.4, 95%CI: 3.4β112.5; Pβ=β0.001) in the prior year; and days from chemotherapy to GNB bacteremia (aOR: 1.1 per day, 95%CI: 1.1β1.2; Pβ<β0.001). Carba-NS bacteremia was independently associated with in-hospital mortality (aOR: 6.6, 95%CI: 3.0β14.8; Pβ<β0.001).
Conslusion
Carba-NS organisms should be considered for antibiotic selection in AML patients having these risk factors