RESUMEN
Because it is an accessible and routine image test, medical personnel commonly use a chest X-ray for COVID-19 infections. Artificial intelligence (AI) is now widely applied to improve the precision of routine image tests. Hence, we investigated the clinical merit of the chest X-ray to detect COVID-19 when assisted by AI. We used PubMed, Cochrane Library, MedRxiv, ArXiv, and Embase to search for relevant research published between 1 January 2020 and 30 May 2022. We collected essays that dissected AI-based measures used for patients diagnosed with COVID-19 and excluded research lacking measurements using relevant parameters (i.e., sensitivity, specificity, and area under curve). Two independent researchers summarized the information, and discords were eliminated by consensus. A random effects model was used to calculate the pooled sensitivities and specificities. The sensitivity of the included research studies was enhanced by eliminating research with possible heterogeneity. A summary receiver operating characteristic curve (SROC) was generated to investigate the diagnostic value for detecting COVID-19 patients. Nine studies were recruited in this analysis, including 39,603 subjects. The pooled sensitivity and specificity were estimated as 0.9472 (p = 0.0338, 95% CI 0.9009-0.9959) and 0.9610 (p < 0.0001, 95% CI 0.9428-0.9795), respectively. The area under the SROC was 0.98 (95% CI 0.94-1.00). The heterogeneity of diagnostic odds ratio was presented in the recruited studies (I2 = 36.212, p = 0.129). The AI-assisted chest X-ray scan for COVID-19 detection offered excellent diagnostic potential and broader application.
RESUMEN
OBJECTIVE: Wheat bran (WB) was co-fermented with Aspergillus oryzae and phytase (Phy) to determine whether co-fermentation improve WB phosphorus and fiber utilization in Isa-brown layers. METHODS: A total of 112 Isa brown layer were randomly divided into 7 treatments with 8 replicates per a treatment and 2 hens per a replicate. The treatments included basal diet (control), basal diet supplemented with 250 unit/kg Phy (control+Phy), diet with 10% WB (10% WB), diet with 5% WB and 250 unit/kg Phy (5% WB+Phy) diet with 10% WB and 250 unit/kg Phy (10% WB+Phy), diet with 5% fermented WB supplemented with molasses and phy (PCFWH) and 125 unit/kg Phy (5% PCFWH), and diet with 10% PCFWH (10% PCFWH). The intestinal microbial population, intestinal morphology, serum antioxidant enzyme activities, and excreta phosphorus content were assessed. RESULTS: In PCFWH, spore counts, protease activity, xylanase activity, and ferulic acid were 8.50 log/g dry matter (DM), 190 unit/g DM, 120 unit/g DM, and 127 µg/g, respectively. Xylobiose and xylotriose were released in PCFWH, while they were not detectable in WB. Antioxidant capacity was also enhanced in PCFWH compared to WB. The 10% WB+Phy and 10% PCFWH groups produced higher egg mass, but hens fed 5% WB+Phy had the lowest amount of feed intake. Eggs from 10% PCFWH had better eggshell weight, eggshell strength, and eggshell thickness. Birds fed with 10% PCFWH also had higher serum superoxide dismutase and catalase activities. Compare to control, 10% PCFWH significantly reduced excreta phosphorus content. CONCLUSION: Diet inclusion of 10% PCFWH improved egg quality, antioxidant status, and excreta phosphorus content of laying hens.