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“…ABSTRACT: State-of-the-art artificial intelligence (AI) has recently gained considerable interest in the healthcare sector and has provided solutions to problems through automated diagnosis. …”
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“…The results of this study show that the proposed strategy for designing flame-retardant properties represents the state-of-the-art, competent coating of inorganic materials for the protection and functionalization of wood substrates.…”
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“…The experimental results show that the proposed Connected-SegNets model outperforms the state-of-the-art methods in terms of Dice score and IoU score. …”
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“…The proportion of identical viral isolates correlated with the duration of treatment (r = 0.822, P = 0.0190), suggesting progressive clonal expansion of infected cells during ART. A broader range of infectivity was also observed among isolates from patients with delayed viremia control (r = 0.79, P = 0.025). …”
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“…Here, we synthesize the current state of the art in our understanding of human risk alleles in two prototypical autoimmune diseases – systemic lupus erythematosus (SLE) and type 1 diabetes (T1D) along with spontaneous murine disease models. …”
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“…The device from TTFA exhibits almost comparable efficiency to that of PEAI and PI controls, indicating that TTFA has an equal excellent passivation effect to state-of-the-art PEAI and PI. Furthermore, the devices based on BPY, DQCN, and TTFA show superior long-term stability with an efficiency loss of only 13.2, 16.7, and 12.9%, respectively, after being stored for 40 days in a ∼12% humidity, low-oxygen level environment, which is 45.4, 38.8, and 44.4% for the control, PEAI, and PI devices, respectively, primarily due to the improved hydrophobicity of the perovskite surface. …”
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“…We have collected PE from 97 patients to explore PE proteomes by applying state-of-the-art liquid chromatography-mass spectrometry (LC-MS) to identify potential biomarkers that correlate with immunohistochemistry assessment of tumor biopsy or with survival data. …”
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“…The performance of the optimized brain tumor segmentation algorithm was then compared to the results of several state-of-the-art techniques. The results obtained, by using the Dice coefficient, Jaccard distance, correlation coefficient, and root mean square error (RMSE) measurements, demonstrated the superiority of the proposed optimized segmentation algorithm over equivalent techniques.…”
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“…Furthermore, the proposed method significantly outperformed the three state-of-the-art baseline models, including U-Net, SegNet, and FCN, in terms of precision, sensitivity, DSC, and Jaccard index, based on Fisher’s least significant difference (LSD) test ([Formula: see text]). …”
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“…Odds of retention were significantly higher for patients at WHO clinical stage 1 compared to stage 4 (adjusted odds ratio (AOR), 1.325; confidence interval (CI), 1.13–1.55), women as opposed to men (AOR, 2.00; CI, 1.63–2.44), and women who were not pregnant (vs. pregnant women) at the start of antiretroviral therapy (ART) (AOR, 2.80; CI, 2.04–3.85). Odds of retention were significantly lower for patients who received a one-month supply rather than multiple months (AOR, 0.22; CI, 0.20–0.23), and for patients in urban health zones (AOR, 0.75; CI, 0.59–0.94) rather than rural. …”
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“…By using an independent test set, SYNPRED exhibits state-of-the-art performance metrics either in the classification (accuracy, 0.85; precision, 0.91; recall, 0.90; area under the receiver operating characteristic, 0.80; and F1-score, 0.91) or in the regression models, mainly when using the Combination Sensitivity Score synergy reference model (root mean square error, 11.07; mean squared error, 122.61; Pearson, 0.86; mean absolute error, 7.43; Spearman, 0.87). …”
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“…The experiments on the public BRACS dataset and a private clinical dataset have shown that our model achieves better segmentation performance, compared to the state-of-art models of U-Net, DoubleU-Net, ResUnet++, HRNet, and DeepLabV3+. …”
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“…RESULTS: In the detection of GA presence or absence, Med-XAI-Net obtained superior performance (91.5%, 93.5%, 82.3%, 82.8%, and 94.6% on accuracy, area under the ROC curve, F(1) score, sensitivity, and specificity, respectively) to that of 2 other state-of-the-art deep learning methods. The performance of ophthalmologists grading only the 5 B-scans selected by Med-XAI-Net as most relevant (95.7%, 95.4%, 91.2%, and 100%, respectively) was almost identical to that of ophthalmologists grading all volume scans (96.0%, 95.7%, 91.8%, and 100%, respectively). …”
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“…We therefore aim to conduct such a study and determine whether PACK-CXL is a viable alternative to conventional state-of-the-art medical therapy for corneal ulcer treatment in dogs. …”
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