This website requires JavaScript.
DOI: 10.1101/2023.05.21.541619

Machine-learning guided Venom Induced Dermonecrosis Analysis tooL: VIDAL

W. M.Laprade K. E. Bartlett C. R. Christensen ...+11 T. P. Jenkins
摘要
Snakebite envenoming is a global public health issue that causes significant morbidity and mortality, particularly in low-income regions of the world. The clinical manifestations of envenomings vary depending on the snake's venom, with paralysis, haemorrhage, and necrosis being the most common and medically relevant effects. To assess the efficacy of antivenoms against dermonecrosis, a preclinical testing approach involves in vivo mouse models that mimic local tissue effects of cytotoxic snakebites in humans. However, current methods for assessing necrosis severity are time-consuming and susceptible to human error. To address this, we present the Venom Induced Dermonecrosis Analysis tool (VIDAL), a machine-learning-guided image-based solution that can automatically identify dermonecrotic lesions in mice, adjust for lighting biases, scale the image, extract lesion area and discolouration, and calculate the severity of dermonecrosis. We also introduce a new unit, the dermonecrotic unit (DnU), to better capture the complexity of dermonecrosis severity. Our tool is comparable to the performance of state-of-the-art histopathological analysis, making it an accessible, accurate, and reproducible method for assessing dermonecrosis. Given the urgent need to address the neglected tropical disease that is snakebite, high-throughput technologies such as VIDAL are crucial in developing and validating new and existing therapeutics for this debilitating disease.
展开全部
图表提取

暂无人提供速读十问回答

论文十问由沈向洋博士提出，鼓励大家带着这十个问题去阅读论文，用有用的信息构建认知模型。写出自己的十问回答，还有机会在当前页面展示哦。

Q1论文试图解决什么问题？
Q2这是否是一个新的问题？
Q3这篇文章要验证一个什么科学假设？
0
被引用
0
笔记
0
问答
领域
· Computer Science· CV