Digestive Department, the First Affiliated Hospital of Jiamusi University, Jiamusi 154000, Heilongjiang, China.
Department of Neurology, the First Affiliated Hospital of Jiamusi University, Jiamusi 154000, Heilongjiang, China.
J Healthc Eng. 2022 Mar 17;2022:2203737. doi: 10.1155/2022/2203737. eCollection 2022.
Neurons refer to nerve cells. Each neuron is connected with thousands of other neurons to form a corresponding functional area and carry out complex communication with other functional areas. Its importance to the human body is self-evident. There are also many scholars studying the mechanism of apoptosis. This paper proposes a study of neuronal apoptosis in patients with liver cirrhosis and neuronal epileptiform discharge models based on multi-modal fusion deep learning, aiming to study the influencing factors of abnormal neuronal discharge in the brain. The method in this paper is to study multi-modal information fusion methods, perform Bayesian inference, and analyze multi-modal medical data. The function of these research methods is to obtain the relationship between the independence of information and the intersection of information among modalities. In the neuronal epileptiform discharge model, the mRNA expression level of the necroptotic signaling pathway related protein was detected, and the mechanism of neuronal necrosis in patients with liver cirrhosis was explored. Experiments show that the neuron recognition rate has been increased from 67.2% to 84.5%, and the time has been reduced, proving the effectiveness of deep learning.
神经元是指神经细胞。每个神经元都与数千个其他神经元相连，形成相应的功能区域，并与其他功能区域进行复杂的通信。它对人体的重要性不言而喻。也有许多学者研究细胞凋亡的机制。本文提出了一种基于多模态融合深度学习的肝硬化患者神经元凋亡和神经元癫痫样放电模型的研究，旨在研究大脑中异常神经元放电的影响因素。本文的方法是研究多模态信息融合方法，进行贝叶斯推断，并分析多模态医学数据。这些研究方法的功能是获取模态间信息独立性和信息交叉的关系。在神经元癫痫样放电模型中，检测了与坏死信号通路相关蛋白的 mRNA 表达水平，探讨了肝硬化患者神经元坏死的机制。实验表明，神经元识别率从 67.2%提高到 84.5%，时间也有所缩短，证明了深度学习的有效性。
