癫痫发作风险预测方法论。将iEEG功能脑网络嵌入低维欧氏空间，定义无量纲生物标志物区分发作间期和发作前期。适用于癫痫发作预测、iEEG分析。触发词：癫痫预测、seizure forecasting、preictal。
将 iEEG 功能连接网络嵌入低维欧氏空间，预测发作前状态（24小时内发作风险）。
来源： arXiv:2505.00856 效用： 1.0
import numpy as np
from sklearn.manifold import MDS
class SeizureRiskForecaster:
def __init__(self, n_components=3):
self.embedder = MDS(n_components=n_components)
def compute_fc(self, iEEG):
fc = np.corrcoef(iEEG)
return 1 - np.abs(fc)
def embed(self, dist):
return self.embedder.fit_transform(dist)
def compute_biomarker(self, curr, ref):
c = np.mean(curr, axis=0)
r = np.mean(ref, axis=0)
return np.linalg.norm(c-r) / (np.std(ref)+1e-10)
def predict(self, iEEG, ref, thresh=2.0):
B = self.compute_biomarker(self.embed(self.compute_fc(iEEG)),
self.embed(self.compute_fc(ref)))
return 1/(1+np.exp(-(B-thresh))), B>thresh
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