基于多模态大模型的ATM全周期诊疗技术方案
1. 数据预处理模块
算法1:多模态数据融合伪代码
def multimodal_fusion(data_dict):
aligned_data = temporal_alignment(
data_dict,
sampling_rate=100Hz,
interpolation='cubic'
)
normalized_data = []
for modality in ['MRI', 'EEG', 'blood']:
scaler = RobustScaler()
normalized_data.append(scaler.fit_transform(aligned_data[modality]))
fused_tensor = cross_attention_layer(
query=normalized_data[0],
key=normalentropy_data[1],
value=normalized_data[2]
)
return fused_tensor
流程图:数据预处理流程