The invention relates to the technical field of medical prediction, in particular to a digital twinborn prediction method for patient
lung protective ventilation supported by ECMO, which comprises the following steps: extracting flow velocity change and jump points under the support of ECMO, constructing a ventilation fluctuation trend map, identifying fluctuation sections by combining compliance and pressure value ratio, delimiting
lung partitions and analyzing
oxygenation ratio trend. And generating an
oxygenation capability classification graph, sequencing ventilation path effects, and outputting a pulmonary protective ventilation digital twinborn prediction scheme. According to the method, dynamic response mapping of ventilation behaviors is established on the basis of timing sequence changes of
breathing flow velocity jump characteristics and compliance pressure value ratios, the
lung regional ventilation state is accurately recognized,
lung function zoning division is achieved by combining
oxygenation ratio waveform classification, ventilation path utility sorting is completed through oxygenation descending characteristics under
path coverage, and the
lung function evaluation accuracy is improved. And a path
state prediction sequence is constructed by fusing the change relationship between the tensile stress and the ventilation pressure, so that the dynamic adaptability of the ventilation strategy to the lung
mechanics and oxygenation state and the region matching precision are improved.