Tostudy thishypothesis, wepropose GatedL0 Regularized Dynamics (GateL0RD), a novel recurrent architecture that incorporates the inductive bias to maintain stable, sparsely changing latent states.

For the constructed knowledge graph, we use randomly initialized embeddingsH(0) = {v1,v2,...,vNKG} RNKG d to represent all node features. Table 2shows that all variants with different number ofretrieved instructionsNP can consistently outperform the baseline model, which proves the effectiveness of our approach in retrieving the working experience to boost the Patient Instruction generation. Asaresult, givenanewmale/female patient at61years old,wewillmatchmale/female patients in the age-group 55 <= Age < 70 in the training data to generate the PIs.

The "Patient Instruction" (PI), which contains critical instructional information provided bothtocarers andtothepatient atthetimeofdischarge,isessential for the patient to manage their condition outside hospital.