Models

We implement the following models for supporting multiple healthcare predictive tasks.

• pyhealth.models.MLP
  • MLP
    • MLP.mean_pooling()
    • MLP.sum_pooling()
    • MLP.forward()
    • MLP.training
• pyhealth.models.CNN
  • CNNLayer
    • CNNLayer.forward()
    • CNNLayer.training
  • CNN
    • CNN.forward()
    • CNN.training
• pyhealth.models.RNN
  • RNNLayer
    • RNNLayer.forward()
    • RNNLayer.training
  • RNN
    • RNN.forward()
    • RNN.training
• pyhealth.models.Transformer
  • TransformerLayer
    • TransformerLayer.forward()
    • TransformerLayer.training
  • Transformer
    • Transformer.forward()
    • Transformer.training
• pyhealth.models.RETAIN
  • RETAINLayer
    • RETAINLayer.reverse_x()
    • RETAINLayer.compute_alpha()
    • RETAINLayer.compute_beta()
    • RETAINLayer.forward()
    • RETAINLayer.training
  • RETAIN
    • RETAIN.forward()
    • RETAIN.training
• pyhealth.models.GAMENet
  • GAMENetLayer
    • GAMENetLayer.forward()
    • GAMENetLayer.training
  • GAMENet
    • GAMENet.generate_ehr_adj()
    • GAMENet.generate_ddi_adj()
    • GAMENet.forward()
    • GAMENet.training
• pyhealth.models.MICRON
  • MICRONLayer
    • MICRONLayer.compute_reconstruction_loss()
    • MICRONLayer.forward()
    • MICRONLayer.training
  • MICRON
    • MICRON.generate_ddi_adj()
    • MICRON.forward()
    • MICRON.training
• pyhealth.models.SafeDrug
  • SafeDrugLayer
    • SafeDrugLayer.pad()
    • SafeDrugLayer.calculate_loss()
    • SafeDrugLayer.forward()
    • SafeDrugLayer.training
  • SafeDrug
    • SafeDrug.generate_ddi_adj()
    • SafeDrug.generate_smiles_list()
    • SafeDrug.generate_mask_H()
    • SafeDrug.generate_molecule_info()
    • SafeDrug.forward()
    • SafeDrug.training
• pyhealth.models.MoleRec
  • MoleRecLayer
    • MoleRecLayer.calc_loss()
    • MoleRecLayer.forward()
    • MoleRecLayer.training
  • MoleRec
    • MoleRec.generate_ddi_adj()
    • MoleRec.generate_substructure_mask()
    • MoleRec.generate_smiles_list()
    • MoleRec.generate_average_projection()
    • MoleRec.encode_patient()
    • MoleRec.forward()
    • MoleRec.training
• pyhealth.models.Deepr
  • DeeprLayer
    • DeeprLayer.forward()
    • DeeprLayer.training
  • Deepr
    • Deepr.forward()
    • Deepr.training
• pyhealth.models.ContraWR
  • ResBlock2D
    • ResBlock2D.forward()
    • ResBlock2D.training
  • ContraWR
    • ContraWR.cal_encoder_stat()
    • ContraWR.torch_stft()
    • ContraWR.forward()
    • ContraWR.training
• pyhealth.models.SparcNet
  • DenseLayer
    • DenseLayer.forward()
  • DenseBlock
  • TransitionLayer
  • SparcNet
    • SparcNet.label_tokenizer
    • SparcNet.forward()
    • SparcNet.training
• pyhealth.models.StageNet
  • StageNetLayer
    • StageNetLayer.cumax()
    • StageNetLayer.step()
    • StageNetLayer.forward()
    • StageNetLayer.training
  • StageNet
    • StageNet.forward()
    • StageNet.training
• pyhealth.models.AdaCare
  • AdaCareLayer
    • AdaCareLayer.forward()
    • AdaCareLayer.training
  • AdaCare
    • AdaCare.forward()
    • AdaCare.training
• pyhealth.models.ConCare
  • ConCareLayer
    • ConCareLayer.concare_encoder()
    • ConCareLayer.forward()
    • ConCareLayer.training
  • ConCare
    • ConCare.training
    • ConCare.forward()
• pyhealth.models.Agent
  • AgentLayer
    • AgentLayer.choose_action()
    • AgentLayer.forward()
    • AgentLayer.training
  • Agent
    • Agent.get_loss()
    • Agent.forward()
    • Agent.training
• pyhealth.models.GRASP
  • GRASPLayer
    • GRASPLayer.sample_gumbel()
    • GRASPLayer.gumbel_softmax_sample()
    • GRASPLayer.gumbel_softmax()
    • GRASPLayer.grasp_encoder()
    • GRASPLayer.forward()
    • GRASPLayer.training
  • GRASP
    • GRASP.forward()
    • GRASP.training
• pyhealth.models.TCN
  • TCNLayer
    • TCNLayer.forward()
    • TCNLayer.training
  • TCN
    • TCN.forward()
    • TCN.training
• pyhealth.models.GAN
  • GAN
    • GAN.discriminate()
    • GAN.sampling()
    • GAN.generate_fake()
    • GAN.training
• pyhealth.models.VAE
  • VAE
    • VAE.encoder()
    • VAE.sampling()
    • VAE.decoder()
    • VAE.loss_function()
    • VAE.forward()
    • VAE.training