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Found 6 papers, 4 papers with code
Conversational Disease Diagnosis via External Planner-Controlled Large Language Models
By utilizing real patient electronic medical record data, we constructed simulated dialogues between virtual patients and doctors and evaluated the diagnostic abilities of our system.
CTP:A Causal Interpretable Model for Non-Communicable Disease Progression Prediction
The CTP model combines trajectory prediction and causal discovery to enable accurate prediction of disease progression trajectories and uncover causal relationships between features.
Replicating Complex Dialogue Policy of Humans via Offline Imitation Learning with Supervised Regularization
Policy learning (PL) is a module of a task-oriented dialogue system that trains an agent to make actions in each dialogue turn.
On Tracking Dialogue State by Inheriting Slot Values in Mentioned Slot Pools
The MSP is a slot-specific memory that records all mentioned slot values that may be inherited, and our model updates slot values according to the MSP and the dialogue context.
Interpretable Disease Prediction based on Reinforcement Path Reasoning over Knowledge Graphs
In the disease prediction task, our model achieves 0. 743 and 0. 639 in terms of macro area under the curve (AUC) in predicting 53 circulation system diseases in the two datasets, respectively.
Deep representation learning for individualized treatment effect estimation using electronic health records
We propose a novel hybrid model bridging multi-task deep learning and K-nearest neighbors (KNN) for ITE estimation.
Ranked #3 on
Causal Inference
on IHDP
