Data for: A Veto-Aware Decision Support Framework for Heterogeneous Medical Large-Scale Group Consensus under Time Pressure

Description

This dataset supports the manuscript “A Veto-Aware Decision Support Framework for Heterogeneous Medical Large-Scale Group Consensus under Time Pressure”. The dataset contains the simulated case-study inputs and analysis tables used to evaluate the VAH-Consensus framework for veto-aware heterogeneous medical large-scale group consensus under time pressure. The files include decision-maker role attributes, initial probabilistic linguistic term set (PLTS) evaluations, transformed PLTS scores, dimensional fluctuation energy and balance factors, normalized expertise and interest weights, consensus-reaching process parameter settings, key iteration records, veto versus non-veto comparison results, and reward-function coefficient configurations. The data are derived from a simulated medical shared decision-making case and do not contain personal, patient-level, or confidential clinical information.

Steps to reproduce

1. Download and unzip the dataset package. 2. Open `manifest.csv` to identify each data file and its corresponding manuscript table. 3. Use `data/table_02_decision_maker_roles_and_attributes.csv` as the simulated decision-maker attribute input. 4. Use `data/table_03_initial_plts_evaluations_partial.csv` and `data/table_11_appendix_initial_plts_evaluations.csv` as the initial PLTS preference-evaluation data. 5. Use `data/table_04_initial_plts_scores_partial.csv` and `data/table_12_appendix_initial_plts_scores.csv` as the transformed score data. 6. Apply the equations and algorithmic steps described in the manuscript to compute heterogeneous weights, group centers, community structures, consensus levels, and adjustment paths. 7. Use `data/table_07_crp_parameter_settings.csv` as the parameter configuration for the consensus-reaching process. 8. Compare the reproduced outputs with `data/table_05_dimensional_fluctuation_energy_and_balance_factor.csv`, `data/table_06_normalized_and_integrated_weights.csv`, `data/table_08_crp_key_parameter_changes_partial.csv`, `data/table_09_veto_vs_non_veto_comparison.csv`, and `data/table_10_reward_function_coefficient_configurations.csv`. 9. For exact mathematical notation and formula definitions, refer to the corresponding equations and tables in the manuscript, because some Word equation objects may not be fully represented as plain text in the CSV files.

Institutions

• Sichuan University

  Sichuan, Chengdu

Categories

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