FairCareAI
Copyright 2025 FairCareAI Contributors

This product includes software developed at Rush University Medical Center.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

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This software implements methodologies described in:

[1] Van Calster B, Collins GS, Vickers AJ, et al. Evaluation of
    performance measures in predictive artificial intelligence models
    to support medical decisions. Lancet Digit Health 2025.
    DOI: 10.1016/j.landig.2025.100916

[2] Coalition for Health AI. RAIC Checkpoint 1: Model Card for
    Responsible AI in Clinical Practice. Version 1.0. 2024.
    https://www.coalitionforhealthai.org

[3] Collins GS, Moons KGM, Dhiman P, et al. TRIPOD+AI statement:
    updated guidance for reporting clinical prediction models that
    use regression or machine learning methods. BMJ 2024.
    DOI: 10.1136/bmj-2023-078378

[4] Chouldechova A. Fair prediction with disparate impact: A study
    of bias in recidivism prediction instruments. Big Data 2017.

[5] Kleinberg J, Mullainathan S, Raghavan M. Inherent trade-offs
    in the fair determination of risk scores. ITCS 2017.
