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Assessing Phenotype Definitions for Algorithmic Fairness [article]

Tony Y. Sun, Shreyas Bhave, Jaan Altosaar, Noémie Elhadad
2022 arXiv   pre-print
In this paper, we propose a set of best practices to assess the fairness of phenotype definitions.  ...  We hope that the proposed best practices can help in constructing fair and inclusive phenotype definitions.  ...  Best Practices: Assessing the Algorithmic Fairness of Phenotypes We propose a set of best practices for the research community to use when constructing and assessing phenotype definitions.  ... 
arXiv:2203.05174v1 fatcat:cdwqn76mbjdppe7e3jznxcbh74

Clinical Research Informatics: Contributions from 2016

C. Daniel, R. Choquet
2017 IMIA Yearbook of Medical Informatics  
The third selected paper describes the FAIR Guiding Principles for scientific data management and stewardship.  ...  The authors of the first paper utilized a comprehensive representation of the patient medical record and semi-automatically labeled training sets to create phenotype models via a machine learning process  ...  The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 2016;3:160018.  ... 
doi:10.15265/iy-2017-024 pmid:29063566 pmcid:PMC6239247 fatcat:wccnwc7n4faz7gawafsyuqnxg4

Clinical Research Informatics: Contributions from 2016

C. Daniel, R. Choquet
2017 IMIA Yearbook of Medical Informatics  
The third selected paper describes the FAIR Guiding Principles for scientific data management and stewardship.  ...  The authors of the first paper utilized a comprehensive representation of the patient medical record and semi-automatically labeled training sets to create phenotype models via a machine learning process  ...  The FAIR Guiding Principles for scientific data management and stewardship. Sci Data 2016;3:160018.  ... 
doi:10.1055/s-0037-1606504 fatcat:uy5mvgca75do5hs34od5fcrqty

Interpretation According to Clone-Specific PD-L1 Cutoffs Reveals Better Concordance in Muscle-Invasive Urothelial Carcinoma

Tzu-Hao Huang, Wei Cheng, Yeh-Han Wang
2021 Diagnostics  
Our findings imply that a universal cutoff value is not feasible for UC; we propose that PD-L1 IHC assays for UC should be interpreted according to a clone-specific scoring algorithm and cutoff value.  ...  Fair to moderate correlation and concordance were observed in IC expression in most pairwise comparisons of clones.  ...  Thus, applying any TC scoring algorithm and cutoffs to SP142 for assessing PD-L1 expression would be inappropriate.  ... 
doi:10.3390/diagnostics11030448 pmid:33807802 fatcat:u5igs2nonrehfjk65h6dmw7pdm

Probabilistic Machine Learning for Healthcare [article]

Irene Y. Chen, Shalmali Joshi, Marzyeh Ghassemi, Rajesh Ranganath
2020 arXiv   pre-print
Beyond predictive models, we also investigate the utility of probabilistic machine learning models in phenotyping, in generative models for clinical use cases, and in reinforcement learning.  ...  Krishnan, Peter Schulam, and Pete Szolovits for helpful and useful feedback. This work was supported in part by a CIFAR AI Chair at the Vector Institute (MG) and Microsoft Research (MG).  ...  In this family of fairness definitions, algorithmic bias is assessed based on known and pre-defined sensitive attribute groups, e.g. race, gender, socioeconomic status.  ... 
arXiv:2009.11087v1 fatcat:htosfeqvhndvfmlmud2pvl3nsy

Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings [article]

Haoran Zhang, Amy X. Lu, Mohamed Abdalla, Matthew McDermott, Marzyeh Ghassemi
2020 arXiv   pre-print
Second, we evaluate performance gaps across different definitions of fairness on over 50 downstream clinical prediction tasks that include detection of acute and chronic conditions.  ...  Finally, we explore shortcomings of using adversarial debiasing to obfuscate subgroup information in contextual word embeddings, and recommend best practices for such deep embedding models in clinical  ...  In order to quantify how "fair" the model is, we must turn to a definition of fairness from the literature.  ... 
arXiv:2003.11515v1 fatcat:jvy2px2s7zejhg64tnxtxoztsq

Towards an Ontology-Based Phenotypic Query Model

Christoph Beger, Franz Matthies, Ralph Schäfermeier, Toralf Kirsten, Heinrich Herre, Alexandr Uciteli
2022 Applied Sciences  
This makes it difficult for domain experts (e.g., clinicians) to build and execute search queries. In this work, the Core Ontology of Phenotypes is used as a general model for phenotypic knowledge.  ...  A specific model describing a set of particular phenotype classes is called a Phenotype Specification Ontology.  ...  Nelson et al. proposed a low-burden, multicentric model for cohort assessments based on computable phenotype algorithms [61] .  ... 
doi:10.3390/app12105214 fatcat:3caezt6hxbfzfihfdj7l3n45uu

Algorithm Fairness in AI for Medicine and Healthcare [article]

Richard J. Chen, Tiffany Y. Chen, Jana Lipkova, Judy J. Wang, Drew F.K. Williamson, Ming Y. Lu, Sharifa Sahai, Faisal Mahmood
2022 arXiv   pre-print
In the current development and deployment of many artificial intelligence (AI) systems in healthcare, algorithm fairness is a challenging problem in delivering equitable care.  ...  In this perspective article, we summarize the intersectional field of fairness in machine learning through the context of current issues in healthcare, outline how algorithmic biases (e.g. - image acquisition  ...  cancer phenotypes, but also elucidating a potential novel, population-specific phenotype for African American patients 275 .  ... 
arXiv:2110.00603v2 fatcat:pspb6bqqxjh45an5mhqohysswu

AGINFRA PLUS D7.4 - Food Security Pilot Evaluation Report

Pascal Neveu, Alice Boizet
2020 Zenodo  
This document describes the evaluation procedure performed in the AGINFRA+ project to assess the VRE developed for the Food Security community and reports on the outcomes of the different evaluation phases  ...  Three phases of evaluation have been performed in order to assess the VRE at different stages of its development and then being able to take into account the users feedbacks for adding improvements.  ...  • FAIR-ness: How does the VRE help in making research data and algorithms FAIR (Findable, Accessible, Interoperable, Reusable).  ... 
doi:10.5281/zenodo.3634623 fatcat:3bjw5iaymnfqjjelbcgv2gni2a

The child bipolar questionnaire: A dimensional approach to screening for pediatric bipolar disorder

Demitri Papolos, John Hennen, Melissa S. Cockerham, Henry C. Thode, Eric A. Youngstrom
2006 Journal of Affective Disorders  
The Child Bipolar Questionnaire (CBQ) is a rapid screener with a Core Index subscale of symptom dimensions frequently reported in childhood-onset bipolar disorder (BD) and scoring algorithms for DSM-IV  ...  Conclusions: The CBQ shows potential for rapid and economically feasible identification of possible childhood-onset BD cases as defined by DSM-IV criteria as well as by alternate disease phenotypes.  ...  proposed (Papolos and Papolos, 2001; Papolos et al., 2005b ) (see Table 1 for phenotype definitions).  ... 
doi:10.1016/j.jad.2006.03.026 pmid:16797720 fatcat:5pt26oh2cjaivfgjlgxyth3fxm


O. Scholz, F. Uhrmann, A. Wolff, K. Pieger, D. Penk
2019 ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences  
The resulting data is then compared to plant assessments of the same plants performed by sugar beet experts in order to evaluate the viability of automatic plant assessment in the sugar beet breeding process  ...  A customized leaf model developed specifically for sugar beet plants then models the leaves, yielding a vector of descriptive parameters for each leaf.  ...  The authors would like to thank all partners within "For3D" for their cooperation and valuable contributions.  ... 
doi:10.5194/isprs-annals-iv-2-w7-161-2019 fatcat:2273dhdkabbk5mvn43xu2fo77u

Machine learning approaches for electronic health records phenotyping: A methodical review [article]

Siyue Yang, Paul Varghese, Ellen Stephenson, Karen Tu, Jessica Gronsbell
2022 medRxiv   pre-print
complex phenotypes and standards for reporting and evaluating phenotyping algorithms.  ...  Federated learning has been applied to develop algorithms across multiple institutions while preserving data privacy (n = 2, 1.9%).DiscussionWhile the use of ML for phenotyping is growing, most articles  ...  Only 1 article evaluated algorithmic fairness [161] . Fairness must be integrated into phenotyping in the future.  ... 
doi:10.1101/2022.04.23.22274218 fatcat:bnbwld7tefe7vm74rql4wuub2q

Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study

Nicole Martinez-Martin, Henry T Greely, Mildred K Cho
2021 JMIR mHealth and uHealth  
, and fairness.  ...  The panelists focused primarily on clinical applications for digital phenotyping for mental health but also included recommendations regarding transparency and data protection to address potential areas  ...  For these reasons, we assessed both the necessity and feasibility.  ... 
doi:10.2196/27343 fatcat:4qcmvnpoejgx3oe6ci5dtafzwq

Challenges and Opportunities in Machine-Augmented Plant Stress Phenotyping

Arti Singh, Sarah Jones, Baskar Ganapathysubramanian, Soumik Sarkar, Daren Mueller, Kulbir Sandhu, Koushik Nagasubramanian
2020 Trends in Plant Science  
We propose an overarching strategy for utilizing ML techniques that methodically enables the application of plant stress phenotyping at multiple scales across different types of stresses, program goals  ...  Standardization of visual assessments and deployment of imaging techniques have improved the accuracy and reliability of stress assessment in comparison with unaided visual measurement.  ...  Accuracy refers to the extent that the estimated stress assessment corresponds to the definite value of stress [14, 16] .  ... 
doi:10.1016/j.tplants.2020.07.010 pmid:32830044 fatcat:soplocjs5jfpnipyryxpk7jmcq

Developing a data element repository to support EHR-driven phenotype algorithm authoring and execution

Guoqian Jiang, Richard C. Kiefer, Luke V. Rasmussen, Harold R. Solbrig, Huan Mo, Jennifer A. Pacheco, Jie Xu, Enid Montague, William K. Thompson, Joshua C. Denny, Christopher G. Chute, Jyotishman Pathak
2016 Journal of Biomedical Informatics  
In conjunction with the HL7 Health Quality Measures Format (HQMF), QDM contains core elements that make it a promising model for representing EHR-driven phenotype algorithms for clinical research.  ...  The objective of the present study is to develop and evaluate a data element repository (DER) for providing machine-readable QDM data element service APIs to support phenotype algorithm authoring and execution  ...  ., textual definition) in the PhEMA phenotype algorithm authoring application and (B) the use of QDM data elements in constructing executable phenotype algorithms in the Konstanz Information Miner (KNIME  ... 
doi:10.1016/j.jbi.2016.07.008 pmid:27392645 pmcid:PMC5490836 fatcat:xuk6zqpgfjfkbmadicpiryecky
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