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Working with Convex Responses: Antifragility from Finance to Oncology

We extend techniques and learnings about the stochastic properties of nonlinear responses from finance to medicine, particularly oncology, where it can inform dosing and intervention. We define antifragility. We propose uses of risk analysis for medical problems, through the properties of nonlinear...

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Detalles Bibliográficos
Autores principales: Taleb, Nassim Nicholas, West, Jeffrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955868/
https://www.ncbi.nlm.nih.gov/pubmed/36832709
http://dx.doi.org/10.3390/e25020343
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author Taleb, Nassim Nicholas
West, Jeffrey
author_facet Taleb, Nassim Nicholas
West, Jeffrey
author_sort Taleb, Nassim Nicholas
collection PubMed
description We extend techniques and learnings about the stochastic properties of nonlinear responses from finance to medicine, particularly oncology, where it can inform dosing and intervention. We define antifragility. We propose uses of risk analysis for medical problems, through the properties of nonlinear responses (convex or concave). We (1) link the convexity/concavity of the dose-response function to the statistical properties of the results; (2) define “antifragility” as a mathematical property for local beneficial convex responses and the generalization of “fragility” as its opposite, locally concave in the tails of the statistical distribution; (3) propose mathematically tractable relations between dosage, severity of conditions, and iatrogenics. In short, we propose a framework to integrate the necessary consequences of nonlinearities in evidence-based oncology and more general clinical risk management.
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spelling pubmed-99558682023-02-25 Working with Convex Responses: Antifragility from Finance to Oncology Taleb, Nassim Nicholas West, Jeffrey Entropy (Basel) Article We extend techniques and learnings about the stochastic properties of nonlinear responses from finance to medicine, particularly oncology, where it can inform dosing and intervention. We define antifragility. We propose uses of risk analysis for medical problems, through the properties of nonlinear responses (convex or concave). We (1) link the convexity/concavity of the dose-response function to the statistical properties of the results; (2) define “antifragility” as a mathematical property for local beneficial convex responses and the generalization of “fragility” as its opposite, locally concave in the tails of the statistical distribution; (3) propose mathematically tractable relations between dosage, severity of conditions, and iatrogenics. In short, we propose a framework to integrate the necessary consequences of nonlinearities in evidence-based oncology and more general clinical risk management. MDPI 2023-02-13 /pmc/articles/PMC9955868/ /pubmed/36832709 http://dx.doi.org/10.3390/e25020343 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Taleb, Nassim Nicholas
West, Jeffrey
Working with Convex Responses: Antifragility from Finance to Oncology
title Working with Convex Responses: Antifragility from Finance to Oncology
title_full Working with Convex Responses: Antifragility from Finance to Oncology
title_fullStr Working with Convex Responses: Antifragility from Finance to Oncology
title_full_unstemmed Working with Convex Responses: Antifragility from Finance to Oncology
title_short Working with Convex Responses: Antifragility from Finance to Oncology
title_sort working with convex responses: antifragility from finance to oncology
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9955868/
https://www.ncbi.nlm.nih.gov/pubmed/36832709
http://dx.doi.org/10.3390/e25020343
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