Responses to Lifestyle Intervention in Individuals at High Risk of Type 2 Diabetes Depend on Pre-Intervention Insulin Sensitivity and Secretion: A Machine Learning Analysis of DEXLIFE and EGIR-RISC Data

S. Sabatini; G. O'Donoghue; A. Kennedy; J. Petrie; M. Walker; D.J. O'Gorman; A. Gastaldelli

doi:10.2139/ssrn.4593215

Responses to Lifestyle Intervention in Individuals at High Risk of Type 2 Diabetes Depend on Pre-Intervention Insulin Sensitivity and Secretion: A Machine Learning Analysis of DEXLIFE and EGIR-RISC Data

S. Sabatini
, G. O'Donoghue
, A. Kennedy
, J. Petrie
, M. Walker
, D.J. O'Gorman
, A. Gastaldelli

School of Biological, Health and Sports Sciences

Research output: Other contribution › peer-review

Original language	Undefined/Unknown
DOIs	https://doi.org/10.2139/ssrn.4593215
Publication status	Published - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

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10.2139/ssrn.4593215

Cite this

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title = "Responses to Lifestyle Intervention in Individuals at High Risk of Type 2 Diabetes Depend on Pre-Intervention Insulin Sensitivity and Secretion: A Machine Learning Analysis of DEXLIFE and EGIR-RISC Data",

author = "S. Sabatini and G. O'Donoghue and A. Kennedy and J. Petrie and M. Walker and D.J. O'Gorman and A. Gastaldelli",

year = "2023",

doi = "10.2139/ssrn.4593215",

language = "Undefined/Unknown",

type = "Other",

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AU - O'Donoghue, G.

AU - Kennedy, A.

AU - Petrie, J.

AU - Walker, M.

AU - O'Gorman, D.J.

AU - Gastaldelli, A.

PY - 2023

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