Transparent Modelling of Risk Assessment factors for Assisted Living

Research output: Contribution to conferencePaper

Abstract

Advances in healthcare and improvements in lifestyle have contributed to a rising population of an aging society. Within the social care profession, this causes concern as resources are continually spread thin resulting in increased stress for individual workers and increased financial implications for established healthcare providers. One possible solution to alleviate stress and free up resources is to employ the use of computational intelligence within a home environment to determine important risk factors which should allow health- and social-care professionals to put preventative measures in place to protect elderly people from harm thereby reducing the financial implications of hospital care. A major limitation of computational risk models can that they can be quite complex and cumbersome due to the richness of data used to derive the model, not all of which is particularly useful for determining associated risk. In this paper, a transparent risk modelling method is presented which as well as computing an overall risk level, also reduces model complexity by determining which data are relevant. The transparent nature of the model allows users to understand the model structure used to compute the risk level which is important if health care professional are expected to use such algorithms in the future.

Conference

ConferenceSYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE
Abbreviated titleCiFER
CountryIndia
CityBenguluru
Period18/11/1820/11/18

Fingerprint

Modeling
Risk assessment
Healthcare
Factors
Resources
Social care
Workers
Risk factors
Modeling method
Computational intelligence
Hospital care
Risk model
Lifestyle
Elderly people

Keywords

  • Risk-analysis
  • Computational modelling

Cite this

Vance, P., Coleman, S., Kerr, D., Lindsay, L., Taylor, B., Kerr, E., ... Wu, C. (Accepted/In press). Transparent Modelling of Risk Assessment factors for Assisted Living. Paper presented at SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE, Benguluru, India.
Vance, Philip ; Coleman, Sonya ; Kerr, Dermot ; Lindsay, Leeanne ; Taylor, Brian ; Kerr, Emmett ; Gardiner, Bryan ; McGinnity, T.Martin ; Wu, Chengdong. / Transparent Modelling of Risk Assessment factors for Assisted Living. Paper presented at SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE, Benguluru, India.7 p.
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abstract = "Advances in healthcare and improvements in lifestyle have contributed to a rising population of an aging society. Within the social care profession, this causes concern as resources are continually spread thin resulting in increased stress for individual workers and increased financial implications for established healthcare providers. One possible solution to alleviate stress and free up resources is to employ the use of computational intelligence within a home environment to determine important risk factors which should allow health- and social-care professionals to put preventative measures in place to protect elderly people from harm thereby reducing the financial implications of hospital care. A major limitation of computational risk models can that they can be quite complex and cumbersome due to the richness of data used to derive the model, not all of which is particularly useful for determining associated risk. In this paper, a transparent risk modelling method is presented which as well as computing an overall risk level, also reduces model complexity by determining which data are relevant. The transparent nature of the model allows users to understand the model structure used to compute the risk level which is important if health care professional are expected to use such algorithms in the future.",
keywords = "Risk-analysis, Computational modelling",
author = "Philip Vance and Sonya Coleman and Dermot Kerr and Leeanne Lindsay and Brian Taylor and Emmett Kerr and Bryan Gardiner and T.Martin McGinnity and Chengdong Wu",
year = "2018",
month = "9",
day = "1",
language = "English",
note = "SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE : IEEE Symposium on Computational Intelligence for Financial Engineering and Economics, CiFER ; Conference date: 18-11-2018 Through 20-11-2018",

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Vance, P, Coleman, S, Kerr, D, Lindsay, L, Taylor, B, Kerr, E, Gardiner, B, McGinnity, TM & Wu, C 2018, 'Transparent Modelling of Risk Assessment factors for Assisted Living' Paper presented at SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE, Benguluru, India, 18/11/18 - 20/11/18, .

Transparent Modelling of Risk Assessment factors for Assisted Living. / Vance, Philip; Coleman, Sonya; Kerr, Dermot; Lindsay, Leeanne; Taylor, Brian; Kerr, Emmett; Gardiner, Bryan; McGinnity, T.Martin; Wu, Chengdong.

2018. Paper presented at SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE, Benguluru, India.

Research output: Contribution to conferencePaper

TY - CONF

T1 - Transparent Modelling of Risk Assessment factors for Assisted Living

AU - Vance, Philip

AU - Coleman, Sonya

AU - Kerr, Dermot

AU - Lindsay, Leeanne

AU - Taylor, Brian

AU - Kerr, Emmett

AU - Gardiner, Bryan

AU - McGinnity, T.Martin

AU - Wu, Chengdong

PY - 2018/9/1

Y1 - 2018/9/1

N2 - Advances in healthcare and improvements in lifestyle have contributed to a rising population of an aging society. Within the social care profession, this causes concern as resources are continually spread thin resulting in increased stress for individual workers and increased financial implications for established healthcare providers. One possible solution to alleviate stress and free up resources is to employ the use of computational intelligence within a home environment to determine important risk factors which should allow health- and social-care professionals to put preventative measures in place to protect elderly people from harm thereby reducing the financial implications of hospital care. A major limitation of computational risk models can that they can be quite complex and cumbersome due to the richness of data used to derive the model, not all of which is particularly useful for determining associated risk. In this paper, a transparent risk modelling method is presented which as well as computing an overall risk level, also reduces model complexity by determining which data are relevant. The transparent nature of the model allows users to understand the model structure used to compute the risk level which is important if health care professional are expected to use such algorithms in the future.

AB - Advances in healthcare and improvements in lifestyle have contributed to a rising population of an aging society. Within the social care profession, this causes concern as resources are continually spread thin resulting in increased stress for individual workers and increased financial implications for established healthcare providers. One possible solution to alleviate stress and free up resources is to employ the use of computational intelligence within a home environment to determine important risk factors which should allow health- and social-care professionals to put preventative measures in place to protect elderly people from harm thereby reducing the financial implications of hospital care. A major limitation of computational risk models can that they can be quite complex and cumbersome due to the richness of data used to derive the model, not all of which is particularly useful for determining associated risk. In this paper, a transparent risk modelling method is presented which as well as computing an overall risk level, also reduces model complexity by determining which data are relevant. The transparent nature of the model allows users to understand the model structure used to compute the risk level which is important if health care professional are expected to use such algorithms in the future.

KW - Risk-analysis

KW - Computational modelling

M3 - Paper

ER -

Vance P, Coleman S, Kerr D, Lindsay L, Taylor B, Kerr E et al. Transparent Modelling of Risk Assessment factors for Assisted Living. 2018. Paper presented at SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE, Benguluru, India.