Current trends of computational tools and artificial intelligence in geriatric medicine

Wireko Andrew Awuah; Brian M. Ou Yong; Tatiana Mikhailova; Jyi Cheng Ng; Toufik Abdul-Rahman; Rohan Yarlagadda; Alexander J. Tedeschi; Goshen David Miteu; Tulika Garg; Lian David; Edouard Lansiaux; Helen Huang; Esther Patience Nansubuga; Ayush Anand; Kateryna Sikora; Arda Isik; Sandip Debnath; Sourish Pramanik; Dibyendu Seth; Nobendu Mukerjee; Flora Narli; Rohit Sharma; Arabinda Ghosh; Ghulam Md Ashraf; Αthanasios Alexiou

doi:10.1016/B978-0-443-15702-8.00023-3

Current trends of computational tools and artificial intelligence in geriatric medicine

Wireko Andrew Awuah
, Brian M. Ou Yong
, Tatiana Mikhailova
, Jyi Cheng Ng
, Toufik Abdul-Rahman
, Rohan Yarlagadda
, Alexander J. Tedeschi
, Goshen David Miteu
, Tulika Garg
, Lian David
, Edouard Lansiaux
, Helen Huang
, Esther Patience Nansubuga
, Ayush Anand
, Kateryna Sikora
, Arda Isik
, Sandip Debnath
, Sourish Pramanik
, Dibyendu Seth
, Nobendu Mukerjee

Flora Narli, Rohit Sharma, Arabinda Ghosh, Ghulam Md Ashraf, Αthanasios Alexiou

Otto von Guericke University Magdeburg
Sumy State University
University of Glasgow
SUNY Upstate Medical University
Universiti Putra Malaysia
Rowan-Virtua School of Osteopathic Medicine
University of Nottingham
Government Medical College & Hospital Chandigarh
University of East Anglia
Université de Lille
Royal College of Surgeons in Ireland
University of Leeds
B P Koirala Institute of Health Sciences
Istanbul Medeniyet University
Visva-Bharati University
West Bengal State University
Novel Global Community Educational Foundation
Saveetha Institute of Medical and Technical Sciences (Deemed to be University)
Technical University of Crete
Banaras Hindu University
Gauhati University
University of Sharjah
AFNP Med
Chandigarh University

Research output: Chapter in Book or Report/Conference proceeding › Chapter › peer-review

Abstract

As lifespans grow across the globe, so does the prevalence of neurodegenerative diseases among a rapidly expanding elderly demographic. Originating in the brain—the least understood organ in the human body—neurodegenerative diseases are caused by complex mechanisms that are challenging to study in a heterogeneous patient population. Machine learning, natural language processing, and other subfields of artificial intelligence have shown great promise as computational tools enabling physician-scientists to tackle these challenges on a potentially large scale. This chapter explores current applications of artificial intelligence in the classification, treatment, and management of the most common neurodegenerative diseases.

Original language	English
Title of host publication	Essential Guide to Neurodegenerative Disorders
Subtitle of host publication	Mechanistic, Diagnostic and Therapeutic Advances
Publisher	Elsevier
Pages	363-374
Number of pages	12
ISBN (Electronic)	9780443157028
ISBN (Print)	9780443157035
DOIs	https://doi.org/10.1016/B978-0-443-15702-8.00023-3
Publication status	Published - 1 Jan 2025
Externally published	Yes

UN SDGs

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

SDG 3 Good Health and Well-being

Keywords

Artificial intelligence
Geriatrics
Machine learning
Neurodegenerative disorders
Therapeutic procedure

Access to Document

10.1016/B978-0-443-15702-8.00023-3

Cite this

Awuah, W. A., Ou Yong, B. M., Mikhailova, T., Ng, J. C., Abdul-Rahman, T., Yarlagadda, R., Tedeschi, A. J., Miteu, G. D., Garg, T., David, L., Lansiaux, E., Huang, H., Nansubuga, E. P., Anand, A., Sikora, K., Isik, A., Debnath, S., Pramanik, S., Seth, D., ... Alexiou, Α. (2025). Current trends of computational tools and artificial intelligence in geriatric medicine. In Essential Guide to Neurodegenerative Disorders: Mechanistic, Diagnostic and Therapeutic Advances (pp. 363-374). Elsevier. https://doi.org/10.1016/B978-0-443-15702-8.00023-3

@inbook{7b3e86dc0ec74150b0d7d96d9748c6fe,

title = "Current trends of computational tools and artificial intelligence in geriatric medicine",

abstract = "As lifespans grow across the globe, so does the prevalence of neurodegenerative diseases among a rapidly expanding elderly demographic. Originating in the brain—the least understood organ in the human body—neurodegenerative diseases are caused by complex mechanisms that are challenging to study in a heterogeneous patient population. Machine learning, natural language processing, and other subfields of artificial intelligence have shown great promise as computational tools enabling physician-scientists to tackle these challenges on a potentially large scale. This chapter explores current applications of artificial intelligence in the classification, treatment, and management of the most common neurodegenerative diseases.",

keywords = "Artificial intelligence, Geriatrics, Machine learning, Neurodegenerative disorders, Therapeutic procedure",

author = "Awuah, \{Wireko Andrew\} and \{Ou Yong\}, \{Brian M.\} and Tatiana Mikhailova and Ng, \{Jyi Cheng\} and Toufik Abdul-Rahman and Rohan Yarlagadda and Tedeschi, \{Alexander J.\} and Miteu, \{Goshen David\} and Tulika Garg and Lian David and Edouard Lansiaux and Helen Huang and Nansubuga, \{Esther Patience\} and Ayush Anand and Kateryna Sikora and Arda Isik and Sandip Debnath and Sourish Pramanik and Dibyendu Seth and Nobendu Mukerjee and Flora Narli and Rohit Sharma and Arabinda Ghosh and \{Md Ashraf\}, Ghulam and Αthanasios Alexiou",

year = "2025",

month = jan,

day = "1",

doi = "10.1016/B978-0-443-15702-8.00023-3",

language = "English",

isbn = "9780443157035",

pages = "363--374",

booktitle = "Essential Guide to Neurodegenerative Disorders",

publisher = "Elsevier",

}

Awuah, WA, Ou Yong, BM, Mikhailova, T, Ng, JC, Abdul-Rahman, T, Yarlagadda, R, Tedeschi, AJ, Miteu, GD, Garg, T, David, L, Lansiaux, E, Huang, H, Nansubuga, EP, Anand, A, Sikora, K, Isik, A, Debnath, S, Pramanik, S, Seth, D, Mukerjee, N, Narli, F, Sharma, R, Ghosh, A, Md Ashraf, G & Alexiou, Α 2025, Current trends of computational tools and artificial intelligence in geriatric medicine. in Essential Guide to Neurodegenerative Disorders: Mechanistic, Diagnostic and Therapeutic Advances. Elsevier, pp. 363-374. https://doi.org/10.1016/B978-0-443-15702-8.00023-3

Current trends of computational tools and artificial intelligence in geriatric medicine. / Awuah, Wireko Andrew; Ou Yong, Brian M.; Mikhailova, Tatiana et al.
Essential Guide to Neurodegenerative Disorders: Mechanistic, Diagnostic and Therapeutic Advances. Elsevier, 2025. p. 363-374.

Research output: Chapter in Book or Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Current trends of computational tools and artificial intelligence in geriatric medicine

AU - Awuah, Wireko Andrew

AU - Ou Yong, Brian M.

AU - Mikhailova, Tatiana

AU - Ng, Jyi Cheng

AU - Abdul-Rahman, Toufik

AU - Yarlagadda, Rohan

AU - Tedeschi, Alexander J.

AU - Miteu, Goshen David

AU - Garg, Tulika

AU - David, Lian

AU - Lansiaux, Edouard

AU - Huang, Helen

AU - Nansubuga, Esther Patience

AU - Anand, Ayush

AU - Sikora, Kateryna

AU - Isik, Arda

AU - Debnath, Sandip

AU - Pramanik, Sourish

AU - Seth, Dibyendu

AU - Mukerjee, Nobendu

AU - Narli, Flora

AU - Sharma, Rohit

AU - Ghosh, Arabinda

AU - Md Ashraf, Ghulam

AU - Alexiou, Αthanasios

PY - 2025/1/1

Y1 - 2025/1/1

N2 - As lifespans grow across the globe, so does the prevalence of neurodegenerative diseases among a rapidly expanding elderly demographic. Originating in the brain—the least understood organ in the human body—neurodegenerative diseases are caused by complex mechanisms that are challenging to study in a heterogeneous patient population. Machine learning, natural language processing, and other subfields of artificial intelligence have shown great promise as computational tools enabling physician-scientists to tackle these challenges on a potentially large scale. This chapter explores current applications of artificial intelligence in the classification, treatment, and management of the most common neurodegenerative diseases.

AB - As lifespans grow across the globe, so does the prevalence of neurodegenerative diseases among a rapidly expanding elderly demographic. Originating in the brain—the least understood organ in the human body—neurodegenerative diseases are caused by complex mechanisms that are challenging to study in a heterogeneous patient population. Machine learning, natural language processing, and other subfields of artificial intelligence have shown great promise as computational tools enabling physician-scientists to tackle these challenges on a potentially large scale. This chapter explores current applications of artificial intelligence in the classification, treatment, and management of the most common neurodegenerative diseases.

KW - Artificial intelligence

KW - Geriatrics

KW - Machine learning

KW - Neurodegenerative disorders

KW - Therapeutic procedure

UR - https://www.scopus.com/pages/publications/85213164057

U2 - 10.1016/B978-0-443-15702-8.00023-3

DO - 10.1016/B978-0-443-15702-8.00023-3

M3 - Chapter

AN - SCOPUS:85213164057

SN - 9780443157035

SP - 363

EP - 374

BT - Essential Guide to Neurodegenerative Disorders

PB - Elsevier

ER -

Current trends of computational tools and artificial intelligence in geriatric medicine

Abstract

UN SDGs

Keywords

Access to Document

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