2021
DOI: 10.32474/lojms.2021.05.000225
|View full text |Cite
|
Sign up to set email alerts
|

A Perspective: Use of Machine Learning Models to Predict the Risk of Multimorbidity

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
3
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
2
2

Relationship

1
3

Authors

Journals

citations
Cited by 4 publications
(3 citation statements)
references
References 37 publications
0
3
0
Order By: Relevance
“…This undercurrent of disease complexities linked to endometriosis that could lead to multimorbidity should be explored to support clinicians and healthcare organisations in future-proofing patient care [5]. In line with this, exploring machine learning as a technique in conjunction with synthetic data methods could demonstrate better predictions and offer a new solution to sample size challenges.…”
Section: Introductionmentioning
confidence: 98%
“…This undercurrent of disease complexities linked to endometriosis that could lead to multimorbidity should be explored to support clinicians and healthcare organisations in future-proofing patient care [5]. In line with this, exploring machine learning as a technique in conjunction with synthetic data methods could demonstrate better predictions and offer a new solution to sample size challenges.…”
Section: Introductionmentioning
confidence: 98%
“…Hence, multimorbidity is challenging to treat, and there remains a paucity of research available to better understand the basic science behind the complex mechanisms that could enable better diagnosis and management long-term [4]. This undercurrent of disease complexities linked to endometriosis that could lead to multimorbidity should be explored to support clinicians and healthcare organisations in futureproofing patient care [5]. In line with this, exploring machine learning as a technique in conjunction with synthetic data methods could demonstrate better predictions and offer a new solution to sample size challenges.…”
Section: Introductionmentioning
confidence: 99%
“…Patients are more vocal about having therapies that are less invasive and more tolerable with minimal side effects. Therefore, precision and personalised medicine has become more appealing to the masses [2]. To develop such befitting research requires high-quality evidence, ideally in shorter timeframes, improved analytical methods and access to existing data within electronic healthcare records (EHRs).…”
mentioning
confidence: 99%