Wearable sensor systems for fall risk assessment: A review

S Subramaniam, AI Faisal, MJ Deen - Frontiers in digital health, 2022 - frontiersin.org
Fall risk assessment and fall detection are crucial for the prevention of adverse and long-
term health outcomes. Wearable sensor systems have been used to assess fall risk and …

Fall prediction using behavioural modelling from sensor data in smart homes

G Forbes, S Massie, S Craw - Artificial Intelligence Review, 2020 - Springer
The number of methods for identifying potential fall risk is growing as the rate of elderly
fallers continues to rise in the UK. Assessments for identifying risk of falling are usually …

A dynamic Bayesian network based approach to safety decision support in tunnel construction

X Wu, H Liu, L Zhang, MJ Skibniewski, Q Deng… - Reliability Engineering & …, 2015 - Elsevier
This paper presents a systemic decision approach with step-by-step procedures based on
dynamic Bayesian network (DBN), aiming to provide guidelines for dynamic safety analysis …

Motion tracking and gait feature estimation for recognising Parkinson's disease using MS Kinect

O Ťupa, A Procházka, O Vyšata, M Schätz… - Biomedical engineering …, 2015 - Springer
Background Analysis of gait features provides important information during the treatment of
neurological disorders, including Parkinson's disease. It is also used to observe the effects …

Using sequential decision making to improve lung cancer screening performance

P Petousis, A Winter, W Speier, DR Aberle, W Hsu… - Ieee …, 2019 - ieeexplore.ieee.org
Globally, lung cancer is responsible for nearly one in five cancer deaths. The National Lung
Screening Trial (NLST) demonstrated the efficacy of low-dose computed tomography …

Estimating the chance of success in IVF treatment using a ranking algorithm

HA Güvenir, G Misirli, S Dilbaz, O Ozdegirmenci… - Medical & biological …, 2015 - Springer
In medicine, estimating the chance of success for treatment is important in deciding whether
to begin the treatment or not. This paper focuses on the domain of in vitro fertilization (IVF) …

Comparing machine learning methods to improve fall risk detection in elderly with osteoporosis from balance data

G Cuaya-Simbro, AI Perez-Sanpablo… - Journal of healthcare …, 2021 - Wiley Online Library
Falls are a multifactorial cause of injuries for older people. Subjects with osteoporosis are
particularly vulnerable to falls. We study the performance of different computational methods …

Prediction of lung cancer incidence on the low-dose computed tomography arm of the National Lung Screening Trial: A dynamic Bayesian network

P Petousis, SX Han, D Aberle, AAT Bui - Artificial intelligence in medicine, 2016 - Elsevier
Introduction Identifying high-risk lung cancer individuals at an early disease stage is the
most effective way of improving survival. The landmark National Lung Screening Trial …

Water point failure in sub-Saharan Africa: The value of a systems thinking approach

ES Liddle, R Fenner - Waterlines, 2017 - JSTOR
Thousands of water points have been installed across sub-Saharan Africa over the past four
decades; however, a number have been found to be dry/low-yielding, unsafe for human …

A Quantitative Analysis of Decision-Making Risk Factors for Mega Infrastructure Projects in China

J Wang, L Luo, R Sa, W Zhou, Z Yu - Sustainability, 2023 - mdpi.com
The “trillion-dollar era” of megaprojects has increased the demand for the scope of mega
infrastructure. To address the requirement for high-quality “investment, construction, and …