Article
Geriatrics & Gerontology
Yurun Cai, Suzanne G. Leveille, Olga Andreeva, Ling Shi, Ping Chen, Tongjian You
Summary: This study aimed to describe fall circumstances among older adults by analyzing quantitative data and using qualitative analysis methods. The results showed that 64% of the participants experienced at least one fall during the 4-year follow-up, with more falls occurring indoors than outdoors. Common activities during the falls included walking, standing, and going down stairs, and the most commonly reported causes were slip or trip and inappropriate footwear.
JOURNALS OF GERONTOLOGY SERIES A-BIOLOGICAL SCIENCES AND MEDICAL SCIENCES
(2023)
Article
Chemistry, Analytical
Shuaijie Wang, Fabio Miranda, Yiru Wang, Rahiya Rasheed, Tanvi Bhatt
Summary: This study aimed to develop models for near-fall event detection based on accelerometry data to identify older adults at a high risk of slip-related falls. The results showed that deep learning models had higher accuracy than machine learning models in classifying loss of balance (LOB) and no loss of balance (NLOB) outcomes. The Inception model showed the highest classification accuracy and area under the receiver operating characteristic curve (AUC), indicating its effectiveness in near-fall (LOB) detection.
Article
Public, Environmental & Occupational Health
Elke Lathouwers, Arnau Dillen, Maria Alejandra Diaz, Bruno Tassignon, Jo Verschueren, Dominique Verte, Nico De Witte, Kevin De Pauw
Summary: This study identified multiple risk factors associated with falling in older adults, including biological, behavioral, environmental, and socio-economic factors. The findings suggest that maintaining a healthy lifestyle and a satisfactory living situation can help reduce the risk of falling.
Article
Computer Science, Interdisciplinary Applications
Jing Cao, Juncheng Gao, Hima Nikafshan Rad, Ahmed Salih Mohammed, Mahdi Hasanipanah, Jian Zhou
Summary: The study aims to propose an efficient machine learning model to predict engineering properties of rock, with the XGBoost-FA model showing superior accuracy and generalization compared to other models.
ENGINEERING WITH COMPUTERS
(2022)
Article
Biotechnology & Applied Microbiology
Kangqi Lv, Dayang Chen, Dan Xiong, Huamei Tang, Tong Ou, Lijuan Kan, Xiuming Zhang
Summary: This study developed a functional deleteriousness-based model of CNV (dbCNV) to predict the pathogenicity of CNVs and provide a deeper understanding of the pathogenic mechanism.
Article
Public, Environmental & Occupational Health
Kazuya Fujihara, Mayuko Yamada Harada, Chika Horikawa, Midori Iwanaga, Hirofumi Tanaka, Hitoshi Nomura, Yasuharu Sui, Kyouhei Tanabe, Takaho Yamada, Satoru Kodama, Kiminori Kato, Hirohito Sone
Summary: This study developed a machine learning model to predict weight change over three years. It found that lifestyle had a significant impact on weight in individuals with high BMI and in young people. The model showed comparable accuracy to multiple regression, suggesting its potential for personalized weight management.
FRONTIERS IN PUBLIC HEALTH
(2023)
Article
Chemistry, Analytical
Shuaijie Wang, Tuan Khang Nguyen, Tanvi Bhatt
Summary: This study aimed to develop prediction models for trip-related fall risk using machine-learning approaches. The results showed that the model with 17 features had the highest accuracy and an AUC of 0.96, while the model with 8 features had a comparable AUC of 0.93 with fewer features.
Article
Medicine, General & Internal
Keitaro Makino, Sangyoon Lee, Seongryu Bae, Ippei Chiba, Kenji Harada, Osamu Katayama, Kouki Tomida, Masanori Morikawa, Hiroyuki Shimada
Summary: The study developed a simplified decision-tree algorithm for fall prediction with easily measurable predictors, outperforming a logistic regression model. The algorithm includes common and easily measurable fall predictors that can be implemented in clinical practice for risk stratification.
JOURNAL OF CLINICAL MEDICINE
(2021)
Article
Geriatrics & Gerontology
Krystal M. Kirby, Sreekrishna Pillai, Robert M. Brouillette, Jeffrey N. Keller, Alyssa N. De Vito, John P. Bernstein, Arend W. A. Van Gemmert, Owen T. Carmichael
Summary: This study found that brain functioning, motor task, and cognitive task performance in challenging dual-task conditions all contribute to the risk of falling among older adults. Multiple factors are involved in determining fall characteristics.
FRONTIERS IN AGING NEUROSCIENCE
(2021)
Article
Parasitology
Honglin Jiang, Weicheng Deng, Jie Zhou, Guanghui Ren, Xinting Cai, Shengming Li, Benjiao Hu, Chunlin Li, Ying Shi, Na Zhang, Yingyan Zheng, Yue Chen, Qingwu Jiang, Yibiao Zhou
Summary: The study utilized machine learning algorithms to construct a 1-year prognostic model for advanced schistosomiasis and identified important predictors, with XGBoost algorithm showing the best predictive performance. Important predictors identified include ascitic fluid volume, HB, TB, ALB, and PT.
INTERNATIONAL JOURNAL FOR PARASITOLOGY
(2021)
Article
Computer Science, Theory & Methods
Chalachew Muluken Liyew, Haileyesus Amsaya Melese
Summary: Predicting daily rainfall using data mining and machine learning techniques is crucial for improving agricultural productivity and securing food and water supply. The study focuses on identifying relevant atmospheric features and predicting rainfall intensity, with Extreme Gradient Boosting machine learning algorithm outperforming others in performance evaluation.
JOURNAL OF BIG DATA
(2021)
Article
Environmental Sciences
Jungsu Park, Woo Hyoung Lee, Keug Tae Kim, Cheol Young Park, Sanghun Lee, Tae-Young Heo
Summary: This study developed an XGBoost ensemble machine learning model to predict chlorophyll-a (Chl-a) concentration and explored the effect of input variable selection on model performance. Using explainable artificial intelligence (XAI) algorithms, the study provided interpretable analyses of model predictions. The results showed that selecting input variables based on the Shapley value (SHAP) algorithm improved model stability and helped reduce the cost of water quality analysis.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Medicine, General & Internal
Muhammad Shahzad, Muhammad Atif Tahir, Musaed Alhussein, Ansharah Mobin, Rauf Ahmed Shams Malick, Muhammad Shahid Anwar
Summary: With the advent of high-throughput screening, in silico-based drug response analysis has opened up many research avenues in personalized medicine. This study proposes a framework called NeuPD to validate the potential anti-cancer drugs against a panel of cancer cell lines in publicly available datasets. The results show that NeuPD outperforms existing approaches with an RMSE of 0.490 and R-2 of 0.929.
Article
Geriatrics & Gerontology
Wendan Li, Xiujun Chen, Jintao Zhang, Jianjun Lu, Chencheng Zhang, Hongmin Bai, Junchao Liang, Jiajia Wang, Hanqiang Du, Gaici Xue, Yun Ling, Kang Ren, Weishen Zou, Cheng Chen, Mengyan Li, Zhonglue Chen, Haiqiang Zou
Summary: This paper presents a method based on mobile phone video to achieve remote FOG recognition in PD patients, which is convenient with high recognition accuracy and can be used to rapidly evaluate FOG in the home environment and remotely manage FOG-PD, or screen patients in large-scale communities.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Computer Science, Artificial Intelligence
Achanta Sampath Dakshina Murthy, Thangavel Karthikeyan, R. Vinoth Kanna
Summary: Technology development and digital techniques open up opportunities for developing automatic systems, with gait energy images used for early fall prediction in a deep learning approach. The proposed DCNN model achieves high classification accuracy and prediction ratio, outperforming traditional methods like ResNet 50 and CNN for gait analysis.
Article
Environmental Sciences
Bohyun Kim, Changhong Youm, Hwayoung Park, Myeounggon Lee, Byungjoo Noh
Summary: This study focused on analyzing age- and sex-related spatiotemporal variability characteristics in elderly individuals based on gait speed variation measured during treadmill walking. Results showed that different age groups and sexes could be distinguished based on certain gait characteristics at different speed conditions, indicating the value of gait variability in determining variations in elderly individuals' gait characteristics.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Multidisciplinary Sciences
Myeounggon Lee, Changhong Youm, Byungjoo Noh, Hwayoung Park
Summary: This study aimed to investigate the association between fundamental movement patterns and gait ability in young adults based on a cut-off point, with results showing that the low TFMS group exhibited slower and shortened walking patterns and worsen gait variability compared to the high TFMS group. The coefficient of variance for specific gait parameters was found to be a classifier between the two groups, indicating that lower TFMS is associated with a decline in gait ability and may require intervention to prevent future injury and improve motor function.
Article
Environmental Sciences
Matthew Gage, Kevin Phillips, Byungjoo Noh, Tejin Yoon
Summary: Various choline-based multi-ingredient supplementations show limited research in the market. The study aimed to investigate the acute effect of a CMS on physical performance, with findings showing that CMS can improve explosive strength by delaying fatigue onset.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Environmental Sciences
Byungjoo Noh, Hyemin Yoon, Changhong Youm, Sangjin Kim, Myeounggon Lee, Hwayoung Park, Bohyun Kim, Hyejin Choi, Yoonjae Noh
Summary: This study successfully identified important features for predicting a potential decline in global cognitive function in older adults using machine learning techniques, providing new insights for early detection and prevention of cognitive function decline in older adults.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Environmental Sciences
Myeounggon Lee, Yoonjae Noh, Changhong Youm, Sangjin Kim, Hwayoung Park, Byungjoo Noh, Bohyun Kim, Hyejin Choi, Hyemin Yoon
Summary: This study investigated multiple prediction models to determine the health-related quality of life in elderly adults in South Korea. The research focused on physical and mental components, analyzing demographic factors, questionnaires, gait ability, physical fitness, and health surveys. The study found that factors such as functional endurance, muscle strength, stress level, and falling risk play important roles in determining HRQoL in elderly adults.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Environmental Sciences
Kwang-Jin Lee, Byungjoo Noh, Keun-Ok An
Summary: This study found that synchronous online physical education classes have a positive impact on adolescents' muscle mass, joint strength, and balance, indicating that appropriate online physical education courses can effectively improve adolescents' physical fitness levels.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Chemistry, Multidisciplinary
Yeoungju Woo, Seoyeong Ko, Sohyun Ahn, Hang Thi Phuong Nguyen, Choonsung Shin, Hieyong Jeong, Byungjoo Noh, Myeounggon Lee, Hwayoung Park, Changhong Youm
Summary: Senior citizens have a higher risk of diabetes-related complications but it is challenging to diagnose and manage elderly diabetics due to lack of clear symptoms. This study classified differences in gait and physical fitness characteristics to propose a non-invasive training system. Abnormalities in gait and physical fitness related to balance ability and walking speed were identified, and a training system using a single RGB camera was developed to correct exercise posture and speed in real-time, with potential risks and errors highlighted for future improvements.
APPLIED SCIENCES-BASEL
(2021)
Article
Nutrition & Dietetics
Eun Kyoung Goh, Oh Yoen Kim, So Ra Yoon, Hyo Jeong Jeon
Summary: This study investigates the timing and determinants of adiposity rebound (AR) in children using large-scale nationwide data. The study finds that the AR usually occurs before the age of 5, and the risk of early AR (EAR) is influenced by gender and time periods. Adequate breastfeeding, proper diet, and reduced sugar-sweetened beverage consumption are important for reducing EAR.
Article
Pediatrics
Eun-Kyoung Goh, Hyo Jeong Jeon
Summary: Behavioral problems in children can be better understood by tracking the changes in relationships between different symptoms. This study used Gaussian graphical network analysis to examine the interactions and centrality in the Korean Child Behavior Checklist. The findings highlight the importance of considering anxiety/depression and posttraumatic stress problems in preschool children to support their adaptation in school.
Article
Environmental Sciences
Bohyun Kim, Changhong Youm, Hwayoung Park, Myeounggon Lee, Hyejin Choi
Summary: Aging-related muscle atrophy is associated with decreased muscle mass, muscle strength, and muscle function, which may lead to impaired motor control, balance, and gait pattern. This study found that using different speed-based gait variables can be useful for evaluating muscle mass, muscle strength, and muscle function in older women.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Environmental Sciences
Hyejin Choi, Changhong Youm, Hwayoung Park, Bohyun Kim, Sang-Myung Cheon, Myeounggon Lee
Summary: This study investigated the turning characteristics that distinguish freezers among people with PD and analyzed the association between NFOGQ scores and gait characteristics according to turning direction. The results revealed that the outer ankle range of motion could distinguish freezers and non-freezers, and higher NFOGQ scores were associated with specific gait characteristics. Assessing maximum speed and turning direction is useful for accurately defining freezers.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)