Article
Health Care Sciences & Services
Toshiro Tango
Summary: Spatial scan statistics, including both circular and non-circular methods, are widely used for disease cluster detection. Different methods have their own advantages and limitations, with the aim of accurately identifying disease clusters of interest.
STATISTICAL METHODS IN MEDICAL RESEARCH
(2021)
Article
Psychiatry
Martin Brynge, Hugo Sjoqvist, Renee M. Gardner, Brian K. Lee, Christina Dalman, Hakan Karlsson
Summary: Maternal infections during pregnancy are associated with autism and intellectual disability in children. However, the association with autism does not seem to be causal, but is more likely explained by factors shared between family members such as genetic variation or aspects of the shared environment. In contrast, the association with intellectual disability may involve causal effects of maternal infections. Specific but rare infections or infections not requiring health care contact may also play a role in autism or intellectual disability.
Article
Geosciences, Multidisciplinary
Adrian Baddeley, Tilman M. Davies, Martin L. Hazelton, Suman Rakshit, Rolf Turner
Summary: Existing methods for fitting Neyman-Scott cluster process models often fail due to fundamental flaws in the model structure. We propose remedies for these problems and suggest derived parameters to improve the understanding of the fitted model.
SPATIAL STATISTICS
(2022)
Article
Mathematics
Mohammad Meysami, Joshua P. French, Ettie M. Lipner
Summary: The detection of disease clusters in spatial data analysis is important in public health. While the circular scan method is commonly used, accurately identifying non-circular (irregular) clusters remains challenging. We propose a method that combines the strengths of the flexible and elliptic scan methods to accurately detect irregularly shaped clusters.
Article
Environmental Sciences
Lauren M. Andersen, Stella R. Harden, Margaret M. Sugg, Jennifer D. Runkle, Taylor E. Lundquist
Summary: This study aimed to understand the spatial determinants of COVID-19 in counties across the U.S. by comparing socioeconomic variables with case and death data. Findings indicated that age, disability, language, race, occupation, and urban status were associated with community-level vulnerability.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Mathematical & Computational Biology
Joseph Boyle, Mary H. Ward, Stella Koutros, Margaret R. Karagas, Molly Schwenn, Debra Silverman, David C. Wheeler
Summary: Health outcomes are influenced by various environmental factors. It is important to estimate cumulative spatial risk for diseases considering participants' multiple residential locations and other risk factors. In this study, a Bayesian model called LRK-MMM is proposed to estimate cumulative spatial risk at the point level, incorporating multiple membership model and low-rank kriging. The model shows improved spatial sensitivity and power to detect regions of elevated risk compared to existing methods. The model is applied to real case-control data to estimate cumulative spatial risk while adjusting for multiple covariates.
STATISTICS IN MEDICINE
(2022)
Article
Biology
Zhifa Shen, Bowen Liu, Biting Wu, Hongyin Zhou, Xiangyun Wang, Jinling Cao, Min Jiang, Yingying Zhou, Feixia Guo, Chang Xue, Zai-Sheng Wu
Summary: The study proposes a mechanism for the metastasis of hepatocellular carcinoma (HCC) cells by regulating the localization and translation of the STAT3 oncogene through fragile X mental retardation protein (FMRP). Knockdown of FMRP suppresses HCC metastasis effectively.
COMMUNICATIONS BIOLOGY
(2021)
Editorial Material
Medicine, General & Internal
Eli Y. Adashi, Daniel P. O'Mahony, I. Glenn Cohen
Summary: This Viewpoint examines the crisis of maternal mortality in the US, the necessity of extending Medicaid coverage postpartum, and the ongoing challenges related to maternal health across the country.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
(2023)
Article
Public, Environmental & Occupational Health
Honghua Lin, Rui Zhang, Zheyuan Wu, Minjuan Li, Jiamei Wu, Xin Shen, Chongguang Yang
Summary: A study conducted in Shanghai found that internal migrants play a significant role in the spatial distribution and transmission of tuberculosis. The notification rate of TB among migrants was higher than among residents. Risk factors for increased TB disease at the county level included the presence of industrial parks and migrants. These findings highlight the importance of targeted tuberculosis control strategies for the mobile population in urban China.
FRONTIERS IN PUBLIC HEALTH
(2023)
Article
Economics
Melanie Guldi, Sarah Hamersma
Summary: Prior research has focused on the short-term and long-term effects of Medicaid eligibility expansions on birth outcomes and adult outcomes. This study examines the early childhood effects using data from the National Maternal and Infant Health Survey. The findings suggest that these expansions lead to earlier prenatal care, modest improvements in birthweight and gestational age, and reduced levels of maternal depression, which ultimately contribute to the longer-term improvements in child developmental scores.
JOURNAL OF HEALTH ECONOMICS
(2023)
Article
Biology
Quan Liu, Mincheng Cai, Dujuan Liu, Simeng Ma, Qianhong Zhang, Zhongchun Liu, Jun Yang
Summary: A two stream Non-Local CNN-LSTM network has been proposed for the preliminary screening of mental retardation, showing better performance than other prevalent deep learning methods. The model has potential value for clinical diagnosis and screening.
COMPUTERS IN BIOLOGY AND MEDICINE
(2022)
Article
Biochemistry & Molecular Biology
Min-Xin Luo, Hsin-Pei Lu, Bing-Hong Huang, Chia-Lung Huang, Yu-Feng Hsu, Pei-Chun Liao
Summary: The study revealed that the divergence between the two subspecies of the butterfly Parantica sita occurred around 23.1 kya, influenced primarily by winter precipitation and annual temperature range. While there was evidence of gene flow between the insular and continental subspecies, long-term precipitation patterns caused divergence between them.
Article
Computer Science, Artificial Intelligence
Arwinder Dhillon, Ashima Singh, Vinod Kumar Bhalla
Summary: This research proposes a framework called BioSurv for identifying cancer biomarkers and predicting cancer survival using machine learning and deep learning techniques. Multi-omics data from breast cancer and lung adenocarcinoma are analyzed, and statistical tests and an optimization algorithm are employed for feature selection. Thirteen BRCA and fifteen LUAD poor prognostic markers are identified, and a Bayesian optimized deep neural network achieves high accuracy in cancer survival prediction for both types of cancer.
APPLIED SOFT COMPUTING
(2023)
Article
Surgery
Devan Stahl
Summary: New evidence confirms that categorical exclusions and denials based on the need for support systems are unethical and discriminatory when considering individuals with intellectual and developmental disabilities.
Article
Computer Science, Interdisciplinary Applications
Joshua P. French, Mohammad Meysami, Lauren M. Hall, Nicholas E. Weaver, Minh C. Nguyen, Lee Panter
Summary: This study describes several extensions of the spatial scan method and compares their performance using 126 benchmark datasets. The comprehensive nature of the study allows for reliable conclusions and concrete recommendations for detecting disease clusters.
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
(2022)