Article
Computer Science, Software Engineering
Gleb Tkachev, Steffen Frey, Thomas Ertl
Summary: The proposed machine learning approach detects and visualizes complex behavior in spatiotemporal volumes by training models to predict future data values and evaluating prediction errors; Aggregating prediction errors and visualizing them highlights regions of interesting behavior; Applicable to datasets from various domains, meaningful results are produced with minimal assumptions.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2021)
Article
Engineering, Civil
Jie Zhao, Chao Chen, Chengwu Liao, Hongyu Huang, Jie Ma, Huayan Pu, Jun Luo, Tao Zhu, Shilong Wang
Summary: Accurate traffic prediction is crucial in Intelligent Transportation Systems, and a novel Dual Graph Gated Recurrent Neural Network (DG(2)RNN) is proposed to model various dependencies and provide flexible predictions for future traffic flow. The model outperforms state-of-the-arts in real-world traffic datasets, showing stable performance for flexible prediction with varying horizons.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Mechanics
Sudeepta Mondal, Soumalya Sarkar
Summary: Data-driven prediction of spatiotemporal fields in fluid flow problems has become increasingly important. However, the accuracy of prevalent approaches is often affected by the scarcity of data, especially when generating high-fidelity data is expensive. This article proposes a novel multi-fidelity spatiotemporal modeling approach to reduce the overhead of high-fidelity simulations and improve the accuracy of predictions.
Article
Mathematics
Francisco Javier Diez, Manuel Arias, Jorge Perez-Martin, Manuel Luque
Summary: OpenMarkov is an open-source software tool designed for probabilistic graphical models, primarily in medicine but also used in other fields and education in over 30 countries. This paper explains how OpenMarkov can be used as a pedagogical tool to teach the main concepts of Bayesian networks and influence diagrams, as well as various inference algorithms.
Article
Geochemistry & Geophysics
Pu Wang, Yi-An Cui, Xingzhong Du
Summary: Seismic inversion is an effective method for investigating lithology and fluid in hydrocarbon-bearing reservoirs. Probabilistic seismic prediction, along with an improved prior considering p-norm and total variation constraints, enhances the accuracy of predictions by updating the probability density function and preserving boundaries while highlighting sparsity.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Computer Science, Information Systems
Hyeonseok Lee, Sungchan Kim
Summary: The novel method SSPNet improves visual tracking accuracy by predicting the spatiotemporal features of the target, addressing limitations of traditional methods, particularly excelling in challenging sequences.
INFORMATION SCIENCES
(2021)
Article
Geochemistry & Geophysics
Matthias Scheiter, Andrew Valentine, Malcolm Sambridge
Summary: This paper discusses the use of generative models to overcome challenges in the application of Monte Carlo methods in geophysics. Generative models can learn probability distributions from given samples and generate new samples, which allows for compression of data and faster computation. The use of generative models opens up new possibilities for improving storage and communication of results, enhancing numerical integration calculation, and assessing the convergence of Monte Carlo procedures.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2022)
Article
Multidisciplinary Sciences
Chawarat Rotejanaprasert, Saranath Lawpoolsri, Patiwat Sa-angchai, Amnat Khamsiriwatchara, Chantana Padungtod, Rungrawee Tipmontree, Lynette Menezes, Jetsumon Sattabongkot, Liwang Cui, Jaranit Kaewkungwal
Summary: Thailand aims to eliminate malaria by 2024 in its national strategic plan. A study used the Thailand malaria surveillance database to develop spatiotemporal models, analyzing past patterns and predicting malaria incidences at the provincial level. The study results showed different predictions for Plasmodium falciparum and Plasmodium vivax, suggesting the possibility of eliminating P. falciparum by 2024 but not P. vivax. Innovative approaches are needed for P. vivax-specific control and elimination plans to make Thailand malaria-free.
SCIENTIFIC REPORTS
(2023)
Article
Geosciences, Multidisciplinary
Hwasoo Shin, Marco A. R. Ferreira
Summary: We propose a novel class of dynamic factor models for spatiotemporal areal data, achieving dimension reduction by assuming that the process can be represented by a few latent factors. Each column of the factor loading matrix follows an intrinsic conditional autoregressive process to account for spatial dependence. We present two case studies, demonstrating the identifiability of our models and the utility of the framework in analyzing the drug overdose epidemic in the United States.
SPATIAL STATISTICS
(2023)
Article
Engineering, Civil
Yuan Li, Zhiyong Wu, Hai He, Quan J. Wang, Huating Xu, Guihua Lu
Summary: Post-processing of sub-seasonal precipitation forecasts from ECMWF using Bayesian joint probability method enhances forecast skills, especially at larger spatial and longer temporal scales. Although forecast skills decrease with lead time, the uncertainty spread of the post-processed forecasts remains reliable across all lead times and spatiotemporal scales.
JOURNAL OF HYDROLOGY
(2021)
Article
Multidisciplinary Sciences
Yuguang Chen, Jintao Huang, Hongbin Xu, Jincheng Guo, Linyong Su
Summary: A dynamic spatiotemporal graph attention network traffic flow prediction model based on the attention mechanism was proposed to improve the accuracy of traffic flow prediction under the influence of nearby time traffic flow disturbance. Experimental results on public data sets demonstrate the superiority of the proposed model compared to six baseline models.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Information Systems
Yue Deng, Rixing He, Yang Liu
Summary: In this study, the introduction of spatiotemporal lag variables effectively mitigated the spatiotemporal dependence in crime data. Four machine learning methods were used to verify the feasibility of this approach. The results showed that incorporating spatiotemporal lag variables significantly improved the prediction accuracy of machine learning models, nonlinear tree-based models outperformed linear models in predicting crime, and interpretable machine learning models revealed the unique contribution of each variable. These findings enhance our understanding of the mechanism of crime occurrence and inform the development of crime prevention strategies.
INFORMATION SCIENCES
(2023)
Article
History & Philosophy Of Science
Christian Dahlman, Eivind Kolflaath
Summary: This paper compares causal models and reason models in the construction of Bayesian networks for legal evidence. It explores the differences between the two models and highlights the advantages of reason models, which are better aligned with the philosophy of Bayesian inference and more suited for measuring the combined support of evidence.
Article
Geochemistry & Geophysics
Wenjing Sang, Sanyi Yuan, Hongwei Han, Haojie Liu, Yue Yu
Summary: Porosity characterization is important for seismic inversion and hydrocarbon prediction. We proposed a SSL-based network (SSLBN) for reservoir porosity prediction, and compared it with a SL-based network (SLBN). The SSLBN, trained with seismic-to-well pairs and unlabelled seismic logs, learns the physical process from observed seismic log to inverted porosity and generated seismic log. Results show that the SSLBN outperforms the SLBN in scenes of RTM imaged seismic data and biased porosity labels, improving estimation accuracy and reducing prediction uncertainty.
GEOPHYSICAL JOURNAL INTERNATIONAL
(2023)
Article
Biodiversity Conservation
Joshua S. North, Erin M. Schliep, Gretchen J. A. Hansen, Holly Kundel, Christopher A. Custer, Paul Mclaughlin, Tyler Wagner
Summary: Estimating relative abundance is crucial for conservation and management efforts in freshwater fisheries. This study developed a joint species distribution model (JSDM) that accounts for varying sampling conditions and captures seasonal variation in species life history. The findings show that not accounting for these variations can bias the inference of relative abundance, limiting our ability to detect responses to management interventions and environmental change. The model can be applied to other systems where catchability may vary as a function of space, time, and species.
JOURNAL OF APPLIED ECOLOGY
(2023)
Article
Infectious Diseases
Siriyaporn Khunthason, Jaranit Kaewkungwal, Wirichada Pan-Ngum, Chusak Okascharoen, Tawatchai Apidechkul, Saranath Lawpoolsri
JOURNAL OF INFECTION IN DEVELOPING COUNTRIES
(2020)
Article
Immunology
Chamnan Pinna, Jaranit Kaewkungwal, Weerawan Hattasingh, Witaya Swaddiwudhipong, Rakdaw Methakulchart, Aree Moungsookjareoun, Saranath Lawpoolsri
Article
Infectious Diseases
Shoichi Shimizu, Sadudee Chotirat, Nichakan Dokkulab, Isarachai Hongchad, Kessuda Khowsroy, Kirakorn Kiattibutr, Nongnuj Maneechai, Khajohnpong Manopwisedjaroen, Pattamaporn Petchvijit, Kanit Phumchuea, Nattawan Rachaphaew, Piyarat Sripoorote, Chayanut Suansomjit, Waraporn Thongyod, Amnat Khamsiriwatchara, Saranath Lawpoolsri, Borimas Hanboonkunupakarn, Jetsumon Sattabongkot, Wang Nguitragool
INTERNATIONAL JOURNAL OF INFECTIOUS DISEASES
(2020)
Article
Infectious Diseases
Yuling Li, Yubing Hu, Yan Zhao, Qinghui Wang, Huguette Gaelle Ngassa Mbenda, Veerayuth Kittichai, Saranath Lawpoolsri, Jetsumon Sattabongkot, Lynette Menezes, Xiaoming Liu, Liwang Cui, Yaming Cao
Article
Environmental Sciences
Chalermkhwan Kuntawee, Kraichat Tantrakarnapa, Yanin Limpanont, Saranath Lawpoolsri, Athit Phetrak, Rachaneekorn Mingkhwan, Suwalee Worakhunpiset
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2020)
Article
Environmental Sciences
Kinley Wangdi, Kinley Penjor, Tobgyal, Saranath Lawpoolsri, Ric N. Price, Peter W. Gething, Darren J. Gray, Elivelton Da Silva Fonseca, Archie C. A. Clements
Summary: By conducting spatial and space-time cluster analysis, Bhutan has seen a significant decrease in malaria cases from 2010 to 2019. The study identified high-risk areas and periods for malaria transmission, aiding in the development of targeted prevention strategies for Bhutan to achieve its goal of malaria elimination by 2022.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2021)
Article
Environmental Sciences
Pittaya Piroonamornpun, Panita Looareesuwan, Viravarn Luvira, Nantawan Wongchidwon, Piyanan Pakdeewut, Saranath Lawpoolsri, Benjaluck Phonrat
Summary: Dengue infection is a significant public health problem in Thailand, but there is a lack of knowledge and understanding among the adult population. The study found that many patients resorted to self-medication during the early stages of the illness, and there were differences in the time taken to seek medical care. Furthermore, there is still a widespread lack of understanding and misperceptions regarding dengue-related knowledge.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2022)
Article
Biology
Kawin Chinpong, Kaewklao Thavornwattana, Peerawich Armatrmontree, Peerut Chienwichai, Saranath Lawpoolsri, Udomsak Silachamroon, Richard J. Maude, Chawarat Rotejanaprasert
Summary: This retrospective study examined the spatiotemporal patterns of tuberculosis (TB) incidence in Thailand from 2011 to 2020. The findings showed an overall decreasing trend in TB incidence, with clusters of high rates along the border of neighboring countries. Understanding the spatial and temporal distribution of TB is crucial for effective control programs and resource allocation.
Article
Infectious Diseases
Viravarn Luvira, Charin Thawornkuno, Saranath Lawpoolsri, Narin Thippornchai, Chatnapa Duangdee, Thundon Ngamprasertchai, Pornsawan Leaungwutiwong
Summary: Dengue infection is a global public health problem, especially in tropical areas. Lack of sensitive diagnostic methods in the early phase of the illness is a challenge in clinical practices. This study analyzed 86 sera of acute febrile patients to study the diagnostic performance of dengue diagnostics. The results showed that dengue NS1 detection by ELISA had the highest sensitivity, while the combination of NS1 and IgM detection in RDT yielded the best results.
TROPICAL MEDICINE AND INFECTIOUS DISEASE
(2023)
Article
Infectious Diseases
Manasvin Onwan, Wasin Matsee, Saranath Lawpoolsri, Phimphan Pisutsan, Tanaya Siripoon, Suda Punrin, Watcharapong Piyaphanee
Summary: The study investigates the acceptance of COVID-19 vaccine among international travelers and identifies the influencing factors. The findings show a high acceptance rate among the travelers, with factors such as vaccine efficacy, protective duration, infection risk, and travel plan playing a significant role.
TROPICAL MEDICINE AND INFECTIOUS DISEASE
(2022)
Article
Health Care Sciences & Services
Sirasuda Sommanus, Raweerat Sitcharungsi, Saranath Lawpoolsri
Summary: Caregiver knowledge and management ability can improve asthma control and quality of life among children with asthma. Attending an educational camp can increase caregivers' asthma knowledge and management ability. However, there was no significant difference in quality of life between camp attendees and non-attendees.
Review
Infectious Diseases
Ashley Siribhadra, Thundon Ngamprasertchai, Pinyo Rattanaumpawan, Saranath Lawpoolsri, Viravarn Luvira, Punnee Pitisuttithum
Summary: Acute undifferentiated febrile illness (AUFI) is a common symptom of various tropical and infectious diseases. Viral infection is the most common cause, making antibiotics unnecessary. Effective treatment for dengue and malaria is important. Antimicrobial stewardship (AMS) is an effective strategy to control unnecessary antibiotic use and antimicrobial resistance (AMR) prevention.
TROPICAL MEDICINE AND INFECTIOUS DISEASE
(2022)
Article
Infectious Diseases
Krit Madsalae, Thundon Ngamprasertchai, Saranath Lawpoolsri, Rujipas Sirijatuphat, Winai Ratanasuwan, Watcharapong Piyaphanee, Punnee Pitisuttithum
Summary: This study highlights the importance of adherence to antiretroviral therapy (ART) and health problems among travellers living with HIV (TLWHIV) during their travels. The findings suggest that international destination plays a significant role in medication adherence and that healthcare providers should provide pretravel consultation to enhance adherence and minimize health risks.
TROPICAL MEDICINE AND INFECTIOUS DISEASE
(2022)
Article
Medical Informatics
Win Min Thit, Sai Wai Yan Myint Thu, Jaranit Kaewkungwal, Ngamphol Soonthornworasiri, Nawanan Theera-Ampornpunt, Boonchai Kijsanayotin, Saranath Lawpoolsri, Sid Naing, Wirichada Pan-ngum
HEALTHCARE INFORMATICS RESEARCH
(2020)
Article
Public, Environmental & Occupational Health
Khuong Cao Ba, Jaranit Kaewkungwal, Oranut Pacheun, Uyen Nguyen Thi To, Saranath Lawpoolsri
ENVIRONMENTAL HEALTH INSIGHTS
(2020)
Article
Computer Science, Artificial Intelligence
Qianghua Liu, Yu Tian, Tianshu Zhou, Kewei Lyu, Ran Xin, Yong Shang, Ying Liu, Jingjing Ren, Jingsong Li
Summary: This study proposes a few-shot disease diagnosis decision making model based on a model-agnostic meta-learning algorithm (FSDD-MAML). It significantly improves the diagnostic process in primary health care and helps general practitioners diagnose few-shot diseases more accurately.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)
Article
Computer Science, Artificial Intelligence
Balazs Borsos, Corinne G. Allaart, Aart van Halteren
Summary: The study demonstrates the feasibility of predicting functional outcomes for ischemic stroke patients and the usability of multimodal deep learning architectures for this purpose.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)
Article
Computer Science, Artificial Intelligence
Abdelmoniem Helmy, Radwa Nassar, Nagy Ramdan
Summary: This study utilizes machine learning models to detect depression symptoms in Arabic and English texts, and provides manually and automatically annotated tweet corpora. The study also develops an application that can detect tweets with depression symptoms and predict depression trends.
ARTIFICIAL INTELLIGENCE IN MEDICINE
(2024)