Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne, Parkville, Victoria, Australia; College of Animal Sciences, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, Zhejiang University, Hangzhou, China.
Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne, Parkville, Victoria, Australia. Electronic address: robinbg@unimelb.edu.au.
Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
College of Animal Sciences, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, Institute of Preventive Veterinary Medicine, Zhejiang University, Hangzhou, 310058, China.
College of Mathematics and Statistics, Fujian Normal University, Fuzhou, 350007, Fujian, PR China; Fujian Key Laboratory of Mathematical Analysis and Applications, Center of Applied Mathematics (FJNU), Fuzhou, 350007, Fujian, PR China. Electronic address: zhou@fjnu.edu.cn.
Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne, Parkville, Victoria, Australia; Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Kulmbach, Germany.
Department of Veterinary Biosciences, Melbourne Veterinary School, The University of Melbourne, Parkville, Victoria, Australia. Electronic address: nyoung@unimelb.edu.au.
Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
College of Animal Sciences, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, Institute of Preventive Veterinary Medicine, Zhejiang University, Hangzhou, 310058, China.
Department of Environmental and Occupational Health and Safety, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
The recent global focus on big data in medicine has been associated with the rise of artificial intelligence (AI) in diagnosis and decision-making following recent advances in computer technology. Up ...
The widespread use of information technology in healthcare leads to extensive data collection, which can be utilised to enhance patient care and manage chronic illnesses. Our objective is to summarise...
To utilize data mining for analysis of corneal transplantations (CT) in Florida from 2005-2014, segmented by demographics, geography, and transplantation technique....
A retrospective, database study was performed utilizing data queried from the Healthcare and Cost Utilization Project using Current Procedural Terminology codes for lamellar keratoplasty (ALK), endoth...
From 2005-2014, CT (n=28,607) represented less than 1% of the total ambulatory surgeries (n=12,695,932) performed in Florida. EK volume increased while PKP and ALK volume decreased, year-over-year. St...
CT rates in Florida appear to overrepresent the female sex and underrepresent ethnic minorities, with propensities between PKP and African Americans, EK and female patients, and EK and Medicare reimbu...
We provide a brief overview of the connotation and characteristics of data mining technology in the era of big data, analyze the feasibility of data mining technology in business management from the e...
The tyrosyl-DNA phosphodiesterase 1 (TDP1) enzyme hydrolyzes the phosphodiester bond between a tyrosine residue and the 3'-phosphate of DNA in the DNA-topoisomerase I (TopI) complex, being involved in...
Image-based data mining (IBDM) is a novel voxel-based method for analyzing radiation dose responses that has been successfully applied in adult data. Because anatomic variability and side effects of i...
We tested IBDM with CT images and dose distributions collected from 167 children (aged 10 months to 20 years) who received proton radiotherapy for primary brain tumors. We used data from four referenc...
Spatial normalizations and dose comparisons were insensitive to reference selection. Normalization discrepancies were small (average contour distance < 2.5 mm, average center-of-mass deviation < 6 mm)...
IBDM is feasible for childhood late-effects research. Our findings may inform cohort selection in future studies of pediatric radiotherapy dose responses and facilitate treatment planning to reduce tr...
Censorship is the primary challenge in survival modeling, especially in human health studies. The classical methods have been limited by applications like Kaplan-Meier or restricted assumptions like t...
We proposed a two-slice temporal Bayesian network model for the survival data, introducing the survival and censorship status in each observed time as the dynamic states. A score-based algorithm learn...
The simulation study shows the superiority of DBN in bias reduction for many scenarios compared with Cox regression and Kaplan-Meier, especially in the late survival times. In the real-world data, the...
Our proposed dynamic Bayesian network model could be used as a data mining technique in the context of survival data analysis. The advantages of this approach are feature selection ability, straightfo...
Sequential pattern mining (SPM) is a major class of data mining topics with a wide range of applications. The continuity and uncertain nature of trajectory data make it distinctively different from ty...
Healthcare programs and insurance initiatives play a crucial role in ensuring that people have access to medical care. There are many benefits of healthcare insurance programs but fraud in healthcare ...
In this study, a fraud detection methodology is presented that utilizes association rule mining augmented with unsupervised learning techniques to detect healthcare insurance fraud. Dataset from the C...
Descriptive analysis shows patterns and trends in the data revealing interesting relationship among diagnosis codes, procedure codes and the physicians. The baseline anomaly detection algorithms gener...
The proposed methodology enhances healthcare insurance fraud detection by using association rule mining for pattern discovery and unsupervised classifiers for effective anomaly detection....
Water quality monitoring programs are essential planning and management tools, but they face many challenges in the developing world. The scarcity of financial and human resources and the unavailabili...
