25 research outputs found
Pan-cancer analysis of the prevalence and associated factors of lung metastasis and the construction of the lung metastatic classification system
This study first presents an analysis of the prevalence and associated factors of the lung metastasis (LM) database and then uses this analysis to construct an LM classification system. Using cancer patient data gathered from the surveillance, epidemiology, and end results (SEER) database, this study shows that the prevalence of LM is not consistent among different cancers; that is, the prevalence of LM ranges from 0.0013 [brain; 95% confidence interval (95% CI); 0.0010–0.0018] to 0.234 (“other digestive organs”; 95% CI; 0.221–0.249). This study finds that advanced age, poor grade, higher tumor or node stage, and metastases including bone, brain, and liver are positively related to LM occurrence, while female gender, income, marital status, and insured status are negatively related. Then, this study generates four categories from 58 cancer types based on prevalence and influence factors and satisfactorily validates these. This classification system reflects the LM risk of different cancers. It can guide individualized treatment and the management of these synchronous metastatic cancer patients and help clinicians better distribute medical resources
1st Workshop on Maritime Computer Vision (MaCVi) 2023: Challenge Results
The 1 Workshop on Maritime Computer Vision (MaCVi) 2023 focused
on maritime computer vision for Unmanned Aerial Vehicles (UAV) and Unmanned
Surface Vehicle (USV), and organized several subchallenges in this domain: (i)
UAV-based Maritime Object Detection, (ii) UAV-based Maritime Object Tracking,
(iii) USV-based Maritime Obstacle Segmentation and (iv) USV-based Maritime
Obstacle Detection. The subchallenges were based on the SeaDronesSee and MODS
benchmarks. This report summarizes the main findings of the individual
subchallenges and introduces a new benchmark, called SeaDronesSee Object
Detection v2, which extends the previous benchmark by including more classes
and footage. We provide statistical and qualitative analyses, and assess trends
in the best-performing methodologies of over 130 submissions. The methods are
summarized in the appendix. The datasets, evaluation code and the leaderboard
are publicly available at https://seadronessee.cs.uni-tuebingen.de/macvi.Comment: MaCVi 2023 was part of WACV 2023. This report (38 pages) discusses
the competition as part of MaCV
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The national food safety control system of China: a systematic review
In recent years, there have been increasing concerns over the safety of the Chinese food supply. Although many of these have only raised concern internally within China, several major food safety issues have had international repercussions. In response, China has implemented new food safety laws and management systems to improve its national food safety control system and reduce public and international concerns. This paper has describes and discusses the components of the Chinese system using the five key elements of a national food control system identified by the World Health Organization (WHO) and the Food and Agriculture Organization (FAO) as essential for an effective system. The latest Chinese national food safety control has made significantly improvement on its regulation framework, however, more work need to be done on standards, law enforcement, and information exchange
A Simple and Rapid Fluorescent Probe for Detection of Cr<sup>3+</sup> Based on a Coumarin Schiff Base in Aqueous Solution
Concept Extraction and Prerequisite Relation Learning from Educational Data
Prerequisite relations among concepts are crucial for educational applications. However, it is difficult to automatically extract domain-specific concepts and learn the prerequisite relations among them without labeled data.In this paper, we first extract high-quality phrases from a set of educational data, and identify the domain-specific concepts by a graph based ranking method. Then, we propose an iterative prerequisite relation learning framework, called iPRL, which combines a learning based model and recovery based model to leverage both concept pair features and dependencies among learning materials. In experiments, we evaluated our approach on two real-world datasets Textbook Dataset and MOOC Dataset, and validated that our approach can achieve better performance than existing methods. Finally, we also illustrate some examples of our approach
An Innovative Method for Project Transaction Mode Design Based on Case-Based Reasoning: A Chinese Case Study
Aiming at the design of a project transaction mode, the case-based reasoning (CBR) method is used as a methodology to build a case-based reasoning system based on project performance predictions. Thirty-four cases are initially selected for the practical application. Based on the classical CBR, the performance forecast is added, an improved continuous variable interpolation scoring method is proposed, and three types of manual revision methods are proposed: owner’s preference for the project transaction mode, extreme value, and secondary learning. The innovative method is verified with Nanjing HF Project as an example, and the results show that the case-based reasoning system can optimize the selection and design of the project transaction mode, providing a certain guarantee for project performance and facilitating the transfer of construction experience and knowledge within the construction industry
Influence of Type 1 Diabetes Mellitus on the Ocular Biometry of Chinese Children
Purpose. To compare ocular biometry between children with type 1 diabetes mellitus (T1DM) and healthy children in China and to determine the correlation of ocular biometry with the glycosylated hemoglobin (HbA1c) level and diabetes duration. Methods. A case-control study was conducted at Children’s Hospital of Fudan University between T1DM children and healthy children. The participants were evaluated for central corneal thickness (CCT), anterior chamber depth (ACD), lens thickness (LT), K1 and K2 keratometry, and axial length (AL); also cycloplegic refraction was performed, and spherical equivalent (SE) was acquired. HbA1c levels of the T1DM cases were obtained. Results. Fifty-four eyes of 54 children with T1DM and 53 eyes of 53 healthy children were included. The mean age of T1DM group and control group was 10.59 ± 3.40 years and 9.55 ± 1.89 years, respectively, and the differences between age and gender were not significant (p=0.052, p=0.700). The mean LT in T1DM group (3.49 ± 0.18 mm) was thicker than that in the control group (3.40 ± 0.16 mm) (p=0.018), the mean ACD in T1DM group (3.52 ± 0.26 mm) was shallower than that in the control group (3.72 ± 0.26 mm) (p<0.001), and there were no significant differences of CCT, K1, K2, AL, and SE (p=0.088, p=0.672, p=0.821, p=0.094, and p=0.306, respectively). There was no significant correlation between HbA1c or diabetes duration and ocular biometry. Conclusions. Thicker LT and shallower ACD occurred in T1DM children rather than age-matched and sex-matched healthy children, but the overall refraction was not affected. HbA1c or diabetes duration was not correlated with ocular biometry in T1DM children