Nowadays, the massive medical data have already influenced the information construction in medical institutes, so it is not enough to solely rely on traditional local storage system to solve the problems like the read/write speed, visualization, and economy brought about by the massive data. Furthermore, various medical cloud services have been developed at home and abroad that patients' medical data can be shared through all medical institutes on the cloud, which makes a higher demand on the transmission speed of the medical data. This article analyzes from multiple aspects like high availability and costs by performing a medical image transmission speed test on the three mainstream storage technologies to provide an optional storage system for future medical image big data in the access process. The experimental result shows that it can be found that in the process of accessing medical image big data, the access speed and performance of object storage system is better than those of the existing local storage systems. However, with comprehensive consideration, it is recommended that the distributed file storage system like HDFS be the first choice for the storage system of the medical images.
Cloud Computing ; Computer Communication Networks ; Humans ; Information Storage and Retrieval ; Technology

Post-marketing surveillance is the principal means to ensure drug use safety. The spontaneous report is the essential method of post-marketing surveillance for drug safety. Often, most spontaneous reports come from medical staff and sometimes come from patients who use the drug. The posts published by individuals on social media platforms that contain drugs and related adverse reaction content have gradually been seen as a new data source similar to spontaneous reports from drug users in recent years. Those user-generated posts potentially provide researchers and regulators with new opportunities to conduct post-marketing surveillance for drug safety from patients' perspectives mostly rather than medical professionals and can afford the possibility theoretically to discover drug-related safety issues earlier than traditional methods. Social media data as a new data source for safety signal detection and signal reinforcement have the unique advantages, such as population coverage, type of drugs, type of adverse reactions, data timeliness and quantity. Most of the social media data used in post-marketing surveillance research for drug safety are still text data in English, and even multiple languages are used by different people worldwide on several social media platforms. Unfortunately, there is still a controversy in the academic circles whether social media data can be used as reliable data sources for routine post-marketing surveillance for drug safety. A couple of obstacles of data, methods and ethics must be overcome before leveraging social media data for post-marketing surveillance. The number of Chinese social media users is large, and the social media data in the Chinese language is rapidly snowballing, which can be employed as the potential data source for post-marketing surveillance for drug safety. However, due to the Chinese language's specific characteristics, the text's diversity is different from the English text, and there is not enough accepted corpus in medical scenarios. Besides, the lack of domestic laws and regulations on privacy and security protection of social media data poses more challenges for applying Chinese social media data for post-market surveillance. The significance of social media data to post-marketing surveillance for drug safety is undoubtedly significant. It will be an essential development direction for future research to overcome the challenges of using social media data by developing new technologies and establishing new mechanisms.
Humans ; Information Storage and Retrieval ; Marketing ; Social Media

The clinical comprehensive evaluation of drugs is an important basis for the return of clinical value, decision-making of medical and health authorities, and allocation of medical resources. In July 2021, the National Health Commission issued the Guidelines for the Management of Clinical Comprehensive Evaluation of Drugs(trial version 2021), which required the evaluation to be implemented from the six dimensions(safety, effectiveness, economy, innovation, suitability, and accessibility), and made detailed arrangements for the clinical comprehensive evaluation of drugs. As Chinese patent medicine differs from chemical medicines in terms of effective components and action modes, the clinical comprehensive evaluation of Chinese patent medicine should highlight the characteristics and advantages of traditional Chinese medicine(TCM) on the basis of general requirements of comprehensive clinical evaluation of drugs. At present, in the clinical comprehensive evaluation of Chinese patent medicine, unified report standards have not yet been generated, resulting in the uneven quality of existing reports. To standardize the clinical comprehensive evaluation report of Chinese patent medicine and improve its quality, the editorial team, based on the relevant policy documents of clinical comprehensive evaluation of drugs, formulated the clinical comprehensive evaluation report standards for Chinese patent medicine in combination with the previous practice and expert opinions. The report standards, containing seven sections with 15 items determined, focus on data source, evaluation content, evidence synthesis, quality control, and evaluation results supported with detailed interpretations to help researchers better understand and apply the report standards for clinical comprehensive evaluation of Chinese patent medicine, improve the report quality, and provide references for the decision-making by the national medical management authorities.
China ; Drugs, Chinese Herbal ; Information Storage and Retrieval ; Medicine, Chinese Traditional ; Nonprescription Drugs ; Quality Control

This article is based on basic data such as field surveys and literature surveys, contrasting and analyzing the distribution of Callicarpa nudiflora by different zoning methods, different data sources, and different spatial scales. The results showed that there were certain differences in the distribution results obtained by using different methods, such as qualitative description, similar ecological environment, and niche model, to divide the distribution of the C. nudiflora, but all of them could reflect the distribution of C. nudiflora to different degrees. Among them, the qualitative description division method has certain advantages in macro guidance in a large scale. The distribution range obtained by the ecological environment similar division method is wider than that obtained by applying the qualitative description method and the niche model method. The results of the zoning of the distribution of the C. nudiflora obtained from different data sources were different. The number and representativeness of the survey data have an impact on the zoning results. Through the analysis of the distribution of different spatial scales, the ecological factors and contribution rates that affect the distribution of C. nudiflora are different in China and in the world. The comprehensive multi-source data analysis showed that C. nudiflora mainly distributed in southern coastal provinces such as Hainan, Guangdong, Guangxi and Fujian in China, and also in Jiangxi, Guizhou, Yunnan, Sichuan, Chongqing, Hunan, Gansu, Taiwan and other provinces. Globally, C. nudiflora are suitable for distribution in Southeast Asia, such as China, Vietnam, Laos, Myanmar, India, etc. There are also potential distribution areas in the southern United States and Mexico.
Callicarpa ; China ; Data Collection ; Information Storage and Retrieval ; Vietnam

OBJECTIVES: This pilot study aimed to provide an overview of the potential for blockchain technology in the healthcare system. The review covers technological topics from storing medical records in blockchains through patient personal data ownership and mobile apps for patient outreach. METHODS: We performed a preliminary survey to fill the gap that exists between purely technically focused manuscripts about blockchains, on the one hand, and the literature that is mostly concerned with marketing discussions about their expected economic impact on the other hand. RESULTS: The findings show that new digital platforms based on blockchains are emerging to enabling fast, simple, and seamless interaction between data providers, including patients themselves. CONCLUSIONS: We provide a conceptual understanding of the technical foundations of the potential for blockchain technology in healthcare, which is necessary to understand specific blockchain applications, evaluate business cases such as blockchain startups, or follow the discussion about its expected economic impacts.
Artificial Intelligence ; Commerce ; Delivery of Health Care* ; Foundations ; Genomics ; Hand ; Humans ; Information Storage and Retrieval ; Marketing ; Medical Records ; Mobile Applications ; Ownership ; Pilot Projects ; Telemedicine

This study sought to describe and to evaluate the characteristics of the Health Screening Records Database (HSRD) of the Korea Association of Health Promotion as a data source for epidemiologic studies. The HSRD was compared to a National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) database for 2015. Common variables between the databases were selected, and sex-based analyses were conducted. The HSRD showed statistical concordance when NHIS-HEALS estimates fell within the HSRD estimate's 95% confidence interval. The HSRD and NHIS-HEALS included 946461 and 111690 participants in health screening programs, respectively. Compared to the NHIS-HEALS, the HSRD had more female (55.2% vs. 42.6%) but fewer older adult participants (34.4% vs. 51.2%). Virtually all variables had clinical concordance, with some having statistical concordance as well, among both general and life-transition program participants. The HSRD comprised more clinical information over a wider age range in contrast to the NHIS-HEALS, while showing clinical concordance. Providing more comprehensive clinical data, the HSRD may serve as an alternative resource for epidemiologic studies.
Adult ; Cohort Studies ; Epidemiologic Studies ; Female ; Health Promotion ; Humans ; Information Storage and Retrieval ; Korea ; Mass Screening ; National Health Programs ; Observational Study ; Physical Examination

Mortalities from cardiovascular disease in Korea have decreased markedly over the past three decades. The major cardiovascular and metabolic risk factors, however, remain prevalent, and their burden on health is large. The Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) planned a cohort study in order to identify novel risk factors and to develop evidence-based prevention strategies of cardiovascular and metabolic diseases. The CMERC deliberately designed two prospective cohorts, a community-based general population cohort (the CMERC cohort) and its sister cohort (a hospital-based high-risk patient cohort), covering a broad spectrum of cardiovascular and metabolic diseases. This paper describes the CMERC cohort study of community-dwelling adults aged 30 to 64 years. A total of 8097 adults completed baseline measurement between 2013 and 2018. Baseline measurements assessed socio-demographic factors, medical history, health-related behaviors, psychological health, social network and support, anthropometry, body composition, and resting blood pressure and comprised electrocardiography, carotid artery ultrasonography, fasting blood analysis, and urinalysis. Both active follow-up through an annual telephone survey and a 5-year on-site health examination survey and passive follow-up through secondary data linkage with national databases, such as national death records, have been applied. Researchers interested in collaborative research may contact the corresponding author.
Adult ; Anthropometry ; Blood Pressure ; Body Composition ; Cardiovascular Diseases ; Carotid Arteries ; Cohort Studies ; Death Certificates ; Electrocardiography ; Fasting ; Follow-Up Studies ; Humans ; Information Storage and Retrieval ; Korea ; Metabolic Diseases ; Mortality ; Prospective Studies ; Republic of Korea ; Risk Factors ; Siblings ; Telephone ; Ultrasonography ; Urinalysis

PURPOSE: The vaccination level of rotavirus vaccine not supported by the government is not known. As vaccines not included in the national immunization schedule are not registered in the computerized national immunization registry system, their vaccination rate cannot be calculated according to the same method used in government-supported vaccines. Therefore, this study aimed to measure the status of the vaccination rate of rotavirus not included in the national immunization schedule. METHODS: The target population is the 0-year-old cohort. The survey population was composed of registered children born in 2017 enrolled in the Immunization Registry Information System. The survey was conducted through a computerized telephone survey method. The survey variables were as follows: vaccination order and date, provider, and data source. Factors related to complete vaccination were the child's sex, residence, birth order, and parents' age, educational level, and job status. RESULTS: Children's vaccination rates for the rotavirus vaccine by 2017 were 88.0%, 86.9%, and 96.6% for the first, second, and third doses, respectively. The rate of complete vaccination was 85.6%. The factors related to rotavirus complete vaccination were the child's sex and birth order, area of residence, parents' age and job status, and father's education level. CONCLUSION: In the future, it is necessary to conduct regular investigations on the rate of rotavirus vaccination as a tool for the development of the rotavirus infectious diseases control policy or as an evaluation tool for vaccine programs.
Birth Order ; Child ; Cohort Studies ; Communicable Diseases ; Education ; Health Services Needs and Demand ; Humans ; Immunization ; Immunization Schedule ; Information Storage and Retrieval ; Information Systems ; Methods ; Rotavirus ; Surveys and Questionnaires ; Telephone ; Vaccination ; Vaccines

Laser surgery (LS) or radiotherapy (RT) is normally recommended in early glottic cancer. The objective of this study was to perform a comprehensive meta-analysis of acoustic and perceptual outcomes to compare voice quality of LS or RT in early-stage glottic cancer. Data sources were obtained after searching PubMed, Google Scholar, EBSCO, and RISS using the following search terms: glottic cancer, glottic carcinoma, endoscopic surgery, laser surgery, radiotherapy, radiation, voice, voice quality, and grade, roughness, breathiness, asthenia, and strain (GRBAS) scale. Articles that compared voice outcomes between LS and RT were identified. This meta-analysis included 15 articles with 744 patients, including 400 in the LS group and 344 in the RT group. Random effects models were selected. Forest plots included standardized mean differences, standard errors, variance, 95% confidence intervals (lower limit to upper limit), z-values, and P-values. In perceptual analysis, grade (G) and asthenia (A) of RT were significantly better than LS. There was no statistically significant difference in roughness (R), breath (B), or strain (S) between LS and RT groups. Jitter, shimmer, and noise to harmonic ratio measurements showed significant differences, resulting in enhanced posttreatment effect of RT compared to LS. Results of our meta-analysis suggested that RT might lead to superior voice quality than LS in early glottic cancer.
Acoustics ; Asthenia ; Forests ; Humans ; Information Storage and Retrieval ; Laser Therapy ; Noise ; Radiotherapy ; Voice ; Voice Quality

Entity normalization, or entity linking in the general domain, is an information extraction task that aims to annotate/bind multiple words/expressions in raw text with semantic references, such as concepts of an ontology. An ontology consists minimally of a formally organized vocabulary or hierarchy of terms, which captures knowledge of a domain. Presently, machine-learning methods, often coupled with distributional representations, achieve good performance. However, these require large training datasets, which are not always available, especially for tasks in specialized domains. CONTES (CONcept-TErm System) is a supervised method that addresses entity normalization with ontology concepts using small training datasets. CONTES has some limitations, such as it does not scale well with very large ontologies, it tends to overgeneralize predictions, and it lacks valid representations for the out-of-vocabulary words. Here, we propose to assess different methods to reduce the dimensionality in the representation of the ontology. We also propose to calibrate parameters in order to make the predictions more accurate, and to address the problem of out-of-vocabulary words, with a specific method.
Dataset ; Information Storage and Retrieval ; Methods ; Semantics ; Vocabulary