1.Health technology in perspective.
Journal of Periodontal & Implant Science 2015;45(1):1-1
No abstract available.
Biomedical Technology*
2.Analysis of the Common Problems of Combination Products Application.
Jiaxin TIAN ; Yongqing WANG ; Wei XU ; Xiaobing FU ; Yubo FAN
Chinese Journal of Medical Instrumentation 2020;44(1):68-70
The number of combination products is increasing, and the cutting-edge and innovative technologies are constantly being used. How to evaluate combination products become difficult points. This study team summarizes the supervision conditions of the combination products and analyzes the common problems of these products application from the perspective of technical review, in order to provide reference for Chinese manufacturers and investigators in these products registration.
Biomedical Technology
3.Value-Based Health Technology Assessment and Health Informatics.
Healthcare Informatics Research 2017;23(3):139-140
No abstract available.
Biomedical Technology*
;
Informatics*
;
Technology Assessment, Biomedical*
4.The Present and Future of Nanotechnology in Medicine.
The Korean Journal of Hepatology 2004;10(3):185-190
No abstract available.
*Biomedical Technology
;
Humans
;
*Nanotechnology
5.The biomedical laboratory center
Journal of Medical Research 2001;15(2):50-52
The Biomedical Laboratory Center of Hanoi Medical University was established in January 17th 1997 and comprises 4 small labors: the functional tests; biochemical; immunology and genetic. According to its functions and tasks, the labor has human resources with the high technical and scientific levels. This resource originated from the faculties of Hanoi Medical University. This is an activity pattern which is suitable and convenient for staffs and students in the university.
Technology Assessment, Biomedical
;
Laboratories
6.Evidence Base Medicine and Pre-Appraised Resources.
Korean Journal of Family Medicine 2010;31(12):897-903
Despite wide acceptance of the idea of 'evidence based medicine (EBM)', there is still a huge gap between evidence and clinical practice. Pre-appraised resources help clinicians find correct answers to clinical questions more easily and rapidly. It will briefly explain the concept and history of EBM. Frequently used pre-appraised resources like as systematic review, evidence based guidelines, health technology assessment, synopses, and clinical information database systems are also introduced.
Biomedical Technology
;
Evidence-Based Medicine
7.The application of nanotechnology in biomedicine.
Acta Academiae Medicinae Sinicae 2002;24(2):197-202
Nanotechnology is a new comprehensive system, which prepares substances or/material at molecular or nuclear level in nanometer scale, and nano materials can be explored to apply on broad aspects of industrial engineering sciences. This paper reviews the following contents: developing molecular engineering, biological molecular robot and nanometer information processing system, the application of nanobiomaterials in the field of tissue engineering, constructing drug carriers with nanobiomaterials, developing nanotechnology relating to diagnosis and monitoring. Developmental trend of nanotechnology in biomedical science is discussed prospectively.
Biomedical Technology
;
Humans
;
Nanotechnology
;
trends
8.Establishment of a Quantitative Medical Technology Evaluation System and Indicators within Medical Institutions.
Suo-Wei WU ; Tong CHEN ; Qi PAN ; Liang-Yu WEI ; Qin WANG ; Chao LI ; Jing-Chen SONG ; Ji LUO
Chinese Medical Journal 2018;131(11):1327-1332
BackgroundThe development and application of medical technologies reflect the medical quality and clinical capacity of a hospital. It is also an effective approach in upgrading medical service and core competitiveness among medical institutions. This study aimed to build a quantitative medical technology evaluation system through questionnaire survey within medical institutions to perform an assessment to medical technologies more objectively and accurately, and promote the management of medical quality technologies and ensure the medical safety of various operations among the hospitals.
MethodsA two-leveled quantitative medical technology evaluation system was built through a two-round questionnaire survey of chosen experts. The Delphi method was applied in identifying the structure of evaluation system and indicators. The judgment of the experts on the indicators was adopted in building the matrix so that the weight coefficient and maximum eigenvalue (λ max), consistency index (CI), and random consistency ratio (CR) could be obtained and collected. The results were verified through consistency tests, and the index weight coefficient of each indicator was conducted and calculated through analytical hierarchy process.
ResultsTwenty-six experts of different medical fields were involved in the questionnaire survey, 25 of whom successfully responded to the two-round research. Altogether, 4 primary indicators (safety, effectiveness, innovativeness, and benefits), as well as 13 secondary indicators, were included in the evaluation system. The matrix is built to conduct the λ max, CI, and CR of each expert in the survey, and the index weight coefficients of primary indicators were 0.33, 0.28, 0.27, and 0.12, respectively, and the index weight coefficients of secondary indicators were conducted and calculated accordingly.
ConclusionsAs the two-round questionnaire survey of experts and statistical analysis were performed and credibility of the results was verified through consistency evaluation test, the study established a quantitative medical technology evaluation system model and assessment indicators within medical institutions based on the Delphi method and analytical hierarchy process. Moreover, further verifications, adjustments, and optimizations of the system and indicators will be performed in follow-up studies.
Biomedical Technology ; methods ; Surveys and Questionnaires
10.Progress in biomedical data analysis based on deep learning.
Suyi LI ; Shijie TANG ; Feng LI ; Jianzhuo QI ; Wenji XIONG
Journal of Biomedical Engineering 2020;37(2):349-357
Traditional biomedical data analysis technology faces enormous challenges in the context of the big data era. The application of deep learning technology in the field of biomedical analysis has ushered in tremendous development opportunities. In this paper, we reviewed the latest research progress of deep learning in the field of biomedical data analysis. Firstly, we introduced the deep learning method and its common framework. Then, focusing on the proposal of biomedical problems, data preprocessing method, model building method and training algorithm, we summarized the specific application of deep learning in biomedical data analysis in the past five years according to the chronological order, and emphasized the application of deep learning in medical assistant diagnosis. Finally, we gave the possible development direction of deep learning in the field of biomedical data analysis in the future.
Algorithms
;
Biomedical Technology
;
Data Analysis
;
Deep Learning