The article discusses an approach to assessing the level of maturity of medical technologies based on the TRL (technology readiness level) methodology. The author presents a tool for planning scientific results and developments in the direction of «medical sciences» with a clear description of the expected results at each level of research and development. The levels of technological maturity of developments in the field of healthcare are described in detail, possible results and reporting forms for each level are presented, their differences are analyzed depending on the planned final product. Also presented are proposals for the distribution of powers between the state and business to finance the process of creating and implementing a new medical technology, depending on its stage of maturity.
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http://dx.doi.org/10.32687/0869-866X-2021-29-s2-1395-1399 | DOI Listing |
ACS Sens
January 2025
National Engineering Research Center for Biomaterials, Sichuan University, Chengdu 610064, P. R. China.
Fluorescence sensing is widely used in in vitro detection due to its high sensitivity and rapid result delivery. However, detection systems based on nanomaterials involving complex and cumbersome purification steps can lead to sample loss and significantly reduce the accuracy of the results. To address this issue, we proposed a lanthanide-based aptasensor featuring the target-triggered antenna effect to significantly enhance the time-resolved luminescence (TRL) of chelated Tb combined with a wash-free strategy.
View Article and Find Full Text PDFNanotechnology
December 2024
Kutateladze Institute of Thermophysics SB RAS, 630090 Novosibirsk, Russia.
Sensors (Basel)
December 2024
Georgia Institute of Technology, School of Chemistry and Biochemistry, 901 Atlantic Dr. NW, Atlanta, GA 30332, USA.
This study introduces an innovative in situ lander/impact-penetrator design tailored for Discovery-class missions to Europa, specifically focused on conducting astrobiological analyses. The platform integrates a microfluidic capacitively coupled contactless conductivity detector (C4D), optimized for the detection of low-concentration salts potentially indicative of biological activity. Our microfluidic system allows for automated sample routing and precise conductivity-based detection, making it suitable for the harsh environmental and logistical demands of Europa's icy surface.
View Article and Find Full Text PDFChirurgie (Heidelb)
December 2024
Max Planck Queensland Centre (MPQC) for the Materials Science of Extracellular Matrices, Queensland University of Technology, QLD 4000, Brisbane, Australien.
IEEE Trans Cybern
November 2024
Traditional reinforcement learning (RL) methods for optimal control of nonlinear processes often face challenges, such as high computational demands, long training times, and difficulties in ensuring the safety of closed-loop systems during training. To address these issues, this work proposes a safe transfer RL (TRL) framework. The TRL algorithm leverages knowledge from pretrained source tasks to accelerate learning in a new, related target task, significantly reducing both learning time and computational resources required for optimizing control policies.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!