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Use of machine learning models for the prognostication of liver transplantation: A systematic review

World Journal of Transplantation 2024年第1期14卷 164-188页

作者： gidion chongo Jonathan Soldera Department of Gastroenterology University of South WalesCardiff CF371DLUnited Kingdom

BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver ***,the equitable allocation of scarce donor organs remains a formidable *** tools are pivotal in identifying the most suitable transplant ***,scoring systems like the model for end-stage liver disease have been instrumental in this ***,the landscape of prognostication is undergoing a transformation with the integration of machine learning(ML)and artificial intelligence *** To assess the utility of ML models in prognostication for LT,comparing their performance and reliability to established traditional scoring *** Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines,we conducted a thorough and standardized literature search using the PubMed/MEDLINE *** search imposed no restrictions on publication year,age,or *** criteria encompassed non-English studies,review articles,case reports,conference papers,studies with missing data,or those exhibiting evident methodological *** Our search yielded a total of 64 articles,with 23 meeting the inclusion *** the selected studies,60.8%originated from the United States and China *** one pediatric study met the ***,91%of the studies were published within the past five *** models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values(ranging from 0.6 to 1)across all studies,surpassing the performance of traditional scoring *** forest exhibited superior predictive capabilities for 90-d mortality following LT,sepsis,and acute kidney injury(AKI).In contrast,gradient boosting excelled in predicting the risk of graft-versus-host disease,pneumonia,and *** This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT,mark

关键词： Liver transplantation Machine learning models Prognostication Allograft allocation Artificial intelligence

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Resonance phenomena in dielectric media: A review and comparison of acoustic and electromagnetic modes

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Journal of Advanced Dielectrics 2023年第4期13卷 35-40页

作者： Gunnar gidion Taimur Aftab Leonhard M.Reindl Stefan J.Rupitsch Department of Microsystems Engineering University of Freiburg Georges-Köhler-Allee 10679110 Freiburg im BreisgauGermany

The theory and application of resonances and vibrational modes are part of the foundation of *** this contribution,examples of acoustical resonators are highlighted,and compared to electromagnetic *** an example from architecture,we describe the phenomenon of whispering galleries;such modes are nowadays known in dielectric and optical resonators.A specimen of a semicircular whispering bench in Park Sanssouci in Potsdam is acoustically investigated and demonstrated to show low losses for sound propagation.A special acoustical bug is discussed which was used for the espionage of the *** in *** Sovyets could interrogate this passive device by radio *** working principle was based on the electromagnetic resonance of the cavity that the sound-sensitive membrane was part *** underlying relation between excitation and resonance is compared to the sound production in flue organ pipes.A stopped flue organ pipe was investigated using a piezoelectric film sensor inside the pipe *** results show that even-numbered modes,which are usually suppressed in the radiated sound of a stopped pipe,are still present in the vibrations inside the resonator.

关键词： Whispering gallery dielectric resonator passive wireless microphone flue organ pipe ferroelectret sensor

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Ferroelectrets:Heterogenous polymer electrets with high piezoelectric sensitivity for transducers

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Journal of Advanced Dielectrics 2023年第4期13卷 3-26页

作者： Xunlin Qiu Peng Fang Axel Mellinger Ruy Alberto Pisani Altafim Werner Wirges Gunnar gidion Dmitry Rychkov Shanghai Key Laboratory of Intelligent Sensing and Detection Technology School of Mechanical and Power Engineering East China University of Science and Technology Shanghai 200237P.R.China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Shenzhen 518055P.R.China Department of Physics Central Michigan University 223 Dow Science ComplexMount PleasantMI 48859USA Computer Systems Department Informatics Center Federal University of ParáıbaJoão Pessoa-PBBrazil Department of Physics and Astronomy University of Potsdam PotsdamBrandenburgGermany Laboratory for Electrical Instrumentation Department of Microsystems Engineering-IMTEK University of FreiburgGeorges-Köhler-Allee 106Freiburg 79110Germany Technology and Study Center Weissenburg Deggendorf Institute of Technology WeissenburgBavariaGermany

Nowadays,the demand for advanced functional materials in transducer technology is growing *** materials transform mechanical variables(displacement or force)into electrical signals(charge or voltage)and vice *** are interesting from both fundamental and application points of ***(also called piezoelectrets)are a relatively young group of piezo-,pyro-and ferroelectric *** exhibit ferroic behavior phenomenologically undistinguishable from that of traditional ferroelectrics,although the materials per se are essentially non-polar space-charge electrets with artificial macroscopic dipoles(i.e.,internally charged cavities).A lot of work has been done on ferroelectrets and their applications up to *** this paper,we review and discuss mostly the work done at University of Potsdam on the research and development of *** will,however,also mention important results from other teams,and prospect the challenges and future progress trend of the field of ferroelectret research.

关键词： Ferroelectret piezoelectret space-charge electret transducer advanced functional materials

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