P
Pantelis Georgiou
Researcher at Imperial College London
Publications - 285
Citations - 5799
Pantelis Georgiou is an academic researcher from Imperial College London. The author has contributed to research in topics: ISFET & CMOS. The author has an hindex of 33, co-authored 284 publications receiving 3999 citations.
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Journal ArticleDOI
Simultaneous DNA amplification and detection using a pH-sensing semiconductor system
Christofer Toumazou,Leila Shepherd,Samuel Reed,Ginny I Chen,Alpesh Patel,David M Garner,Chan-Ju A Wang,Chung-Pei Ou,Krishna Amin-Desai,Panteleimon Athanasiou,Hua Bai,Ines M Q Brizido,Benjamin Caldwell,Daniel Coomber-Alford,Pantelis Georgiou,Karen S Jordan,John C Joyce,Maurizio La Mura,Daniel Morley,Sreekala Sathyavruthan,Sara Temelso,Risha E Thomas,Linglan Zhang +22 more
TL;DR: This work has developed an integrated chip for real-time amplification and detection of nucleic acid using pH-sensing complementary metal-oxide semiconductor (CMOS) technology and evaluated the platform using two amplification strategies: PCR and isothermal amplification.
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Machine learning for clinical decision support in infectious diseases: a narrative review of current applications.
Nathan Peiffer-Smadja,Nathan Peiffer-Smadja,Timothy M. Rawson,Raheelah Ahmad,Albert Buchard,Pantelis Georgiou,François-Xavier Lescure,Gabriel Birgand,Alison Holmes +8 more
TL;DR: Considering comprehensive patient data from socioeconomically diverse health care settings, including primary care and LMICs, may improve the ability of ML-CDSS to suggest decisions adapted to various clinical contexts.
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ISFETs in CMOS and Emergent Trends in Instrumentation: A Review
TL;DR: In this paper, the authors present a review of the state-of-the-art in terms of device and early readout circuity for ion-sensitive field effect transistors (ISFETs).
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Convolutional Recurrent Neural Networks for Glucose Prediction
TL;DR: A deep learning model capable of forecasting glucose levels with leading accuracy for simulated patient cases and with minimal time lag both in a simulated patient dataset and in a real patient dataset is presented.
Journal ArticleDOI
ISFET characteristics in CMOS and their application to weak inversion operation
TL;DR: In this article, the main factors modifying the intrinsic characteristics of the MOSFET from which it is made and derive a model for its operation and pH sensitivity in weak inversion.