| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Senthil Murugan, Ganapathy
University of Southampton
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (22/22 displayed)
- 2022Study of prediction intervals in machine learning assisted mid-infrared spectroscopy for the diagnosis of neonatal respiratory distress syndrome
- 2022Prediction of neonatal respiratory distress biomarker concentration by application of machine learning to mid-infrared spectracitations
- 2019Mid-IR thermo-optic on-chip spectrometer on a III-V semiconductor platform
- 2018Chalcogenide glass waveguides with paper-based fluidics for mid-infrared absorption spectroscopycitations
- 2017Optical quality ZnSe films and low loss waveguides on Si substrates for mid-infrared applicationscitations
- 2014High-contrast, GeTe4 waveguides for mid-infrared biomedical sensing applicationscitations
- 2012Chalcogenide microsphere fabricated from fiber tapers using contact with a high-temperature ceramic surfacecitations
- 2012High-Q bismuth silicate nonlinear glass microsphere resonatorscitations
- 2012Investigation of Erbium-doped tellurite glasses for a planar waveguide power amplifier at 1.57 microns
- 2012Er-doped Tellurite glasses for planar waveguide power amplifier with extended gain bandwidthcitations
- 2011Integrated Nd-doped borosilicate glass microsphere lasercitations
- 2011Chalcogenide microsphere fabricated from fibre taper-drawn using resistive heating
- 2011Lead silicate glass microsphere resonators with absorption-limited Qcitations
- 2010Multifarious transparent glass nanocrystal composites
- 2010Position-dependent coupling between a channel waveguide and a distorted microsphere resonatorcitations
- 2010Chalcogenide glass microsphere lasercitations
- 2010Transparent silicate glass-ceramics embedding Ni-doped nanocrystals
- 2009Chalcogenide glass microspheres and their applications
- 2009Optical nonlinearities of tellurite glasses with ultrawide Raman bands
- 2007Chalcogenide glass microspheres: their production characterization and potentialcitations
- 2006Control of coupling between waveguides and microsphere resonators
- 2005Raman spectroscopic studies of quaternary tellurite glasses containing Nb2O5 and Ta2O5
Places of action
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document
Study of prediction intervals in machine learning assisted mid-infrared spectroscopy for the diagnosis of neonatal respiratory distress syndrome
Abstract
Point of care devices present an attractive proposition for a rapid, evidenced based, diagnosis to be provided at the patient bedside, and give clinicians access to almost real-time information about a patient's condition.Devices based on attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) can provide rapid, label free measurements consistent with delivery of bedside care.Neonatal respiratory distress syndrome (nRDS) affects some pre-term neonates from their first breath and delays in treatment are associated with poor clinical outcomes.nRDS can be diagnosed by analysis of the lecithin/sphingomyelin ratio (L/S ratio) of the lung surfactant obtained from bronchoalveolar lavage.Following on from our work on mid-infrared spectroscopy for the diagnosis of nRDS, where we established a data processing methodology to evaluate machine learning algorithms used for determining L/S ratios of simple mixtures, this work develops the process, by increasing the number of constituents and using smaller calibration steps to more closely match the patient sample. We will show the performance of machine/deep learning algorithms to predict the concentrations of the constituents present and their L/S ratio along with prediction intervals indicating the uncertainty in the measurement.The results will further inform calibration procedures for a proof-of-principal ATR-FTIR based point-of-care device that can be used in a clinical setting to provide a rapid indication of the L/S ratio of patient samples.