Fig 4 - by Ashutosh P. Raman (19825936)

Subjects:

Fig 1 - by Ashutosh P. Raman (19825936)

Subjects:

Emission wavelength and full width at half maximum (FWHM) values for various metabolically important endogenous fluorophores after 405 nm laser excitation [30–31]. by Ashutosh P. Raman (19825936)

Subjects:

Comparison of performance between the machine learning pipelines for tissue classification. by Ashutosh P. Raman (19825936)

Subjects:

Fig 2 - by Ashutosh P. Raman (19825936)

Subjects:

pdig.0000602.t003 - Machine learning approaches in non-contact autofluorescence spectrum classification by Ashutosh P. Raman (19825936)

Subjects:

Fig 7 - by Ashutosh P. Raman (19825936)

Subjects:

Plot of 5 most important principal components (PCs), defined as those PCs making up 95% of total dataset variance together, and their respective variance intensity at each waveleng... by Ashutosh P. Raman (19825936)

Subjects:

Average spectra for both tissue classes, with standard error regions. by Ashutosh P. Raman (19825936)

Subjects:

Fig 9 - by Ashutosh P. Raman (19825936)

Subjects:

Fig 8 - by Ashutosh P. Raman (19825936)

Subjects:

Specific configuration of autofluorescence device with freshly resected tissue sample prior to laser excitation and subsequent signal acquisition. by Ashutosh P. Raman (19825936)

Subjects:

Specific hyperparameters optimized for each non-ANN model in the Nested Grid Search process. by Ashutosh P. Raman (19825936)

Subjects:

Staging of AKI according to KDIGO criteria. by Christian Porschen (12967868)

Subjects:

Overall accuracy of human vs. pyAKI generated labels by classification method. by Christian Porschen (12967868)

Subjects:

Comparison between pyAKI’s generated labels and the labels generated by the MIMIC-code implementation of the KDIGO criteria. by Christian Porschen (12967868)

Subjects:

pyAKI data model. by Christian Porschen (12967868)

Subjects:

Workflow of validating the pyAKI pipeline. by Christian Porschen (12967868)

Subjects:

Accuracy of human-assigned and pyAKI-generated labels across different acute kidney injury stages at each point in time. by Christian Porschen (12967868)

Subjects: