Non-invasive dengue screening method via optical spectroscopy: A multivariate investigation / Abdul Halim Poh Yuen Wu
More feared than understood, dengue fever often evokes emotions of morbidity in the public space, arguably due to a positive response to media campaigns. A symphony of clinical analysis of blood results (not necessarily dependent only on the NS1 detection), symptoms, and day of fever onset, among...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Published: |
2019
|
| Subjects: | |
| Online Access: | http://studentsrepo.um.edu.my/13135/1/Abdul_Halim_Poh.pdf http://studentsrepo.um.edu.my/13135/2/Abdul_Halim_Poh.pdf http://studentsrepo.um.edu.my/13135/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | More feared than understood, dengue fever often evokes emotions of morbidity in
the public space, arguably due to a positive response to media campaigns. A symphony
of clinical analysis of blood results (not necessarily dependent only on the NS1 detection),
symptoms, and day of fever onset, among others, contributes to a successful diagnosis,
often spanning many man-hours (or days) combined with costly overhead expenditure.
For dengue-related management, the Government of Malaysia spent close to US$73.5
million in 2010, which was 0.03% of the country’s GDP during that time.
With the aim of reduction of the time and monetary costs involved in this issue, a
potentially non-invasive method was scrutinized in painstaking detail to circumvent at
least a few hurdles in dengue patient care, especially in diagnostics. This method is
namely Diffuse Optical Reflectance Skin Spectroscopy. With a probe and a light source
combined with spectrometers, the forearm of a suspect patient in the University of Malaya
Medical Centre (UMMC) is scanned. The spectroscopy data is then collected and saved
via a software tailored to consolidate all information regarding the patient. The patient is
then assigned to a diagnosis by UMMC physicians. Three groups were later formulated
for the classification, namely confirmed dengue, probable dengue, and control patients.
Based on multivariate analysis on the spectroscopy data of 230 patients, we have
come to at least two major findings. First, the modelling produced by the statistical
algorithms predicted the accuracy of detection up to 98.65% on discriminating all three
groups. Second, several feasible algorithmic models for classifying dengue patients was
synthesized, ranging from sensitivities and specificities of 76.67%-89.29% and 94.85-
100% respectively. From these findings, further clinical trials on non-invasive dengue
screening are recommended.
|
|---|