Prediction of Changes in Blood Parameters Induced by Low-Frequency Ultrasound
Abstract
:1. Introduction
1.1. Related Work
1.2. Research Objectives
2. Materials and Methods
2.1. Sonication of Blood Samples
2.2. Investigation of Hematological Parameters
2.3. Investigation of Platelet Aggregation
2.4. Kruskal-Wallis Test
2.5. Platelet Number Prediction by Machine Learning
3. Results
3.1. Platelet Aggregation
3.2. Blood Analysis
3.3. Statistical Analysis
3.4. Platelet Number Prediction
4. Discussion
Suggestions for the Future
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Data Availability Statement
Conflicts of Interest
References
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Sonication Mode | Ultrasound Exposure, s | Ultrasound Intensity, mW/cm2 | Electric Power, W | Ultrasound Frequency, kHz |
---|---|---|---|---|
K | 0 | 0 | 0 | 0 |
A | 90 | 100–150 | 60 | 48 |
B | 180 | 100–150 | 60 | 48 |
C | 90 | 50–70 | 35 | 44 |
D | 180 | 50–70 | 35 | 44 |
E | 90 | 5–12 | 10 | 44 |
F | 180 | 5–12 | 10 | 44 |
Parameter: | F40,6 | p-Value |
---|---|---|
RBC | 13.80 | <0.01 |
MCV | 12.51 | <0.01 |
HCT | 12.61 | <0.01 |
MPV | 14.58 | <0.01 |
PDW | 15.20 | <0.01 |
LPCR | 15.31 | <0.01 |
WBC | 29.43 | <0.01 |
HGB | 2.25 | 0.039 |
MCH | 17.34 | <0.01 |
MCHC | 2.53 | 0.021 |
LYM | 16.98 | <0.01 |
GRAN | 32.88 | <0.01 |
LYM% | 13.52 | <0.01 |
GRA% | 7.29 | <0.01 |
MID% | 23.49 | <0.01 |
Blood Parameters with p-Value < 0.05 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|
RBC | HTC | MPV | PDW | LPCR | WBC | MCH | MCHC | GRA(%) | GRAN | MID(%) |
<0.001 | <0.001 | 0.037 | 0.044 | 0.015 | 0.010 | <0.001 | <0.001 | 0.006 | 0.002 | <0.001 |
Blood Parameters with p-Value > 0.05 | ||||||||||
RDW | MCV | PLT | PCT | HGB | LYM | MID | RDWa | LYM(%) | ||
0.990 | 0.842 | 0.885 | 0.808 | 0.584 | 0.166 | 0.467 | 0.977 | 0.157 |
Blood Parameter | p-Values Adjusted by the Bonferroni Correction | |||||
---|---|---|---|---|---|---|
0 C-180 W | 0 C-90 M | 0 C-180 H | 0 C-90 H | 0 C-90 W | 0 C-180 M | |
RBC | 1.000 | 1.000 | 0.469 | 0.037 | 1.000 | 1.000 |
HTC | 1.000 | 1.000 | 0.324 | 0.047 | 1.000 | 1.000 |
MCH | 1.000 | 0.008 | 0.000 | 0.000 | 1.000 | 0.03 |
MCHC | 1.000 | 0.000 | 0.000 | 0.000 | 1.000 | 0.000 |
MID, % | 1.000 | 1.000 | 0.028 | 1.000 | 1.000 | 1.000 |
ML Algorithm | 90 W | 180 W | 90 M | 180 M | 90 H | 180 H |
---|---|---|---|---|---|---|
DT | 44.156 | 36.61 | 41.61 | 35.8 | 67.34 | 60.16 |
RF | 47.822 | 33.68 | 34.49 | 29.75 | 67.98 | 52.63 |
ANN | 66.04 | 51.84 | 27.04 | 41.75 | 154.24 | 93.96 |
LR | 48.99 | 42.83 | 43.54 | 38.77 | 76.05 | 82.83 |
SVR | 23.45 | 27.73 | 22.90 | 27.12 | 35.41 | 55.80 |
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Ostasevicius, V.; Paulauskaite-Taraseviciene, A.; Lesauskaite, V.; Jurenas, V.; Tatarunas, V.; Stankevicius, E.; Tunaityte, A.; Venslauskas, M.; Kizauskiene, L. Prediction of Changes in Blood Parameters Induced by Low-Frequency Ultrasound. Appl. Syst. Innov. 2023, 6, 99. https://doi.org/10.3390/asi6060099
Ostasevicius V, Paulauskaite-Taraseviciene A, Lesauskaite V, Jurenas V, Tatarunas V, Stankevicius E, Tunaityte A, Venslauskas M, Kizauskiene L. Prediction of Changes in Blood Parameters Induced by Low-Frequency Ultrasound. Applied System Innovation. 2023; 6(6):99. https://doi.org/10.3390/asi6060099
Chicago/Turabian StyleOstasevicius, Vytautas, Agnė Paulauskaite-Taraseviciene, Vaiva Lesauskaite, Vytautas Jurenas, Vacis Tatarunas, Edgaras Stankevicius, Agilė Tunaityte, Mantas Venslauskas, and Laura Kizauskiene. 2023. "Prediction of Changes in Blood Parameters Induced by Low-Frequency Ultrasound" Applied System Innovation 6, no. 6: 99. https://doi.org/10.3390/asi6060099