| Title |
New therapeutic opportunities discovered by statistical models and AI algorithms / |
| Authors |
Ostaševičius, Vytautas |
| DOI |
10.15388/DAMSS.14.2023 |
| ISBN |
9786090709856 |
| Full Text |
|
| Is Part of |
DAMSS 2023:14th conference on data analysis methods for software systems, November 30 – December 2, 2023, Druskininkai, Lithuania.. Vilnius : Vilnius University press, 2023. p. 68.. ISBN 9786090709856 |
| Abstract [eng] |
Technological advances in high-speed data processing have transformed medical biology into a field of data mining, where new data sets are regularly dissected and analysed with the help of increasingly sophisticated statistical models and artificial intelligence algorithms. One of the most common ways of identifying health status is through blood analysis. As a result of this research, faster statistical and artificial intelligence methods have been proposed for speeding up the analysis and interpretation of blood parameters, allowing to avoid the mistakes of inexperienced analysts, and to take timely actions to improve human health. Such a possibility of improving human health was revealed by affecting the blood with low-frequency ultrasound, the influence of which is associated with the exchange of O2 and CO2 gases in red blood ceells and platelet aggregation. Statistical analysis, ANOVA and the non-parametric Kruskal-Wallis method, was used to evaluate the effect of ultrasound on various blood parameters. The obtained results suggest that there are statistically significant variances in blood parameters attributed to low-frequency ultrasound exposure. Furthermore, among the five machine learning algorithms employed to predicts ultrasound’s impact on platelet counts, Support Vector Regression (SVR) exhibited the highest prediction accuracy, yielding an average MAPE at 10.34%. Notably it was found that the effect of ultrasound on hemoglobin in red blood cells outperformed its impact on platelet aggregation highlighting the significance of hemoglobin in facilitating the transfer of oxygen from the lungs to the body’s tissues. |
| Published |
Vilnius : Vilnius University press, 2023 |
| Type |
Conference paper |
| Language |
English |
| Publication date |
2023 |
| CC license |
|
