| Autor: |
Reddy, K. Subba, Narasimhulu, K., Muneeswari, K., Haritha, P., Charitha, P. Sai, Dileep, K. |
| Předmět: |
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| Zdroj: |
AIP Conference Proceedings; 2023, Vol. 2821 Issue 1, p1-5, 5p |
| Abstrakt: |
Forming health tweets clusters is required to give healthcare solutions based on the assessment of tweets related to diseases and symptoms. As part of this work, existing topic models are enhanced by designing and implementing prototypes of ailments. An ailment refers to either illness or sign of a particular health problem. Millions of tweets are collected based on conditions and assessed with ailment topic aspect models. Recent ailments topic aspect model (ATAM) overcome the problems of these topic models and delivers the healthcare assessment results concerning the fundamental aspects of ailments data except side-effects analysis of treatments. An enhanced model of ATAM has been developed in the distributed environment to consider the fourth aspect, i.e., side-effects analysis of treatments from the tweets data. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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