Development and validation of machine learning based prediction model for postoperative pain risk after extraction of impacted mandibular third molars
Dongsheng Yu, Zifeng Liu, Weijie Zhuang, Kechen Li, Yaxin Lu · 2023
Read Development and validation of machine learning based prediction model for postoperative pain risk after extraction of impacted mandibular third molars by Dongsheng Yu, Zifeng Liu, Weijie Zhuang, Kechen Li, Yaxin Lu (2023) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-10703859.txt.
Description
Dongsheng Yu, Zifeng Liu, and three co-authors build a machine learning model to flag severe pain after wisdom tooth surgery. Their study, from twenty twenty-three, follows dental outpatients prospectively. One hundred eighty-five patients supply two hundred two extraction cases. High risk means peak pain of seven or more on a ten-point scale within a day.
Nine learning algorithms compete on the same data. A screening step narrows the inputs to five key variables. Checks run inside the sample and on later patients over time. Standard scores rate accuracy, sensitivity, and balance. A good flag lets dentists plan stronger pain control in advance. The model aims at routine clinic use.
Catalog record
| CREATOR | Dongsheng Yu, Zifeng Liu, Weijie Zhuang, Kechen Li, Yaxin Lu |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 35 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |