A Study on the Integrated Application of Deep Learning and Semantic Analysis Techniques in Sentiment Interpretation of Medical Texts
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19 mar 2025
INFORMAZIONI SU QUESTO ARTICOLO
Pubblicato online: 19 mar 2025
Ricevuto: 22 ott 2024
Accettato: 19 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0461
Parole chiave
© 2025 Chunjun Cheng et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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The parameter settings of the AC-BiLSTM model
| Model | Precision/% | Recall/% | F1/% |
|---|---|---|---|
| LSTM | 87.48 | 85.79 | 86.63 |
| BiLSTM | 88.32 | 86.94 | 87.62 |
| CNN-LSTM | 89.79 | 86.54 | 88.14 |
| AC-BiLSTM | 91.45 | 88.65 | 90.03 |
The “theme-word” distribution of the medical and public opinion of the year
| Year | Topics | Key words |
|---|---|---|
| 2018 | Topic1: Thank you, doctor | Injury (0.051), Heart (0.044), Thank you (0.042), World (0.041), It’s worth (0.030) |
| Topic2: Hope to understand | Reason (0.116), I hope (0.048), Social (0.048), Doctor (0.047), That happened at (0.045). | |
| Topic3: Doctor injury | Candles (0.125), Doctor (0.077), Hospital (0.030), Death (0.026), Injured doctor (0.024) | |
| Topic4: Medical dispute | Medical disputes (0.148), Violence (0.087), Dispute (0.069), Medical treatment (0.050), Medical (0.033) | |
| 2019 | Topic5: Blog forwarding | Smile (0.171), Forward (0.091), Medical staff (0.069), News (0.051), Child (0.042) |
| Topic6: Get angry | Doctor (0.136), Hospital (0.059), Patient (0.044), Patient (0.042), Social (0.033) | |
| Topic7: Understanding protection | Occupation (0.091), Death (0.085), Understand (0.078), Doctor (0.071), Protection (0.062) | |
| Topic8: Doctor’s benevolence | Treatment (0.065), Doctor (0.057), Heart (0.038), Clinical (0.036), Benevolence (0.035) | |
| 2020 | Topic9: Protect the doctor | Hospital (0.049), Protection (0.045), Doctor (0.042), Wife (0.040), Support at (0.039) |
| Topic10: Execution | Death penalty (0.201), Execution (0.082), Judgement (0.063), Anger (0.054), Smile (0.047) | |
| Topic11: Kill the doctor | Death (0.119), Kill (0.103), Doctor (0.074), Medical troubles (0.042), Hurt (0.031) | |
| Topic12: Terrible anger | Heat (0.120), Search for (0.111), State (0.058), Terrible (0.043), Anger (0.038) | |
| 2021 | Topic13: Conflict resolution | Health care commission (0.081), Death (0.067), State (0.056), Solve (0.040), Law (0.032) |
| Topic14: Call for punishment | Call on (0.125), Punish (0.123), News (0.041), Medical personnel (0.037), Unfortunately (0.029) | |
| Topic15: Protection protection | Doctor (0.078), Response (0.043), Protection (0.041), I hope (0.039), Medical staff (0.033) | |
| Topic16: Attention to medical ethics | Hospital (0.096), Occur (0.069), Epidemic situation (0.048), Take seriously (0.047), Bad (0.029) |