Leila Aissaoui Ferhi
Biographic Data
| ID | 4638994 |
|---|---|
| NAME | Leila Aissaoui Ferhi |
| GIVEN NAMES | Leila Aissaoui |
| FAMILY NAME | Ferhi |
| SIGNATURE | FERHI L A |
| AFFILIATIONS | Virtual University of Tunis (UVT) Tunis Tunisia |
| ORCID | 0000-0002-7580-6004 |
| VERIFIED | Yes |
| TOTAL WORKS | 1 |
| TOTAL CITATIONS | 1 |
| WORKS AS AUTHOR | 1 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2025 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 1 |
Improving Symptom‐Based Medical Diagnosis Using Ensemble Learning Approaches
Symptoms‐based health checkers are emerging as digital tools in modern healthcare offering patients the ability to self‐assess their health status by inputting symptoms and receiving diagnostic suggestions. These systems rely on machine learning models to accurately predict medical conditions based on symptom data. In this study, we explore the effectiveness of various machine learning algorithms with a particular focus on ensemble learning metho…
Improving Symptom‐Based Medical Diagnosis Using Ensemble Learning Approaches
Symptoms‐based health checkers are emerging as digital tools in modern healthcare offering patients the ability to self‐assess their health status by inputting symptoms and receiving diagnostic suggestions. These systems rely on machine learning models to accurately predict medical conditions based on symptom data. In this study, we explore the effectiveness of various machine learning algorithms with a particular focus on ensemble learning metho…
Improving Symptom‐Based Medical Diagnosis Using Ensemble Learning Approaches
Symptoms‐based health checkers are emerging as digital tools in modern healthcare offering patients the ability to self‐assess their health status by inputting symptoms and receiving diagnostic suggestions. These systems rely on machine learning models to accurately predict medical conditions based on symptom data. In this study, we explore the effectiveness of various machine learning algorithms with a particular focus on ensemble learning metho…
Artificial Intelligence (1 work) · Artificial Intelligence in Healthcare and Education (1 work) · Bootstrap aggregating (1 work) · Computer Science (1 work) · Data mining (1 work) · Decision tree (1 work) · Ensemble learning (1 work) · Logistic regression (1 work) · Machine learning (1 work) · Machine Learning in Healthcare (1 work)