Trends and Key Areas of Research on Artificial Intelligence in Lymphoma: A Bibliometric Study from 2010 to 2024
-
By
-
Haixin Mao
-
Qin Zhang
-
Dan Wan
-
Yujie Lu
-
Yutao Zhang
-
January 1, 2026
-
Clinical Scorecard: Trends and Key Areas of Research on Artificial Intelligence in Lymphoma: A Bibliometric Study from 2010 to 2024
At a Glance
| Category | Detail |
|---|
| Condition | |
| Key Mechanisms | |
| Target Population | Patients with Hodgkin lymphoma and non-Hodgkin lymphoma, particularly among the elderly, including specific subtypes. |
| Care Setting | |
Key Highlights
- NHL is the 10th most common cancer worldwide.
- AI enhances diagnostic accuracy and treatment response predictions.
- Bibliometric analysis identifies research trends and hotspots in AI and lymphoma.
- AI's role in improving patient outcomes is critical.
Guideline-Based Recommendations
Diagnosis
Management
Monitoring & Follow-up
Risks
- Be aware of the limitations of traditional diagnostic methods that may impact accuracy, including potential biases in AI algorithms.
Patient & Prescribing Data
AI can assist in identifying precise targeted therapies based on genetic subtypes, such as B-cell and T-cell lymphomas.
Clinical Best Practices
- Incorporate AI technologies such as deep learning models in routine diagnostic workflows.
- Leverage electronic health records for enhanced research and decision-making, utilizing platforms like IBM Watson.
References
