Data · dataset · 2025
Visual analysis of research hotspots and trends of artificial intelligence in the diagnosis and treatment of prostate cancer based on Cite Space and VOS viewer
Listed in ScienceDB
Objective To analyze the research hotspots and trends of artificial intelligence in the diagnosis and treatment of prostate cancer.
Description
Methods
The literature source was Web of Science database, and all the literature related to prostate cancer and artificial intelligence was searched. VOSviewer and Cite Space were used for visual analysis including authors, journals, countries, institutions, keywords, etc.Results A total of 605 literatures were used for visual analysis, and the number of publications in this field showed an increasing trend. The annual number of publications increased exponentially after 2017 (reaching 129 papers in 2024).
Read the rest (2 more)
The United States led the research output (184 papers, 30.4%), followed by China but with low citation volume. Keywords co-occurrence and emergence analysis showed that research focused on MRI radiomics (such as PI-RADS automation), deep learning-driven biopsy optimization and multimodal data integration, and emerging trends pointed to the intersection of artificial intelligence and immunotherapy response prediction. The institutional cooperation network showed that the University of British Columbia and Shanghai Jiaotong University were high-yield institutions, but cross-regional cooperation still needed to be strengthened.Conclusions AI is promoting the development of precision diagnosis and treatment of prostate cancer.
In the future, multi-center clinical validation, interpretable model development and ethical standards should be paid attention to to promote technology transformation.
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.dmh.00159 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Medicine & Health · Social Science
- Inferred from text
- Applied computing 70% · Cancer 75% · Magnetic resonance imaging 65%
Related
Provenance · 1 source records, 15 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.dmh.00159 | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[disease].local:disease:cancer | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[field].anzsrc:group:4601 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (70%) |
| concepts[field].local:field:computer-science-ai | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[modality].local:modality:mri | enrichment · scidb cn | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/rights |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |