Latest Research in AI in cancer detection

Top Research Topics in AI in cancer detection

• Single-cell and spatial transcriptomics — 10 papers
• AI in cancer detection — 5 papers
• Computer Vision and Pattern Recognition — 5 papers
• HIV Research and Treatment — 4 papers
• Methodology — 3 papers
• Protein Degradation and Inhibitors — 3 papers
• Immune responses and vaccinations — 2 papers
• interferon and immune responses — 2 papers
• DNA Repair Mechanisms — 2 papers
• BRCA gene mutations in cancer — 1 papers

Highest-Cited Papers

1. Impact of Single‐Cell RNA Reference Selection for the Deconvolution of Breast Cancer Spatial Transcriptomics Datasets (1 citations)
2. Extending single-cell proteomics from HeLa to small primary human immune cells
3. The BRCA1 coiled-coil domain is dispensable for suppression of tandem duplications and tolerance of FANCM loss
4. Extracellular vesicle miRNAs reflect treatment duration and inflammation state in long-term treated people living with HIV
5. Secreted ORF8 reprograms macrophages to enhance SARS-CoV-2 infection of lung epithelial cells
6. SmartHisto: Bayesian active learning for histology images
7. Compressive Bayesian non-negative matrix factorization for mutational signatures analysis
8. A Survey on the Evolution and Future Trajectory of Flow Cytometry Analysis
9. Differential effects of BCG-Russia and BCG-TICE on trained immunity: Potential implications for bladder cancer immunotherapy
10. Circular RNAs Associated with Human Cytomegalovirus Infection
11. From Daffodils to Drug Leads: Amaryllidaceae Alkaloids Target Protein Translation in Chronic Lymphocytic Leukemia to Induce Selective Apoptosis
12. HemaHier: Chain-Conditioned Ordinal Hierarchies for Lineage-Aware Bone-Marrow Cytology
13. STING-mediated JAK-STAT suppression drives CD4⁺ T cell dysfunction in aging people living with HIV-1
14. Velociraptor Machine Learning Quantifies Similarity to Known Cell Types and Matches Cells Across Flow and Imaging Cytometry Platforms
15. Temporal lymphatic tissue destruction and impairment of de novo T cell responses after an acute virus infection
16. Pretraining and Distillation Matter More Than Architecture Family for Label-Free Single-Cell Classification
17. LSP-DETR: Efficient and Scalable Nuclei Segmentation in Whole-Slide Images
18. Scalable Dirichlet Process Mixture Models with Unknown Concentration and Adaptive Covariance for High-Dimensional Clustering Applied to Leukemia Transcriptomics
19. Chemogenomic maps reveal a PRDX1-dependent iron–damage axis in the DNA damage response
20. Detection of Single-Stranded DNA Gaps Reveals a Functional Biomarker of Therapeutic Response