ReviewDiagnostics (Basel, Switzerland)2023
Artificial Intelligence and Radiomics: Clinical Applications for Patients with Advanced Melanoma Treated with Immunotherapy.
Review in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 11 citations in OpenAlex.
- CT radiomics showed no improvement beyond volume dynamics for early lesion-level size response to immunotherapy in metastatic melanoma.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Review
- Advancing precision immuno-oncology in melanoma: the synergistic convergence of personalized neoantigen vaccines and multi-omics biomarker profiling.Frontiers in immunology · 2026Review
- Digital Pathology-Based Comparison of PyRadiomics and HistomicsTK for Nuclei Classification in Melanoma Whole Slide Images.International journal of biomedical imaging · 2026Article
- A computed tomography-based deep learning radiomics for predicting the response to neoadjuvant chemotherapy combined with immunotherapy in patients with locally advanced esophageal cancer: a multicenter cohort study.Journal of thoracic disease · 2025Article
- Metastatic Melanoma Prognosis Prediction Using a TC Radiomic-Based Machine Learning Model: A Preliminary Study.Cancers · 2025Article
- Rewiring lipid metabolism to enhance immunotherapy efficacy in melanoma: a frontier in cancer treatment.Frontiers in oncology · 2025Review
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- Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 7 institutions in 3 countries.
Funding
Abstract
Immunotherapy has greatly improved the outcomes of patients with metastatic melanoma. However, it has also led to new patterns of response and progression, creating an unmet need for better biomarkers to identify patients likely to achieve a lasting clinical benefit or experience immune-related adverse events. In this study, we performed a focused literature survey covering the application of artificial intelligence (AI; in the form of radiomics, machine learning, and deep learning) to patients diagnosed with melanoma and treated with immunotherapy, reviewing 12 studies relevant to the topic published up to early 2022. The most commonly investigated imaging modality was CT imaging in isolation (
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.