ArticleMedical science monitor : international medical journal of experimental and clinical research2024
Editorial: Artificial Intelligence (AI), Digital Image Analysis, and the Future of Cancer Diagnosis and Prognosis.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed.
- A guide to cancer screening.Nature reviews. Clinical oncology · 2026Review
- A Review of Circulating Tumor DNA (ctDNA) and the Liquid Biopsy in Cancer Diagnosis, Screening, and Monitoring Treatment Response.Medical science monitor : international medical journal of experimental and clinical research · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
On October 8 2024, the Royal Swedish Academy of Sciences announced the 2024 Nobel Prize in Physics was awarded to Hopfield and Hinton for their foundation research on machine learning with artificial neural networks, which resulted in the current applications for artificial intelligence (AI). Digital diagnostic histopathology combines image capture with image analysis and uses digital tools to collect, analyze, and share diagnostic information. An increase in chronic diseases, diagnostic departmental workloads, and diagnostic tests to support targeted therapy in cancer patients have driven the use and development of image analysis systems, and several medical device companies have recently developed whole-slide scanning devices. In April 2017, the US Food and Drug Administration (FDA) permitted marketing authorization for the first whole slide imaging (WSI) system. During 2024, large-scale studies from several cancer centers have shown the potential for diagnostic reporting for real-world data and whole-slide modeling to develop validated diagnostic AI algorithms. This editorial discusses why recent advances and applications in AI and digital image analysis may have an important future role in cancer diagnosis and prognosis.
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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.