ReviewCancer innovation2022
Applications of digital Medicine in oncology: Prospects and challenges.
Review in Cancer innovation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed, 23 citations in OpenAlex.
- Review
- The Impact of Diet on Long-Term Oncological Outcomes: Investigating Nutritional Mechanisms in Cancer Prevention Management and Prognosis.Nutrients · 2026Review
- An Integrative Review of Computational Methods Applied to Biomarkers, Psychological Metrics, and Behavioral Signals for Early Cancer Risk Detection.Bioengineering (Basel, Switzerland) · 2025Article
- Digital Therapeutics in Cardiovascular Healthcare: A Narrative Review.Current cardiology reports · 2025Review
- Article
- Recent advances in nanoultrasonography for the diagnosis and treatment of gastrointestinal diseases.Nanomedicine (London, England) · 2025Review
- Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation.Frontiers in digital health · 2025Review
- Oncogenic potential of SARS-CoV-2-targeting hallmarks of cancer pathways.Cell communication and signaling : CCS · 2024Review
- Internet of Medical Things and Healthcare 4.0: Trends, Requirements, Challenges, and Research Directions.Sensors (Basel, Switzerland) · 2023Review
- Applications of digital Medicine in oncology: Prospects and challenges.Cancer innovation · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The current state of oncology medical services is not encouraging and is unable to fully meet the needs of patients with cancer. In recent years, rapidly developing artificial intelligence technology and gradual advancements in mobile phones, sensors, and wearable devices, which have made these more compact, affordable, and popular, have greatly expanded the development of digital medicine. Digital medicine refers to clinical evidence-based technology and products with a direct impact on disease management and research. Integrating digital medicine into clinical practice has the advantages of broader applicability, greater cost-effectiveness, better accessibility, and improved diagnostic and therapeutic performance. Digital medicine has emerged in different clinical application scenarios, including cancer prevention, screening, diagnosis, and treatment, as well as clinical trials. Additionally, big data generated from digital medicine can be used to improve levels of clinical diagnosis and treatment. However, digital medicine also faces many challenges, including security regulation and privacy protection, product usability, data management, and optimization of algorithms. In summary, the application and development of digital medicine in the field of cancer face numerous opportunities and challenges.
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.