ReviewJCO clinical cancer informatics2019
Decision Support Systems in Oncology.
Review in JCO clinical cancer informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 65 papers, 1 of them a synthesis that pooled it.
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
65 citing papers in PubMed, 1 synthesis or guideline pooled it, 159 citations in OpenAlex.
- Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.The Journal of pathology · 2019Guideline
- Development of a Comprehensive Decision Support Tool for Chemotherapy-Cycle Prescribing: Initial Usability Study.JMIR formative research · 2025Trial
- Role prompting modulates linguistic style but not clinical decision structure in GPT-5 tumour board simulation.NPJ digital medicine · 2026Article
- Real-World Barriers to and Facilitators of Implementing AI-Based Clinical Decision Support Systems: Scoping Review.JMIR medical informatics · 2026Article
- Towards an ecosystem of clinical decision support tools for precision cancer medicine.NPJ precision oncology · 2026Review
- Supporting Parental Decision-Making After Life-Limiting Fetal Diagnoses: The Role of Perinatal Hospice and the NOVA-L Decision Support System.Healthcare (Basel, Switzerland) · 2026Article
- Perceived Potential and Challenges of Supporting Coronary Artery Disease Treatment Decisions With AI: Qualitative Study.JMIR cardio · 2026Article
- Advancing the adoption of oncology decision support tools in Europe: insights from CAN.HEAL.Frontiers in digital health · 2026Article
- Data-Driven Culture in Medicine and Surgery: Policy Pathways to Learning Health Systems.International journal of general medicine · 2026Article
- Development of a Rule-Based Knowledge Base for Digitalization of Standard Operating Procedures on Radiotherapy in Breast Cancer.Oncology · 2026Article
- Disparities in access to systemic therapies for patients with hepatocellular carcinoma: an analysis from the International Liver Cancer Association.The Lancet regional health. Europe · 2025Review
- Using Artificial Intelligence to Develop Clinical Decision Support Systems-The Evolving Road of Personalized Oncologic Therapy.Diagnostics (Basel, Switzerland) · 2025Article
- Need Analysis of Clinician-Oriented Integrated Precision Oncology Decision Support Tools: Qualitative Descriptive Study.JMIR human factors · 2025Article
- Opportunities for Artificial Intelligence in Oncology: From the Lens of Clinicians and Patients.JCO oncology practice · 2025Review
- Harnessing Radiomics and Explainable AI for the Classification of Usual and Nonspecific Interstitial Pneumonia.Journal of clinical medicine · 2025Article
- Implicit versus explicit Bayesian priors for epistemic uncertainty estimation in clinical decision support.PLOS digital health · 2025Article
- Externally validated and clinically useful machine learning algorithms to support patient-related decision-making in oncology: a scoping review.BMC medical research methodology · 2025Article
- The initiation of the second-step intradisciplinary tumor board discussion and its impact on treatment decision. Retrospective data analysis of 12 years' experience in a tertiary oncology center.Frontiers in oncology · 2025Article
- AI and mental health: evaluating supervised machine learning models trained on diagnostic classifications.AI & society · 2025Article
- The Role of Artificial Intelligence on Tumor Boards: Perspectives from Surgeons, Medical Oncologists and Radiation Oncologists.Current oncology (Toronto, Ont.) · 2024Review
5 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Precision medicine is the future of health care: please watch the animation at https://vimeo.com/241154708 . As a technology-intensive and -dependent medical discipline, oncology will be at the vanguard of this impending change. However, to bring about precision medicine, a fundamental conundrum must be solved: Human cognitive capacity, typically constrained to five variables for decision making in the context of the increasing number of available biomarkers and therapeutic options, is a limiting factor to the realization of precision medicine. Given this level of complexity and the restriction of human decision making, current methods are untenable. A solution to this challenge is multifactorial decision support systems (DSSs), continuously learning artificial intelligence platforms that integrate all available data-clinical, imaging, biologic, genetic, cost-to produce validated predictive models. DSSs compare the personalized probable outcomes-toxicity, tumor control, quality of life, cost effectiveness-of various care pathway decisions to ensure optimal efficacy and economy. DSSs can be integrated into the workflows both strategically (at the multidisciplinary tumor board level to support treatment choice, eg, surgery or radiotherapy) and tactically (at the specialist level to support treatment technique, eg, prostate spacer or not). In some countries, the reimbursement of certain treatments, such as proton therapy, is already conditional on the basis that a DSS is used. DSSs have many stakeholders-clinicians, medical directors, medical insurers, patient advocacy groups-and are a natural consequence of big data in health care. Here, we provide an overview of DSSs, their challenges, opportunities, and capacity to improve clinical decision making, with an emphasis on the utility in oncology.
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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.