ArticleCancers2022
An Artificial Intelligence-Based Tool for Data Analysis and Prognosis in Cancer Patients: Results from the Clarify Study.
Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed, 45 citations in OpenAlex.
- Applications of Artificial Intelligence in Cancer Diagnosis and Treatment.Cancer medicine · 2026Review
- Artificial intelligence in cancer diagnosis and therapy using sex and gender as precision biomarkers.Discover oncology · 2026Review
- Artificial Intelligence inCancers · 2026Review
- Artificial Intelligence-Based Wearable Sensing Technologies for the Management of Cancer, Diabetes, and COVID-19.Biosensors · 2025Review
- Advances in Artificial Intelligence (AI) Models and Generative Algorithms Represent a New Paradigm for Genomics Research.International journal of molecular sciences · 2025Review
- Artificial intelligence in neuro-oncology: methodological bases, practical applications and ethical and regulatory issues.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025Review
- Wearable Technologies in Head and Neck Oncology: Scoping Review.JMIR mHealth and uHealth · 2025Article
- Review
- Target identification of natural products in cancer with chemical proteomics and artificial intelligence approaches.Cancer biology & medicine · 2025Review
- Importance of Health Economics and Outcomes Research in the Product Lifecycle.Pharmaceutical medicine · 2025Review
- Personalised Risk Modelling for Older Adult Cancer Survivors: Combining Wearable Data and Self-Reported Measures to Address Time-Varying Risks.Sensors (Basel, Switzerland) · 2025Article
- A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer.Cancers · 2025Review
- Patient Consent and The Right to Notice and Explanation of AI Systems Used in Health Care.The American journal of bioethics : AJOB · 2025Article
- Single center experience of the impact of artificial intelligence image analysis software on short-term prognosis of non-small cell lung cancer.Frontiers in oncology · 2025Article
- Integrating Artificial Intelligence-Driven Wearable Technology in Oncology Decision-Making: A Narrative Review.Oncology · 2025Review
- GPT-based prediction of short-term survival following decompressive hemicraniectomy in malignant middle cerebral artery infarction.Frontiers in neurology · 2025Article
- Data Analytics to Support Policy Making for Noncommunicable Diseases: Scoping Review.Online journal of public health informatics · 2024Article
- Controlling Nutritional Status (CONUT) Score is Associated with Overall Survival in Patients with Hepatocellular Carcinoma Treated with Conventional Transcatheter Arterial Chemoembolization: A Propensity Score Matched Analysis.Cardiovascular and interventional radiology · 2024Article
- Risk Management and Patient Safety in the Artificial Intelligence Era: A Systematic Review.Healthcare (Basel, Switzerland) · 2024Review
- New regulatory thinking is needed for AI-based personalised drug and cell therapies in precision oncology.NPJ precision oncology · 2024Review
Corrections and comments
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Authors and funding
16 authors at 8 institutions in 4 countries.
Funding
Abstract
backgroundArtificial intelligence (AI) has contributed substantially in recent years to the resolution of different biomedical problems, including cancer. However, AI tools with significant and widespread impact in oncology remain scarce. The goal of this study is to present an AI-based solution tool for cancer patients data analysis that assists clinicians in identifying the clinical factors associated with poor prognosis, relapse and survival, and to develop a prognostic model that stratifies patients by risk. MATERIALS AND
methodsWe used clinical data from 5275 patients diagnosed with non-small cell lung cancer, breast cancer, and non-Hodgkin lymphoma at Hospital Universitario Puerta de Hierro-Majadahonda. Accessible clinical parameters measured with a wearable device and quality of life questionnaires data were also collected.
resultsUsing an AI-tool, data from 5275 cancer patients were analyzed, integrating clinical data, questionnaires data, and data collected from wearable devices. Descriptive analyses were performed in order to explore the patients' characteristics, survival probabilities were calculated, and a prognostic model identified low and high-risk profile patients.
conclusionOverall, the reconstruction of the population's risk profile for the cancer-specific predictive model was achieved and proved useful in clinical practice using artificial intelligence. It has potential application in clinical settings to improve risk stratification, early detection, and surveillance management of cancer patients.
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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.