ArticleHaematologica2019
Machine learning reveals chronic graft-
Article in Haematologica, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A Systematic Review of Machine Learning Techniques in Hematopoietic Stem Cell Transplantation (HSCT).Sensors (Basel, Switzerland) · 2020Pooled it
- Critical care in hematopoietic stem cell transplantation: Common complications and management.World journal of critical care medicine · 2026Review
- Extracorporeal Photopheresis for Chronic Graft-Versus-Host Disease According to 2014 NIH Consensus Criteria.Journal of clinical apheresis · 2025Article
- Blood proteomics for quantitative biomarkers of cellular therapies.Biomarker research · 2025Review
- Distinct type 1 immune networks underlie the severity of restrictive lung disease after COVID-19.Nature immunology · 2025Article
- Transparency and Representation in Clinical Research Utilizing Artificial Intelligence in Oncology: A Scoping Review.Cancer medicine · 2025Article
- The Applications of Machine Learning in the Management of Patients Undergoing Stem Cell Transplantation: Are We Ready?Cancers · 2025Review
- Programmable biomaterials for bone regeneration.Materials today. Bio · 2024Review
- Oral Chronic Graft-Versus-Host Disease: Pathogenesis, Diagnosis, Current Treatment, and Emerging Therapies.International journal of molecular sciences · 2024Review
- Longitudinal clinical data improve survival prediction after hematopoietic cell transplantation using machine learning.Blood advances · 2024Article
- Chronic graft-versus-host disease. Part I: Epidemiology, pathogenesis, and clinical manifestations.Journal of the American Academy of Dermatology · 2024Review
- Optimization of diagnosis and treatment of hematological diseases via artificial intelligence.Frontiers in medicine · 2024Review
- Anti-Idiotypic mRNA Vaccine to Treat Autoimmune Disorders.Vaccines · 2023Review
- Chronic GvHD NIH Consensus Project Biology Task Force: evolving path to personalized treatment of chronic GvHD.Blood advances · 2023Article
- Expanding Personalized, Data-Driven Dermatology: Leveraging Digital Health Technology and Machine Learning to Improve Patient Outcomes.JID innovations : skin science from molecules to population health · 2022Review
- Establishment of a predictive model for GVHD-free, relapse-free survival after allogeneic HSCT using ensemble learning.Blood advances · 2022Article
- Prediction and recommendation by machine learning through repetitive internal validation for hepatic veno-occlusive disease/sinusoidal obstruction syndrome and early death after allogeneic hematopoietic cell transplantation.Bone marrow transplantation · 2022Article
- A Clinical Prognostic Model Based on Machine Learning from the Fondazione Italiana Linfomi (FIL) MCL0208 Phase III Trial.Cancers · 2021Article
- Methods to Assess Disease Activity and Severity in Cutaneous Chronic Graft-versus-Host Disease: A Critical Literature Review.Transplantation and cellular therapy · 2021Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
The application of machine learning in medicine has been productive in multiple fields, but has not previously been applied to analyze the complexity of organ involvement by chronic graft-
Indexed as
Identifiers
What Socratic 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 Socratic graph.