Evidence map›Paper›PMID 40869512›Full record

ReviewJournal of clinical medicine2025

Genomic Evaluation of AML-Main Techniques and Novel Approaches.

Dinnar Yahya, Milena Stoyanova, Mari Hachmeriyan, Mariya Levkova

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Journal of clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. CharacterizingCancers · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Dinnar YahyaDepartment of Medical Genetics, Faculty of Medicine, Medical University of Varna, 9000 Varna, Bulgaria.ORCID 0000-0002-3410-5033
Milena StoyanovaDepartment of Medical Genetics, Faculty of Medicine, Medical University of Varna, 9000 Varna, Bulgaria.
Mari HachmeriyanDepartment of Medical Genetics, Faculty of Medicine, Medical University of Varna, 9000 Varna, Bulgaria.ORCID 0000-0002-8847-4651
Mariya LevkovaDepartment of Medical Genetics, Faculty of Medicine, Medical University of Varna, 9000 Varna, Bulgaria.ORCID 0000-0002-9358-7263

Funding

European Union-NextGenerationEU, through the National Recovery and Resilience Plan of the Republic of Bulgaria; Scientific Group 3.1.6. BG-RRP-2.004-0009-C02
6 · The paper itself

Abstract

The genetic diversity of acute myeloid leukemia creates a major obstacle for current research and clinical practice. Despite advances in molecular genetic techniques, various omics approaches, and artificial intelligence, developing a universal algorithm to thoroughly assess each clinical case remains difficult. Starting with current recommendations and classifications, this narrative review highlights the most important diagnostic options available today, new opportunities that are emerging, and the challenges in diagnosing and managing this complex disease.

Indexed as

acute myeloid leukemiaartificial intelligencegenetic markersmachine learningnext-generation sequencing

Identifiers

PMID40869512
PMCPMC12386541

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.