Evidence map›Paper›PMID 35781249›Full record

ArticleBritish journal of haematology2022

Integrating artificial intelligence into haematology training and practice: Opportunities, threats and proposed solutions.

Shang Yuin Chai, Amjad Hayat, Gerard Thomas Flaherty

Open access · hybridAbstract read
In one paragraph

Article in British journal of haematology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 16% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

  1. Pooled it
  2. Hematology-Oncology Fellows' Use of Artificial Intelligence: A Multicenter Educational Practice and Needs Assessment Survey.Journal of cancer education : the official journal of the American Association for Cancer Education · 2026
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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

3 authors at 1 institution in 1 country.

Shang Yuin ChaiDepartment of Haematology, University Hospital Galway, Galway, Ireland.
Amjad HayatDepartment of Haematology, University Hospital Galway, Galway, Ireland.
Gerard Thomas FlahertySchool of Medicine, National University of Ireland Galway, Galway, Ireland.ORCID 0000-0002-5987-1658
Ollscoil na Gaillimhe – University of Galway · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There remains a limited emphasis on the use beyond the research domain of artificial intelligence (AI) in haematology and it does not feature significantly in postgraduate medical education and training. This perspective article considers recent developments in the field of AI research in haematology and anticipates the potential benefits and risks associated with its deeper integration into the specialty. Anxiety towards the greater use of AI in healthcare stems from legitimate concerns surrounding data protection, lack of transparency in clinical decision-making, and erosion of the doctor-patient relationship. The specialty of haematology has successfully embraced multiple disruptive innovations. We are at the cusp of a new era of closer integration of AI into routine haematology practice that will ultimately benefit patient care but to harness its benefits the next generation of haematologists will need access to bespoke learning opportunities with input from data scientists.

Indexed as

Artificial IntelligenceHematologyHumansPhysician-Patient Relationsclinical decision supporthaematological malignancieshaemoglobinopathiesmachine learningmedical educationstem cell transplantation

Identifiers

PMID35781249
PMCPMC9543760
OpenAlexW4283795334

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.