Evidence map›Paper›PMID 38810186›Full record

ReviewThe New England journal of medicine2024

Medical Artificial Intelligence and Human Values.

Kun-Hsing Yu, Elizabeth Healey, Tze-Yun Leong, Isaac S Kohane, Arjun K Manrai

Abstract readReview
In one paragraph

Review in The New England journal of medicine, 2024. 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.

0numbers the graph read from it
0cells of the map it votes in
65citing papers in PubMed, 1 pooled it
–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

65 citing papers in PubMed, 1 synthesis or guideline pooled it.

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5 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Kun-Hsing YuFrom the Department of Biomedical Informatics, Harvard Medical School (K.-H.Y., E.H., I.S.K., A.K.M.), the Department of Pathology, Brigham and Women's Hospital (K.-H.Y.), and the Harvard-MIT Division of Health Sciences and Technology (E.H.) - all in Boston; and the School of Computing, National University of Singapore, Singapore (T.-Y.L.).ORCID 0000-0001-9892-8218
Elizabeth HealeyFrom the Department of Biomedical Informatics, Harvard Medical School (K.-H.Y., E.H., I.S.K., A.K.M.), the Department of Pathology, Brigham and Women's Hospital (K.-H.Y.), and the Harvard-MIT Division of Health Sciences and Technology (E.H.) - all in Boston; and the School of Computing, National University of Singapore, Singapore (T.-Y.L.).
Tze-Yun LeongFrom the Department of Biomedical Informatics, Harvard Medical School (K.-H.Y., E.H., I.S.K., A.K.M.), the Department of Pathology, Brigham and Women's Hospital (K.-H.Y.), and the Harvard-MIT Division of Health Sciences and Technology (E.H.) - all in Boston; and the School of Computing, National University of Singapore, Singapore (T.-Y.L.).
Isaac S KohaneFrom the Department of Biomedical Informatics, Harvard Medical School (K.-H.Y., E.H., I.S.K., A.K.M.), the Department of Pathology, Brigham and Women's Hospital (K.-H.Y.), and the Harvard-MIT Division of Health Sciences and Technology (E.H.) - all in Boston; and the School of Computing, National University of Singapore, Singapore (T.-Y.L.).
Arjun K ManraiFrom the Department of Biomedical Informatics, Harvard Medical School (K.-H.Y., E.H., I.S.K., A.K.M.), the Department of Pathology, Brigham and Women's Hospital (K.-H.Y.), and the Harvard-MIT Division of Health Sciences and Technology (E.H.) - all in Boston; and the School of Computing, National University of Singapore, Singapore (T.-Y.L.).ORCID 0000-0001-9657-9800

Funding

Robust, Generalizable, and Fair Machine Learning Models for BiomedicineR35GM142879 · NIGMS · HARVARD MEDICAL SCHOOL · PI YU, KUN-HSING · 2021 to 2025
$2.4M
Mitigating Hematologic Adverse Events in Patients with Myeloid Malignancies: A Novel Causal Artificial Intelligence ApproachR01HL174679 · NHLBI · HARVARD MEDICAL SCHOOL · PI Kun-Hsing Yu · 2024 to 2026
$2.3M
NHLBI NIH HHS R01 HL174679NIGMS NIH HHS R35 GM142879
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Artificial IntelligenceClinical Decision-MakingSocial ValuesBiasClinical ReasoningHumansLanguageRisk

Identifiers

PMID38810186
PMCPMC12425466

What OpenQuestion holds

Textmetadata
LicenceTDM
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.