Evidence map›Paper›PMID 40866573›Full record

ReviewNPJ digital medicine2025

The algorithmic consultant: a new era of clinical AI calls for a new workforce of physician-algorithm specialists.

Jayson S Marwaha, William Yuan, Mukund Poddar, Pansy Elsamadisi, Gabriel A Brat

Abstract readReview
In one paragraph

Review in NPJ digital medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

5 authors.

Jayson S MarwahaDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA. jaysonm@med.umich.edu.
William YuanDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Mukund PoddarDepartment of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, MA, USA.
Pansy ElsamadisiDepartment of Pharmacy, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Gabriel A BratDepartment of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.

Funding

RESEARCH TRAINING-MEDICAL INFORMATICS 90T15LM007092 · NLM · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Nils Gehlenborg · 1992 to 2026
$32.8M
RESEARCH TRAINING IN PEDIATRIC EMERGENCY MEDICINET32HD040128 · NICHD · CHILDREN'S HOSPITAL BOSTON · PI Kenneth D. Mandl · 2001 to 2026
$5.0M
Eunice Kennedy Shriver National Institute of Child Health and Human Development T32HD040128Harvard Medical School Blavatnik Pilot GrantNICHD NIH HHS T32 HD040128NLM NIH HHS T15 LM007092U.S. National Library of Medicine T15LM007092
6 · The paper itself

Abstract

As complex AI systems become more common in clinical decision-making, a new type of physician-data science specialist is needed to bridge the gap between these AI tools and practicing clinicians. Analogous to how clinical pharmacists currently guide appropriate medication use and govern a hospital's formulary, this specialist would offer point-of-care guidance on AI tool selection and interpretation, and manage a hospital's AI systems. This role aims to enable safe and effective clinical AI by collaborating with patient-facing providers to ensure appropriate model application in the real world.

Identifiers

PMID40866573
PMCPMC12391404

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.