Evidence map›Paper›PMID 39758456›Full record

ArticleMedical science educator2024

Preparing Physicians of the Future: Incorporating Data Science into Medical Education.

Rishi M Shah, Kavya M Shah, Piroz Bahar, Cornelius A James

Abstract readEditorial
PubMed Full text at PMC Publisher
In one paragraph

Article in Medical science educator, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Rishi M ShahDepartment of Applied Mathematics, Yale College, New Haven, CT USA.ORCID 0009-0006-8515-5192
Kavya M ShahDepartment of Clinical Neurosciences, University of Cambridge, Hills Road, Cambridge, England CB2 0QQ UK.ORCID 0000-0002-8722-4095
Piroz BaharUniversity of Michigan Medical School, Ann Arbor, MI USA.
Cornelius A JamesDepartment of Internal Medicine, Pediatrics, and Learning Health Sciences, University of Michigan Medical School, Ann Arbor, MI USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The recent excitement surrounding artificial intelligence (AI) in health care underscores the importance of physician engagement with new technologies. Future clinicians must develop a strong understanding of data science (DS) to further enhance patient care. However, DS remains largely absent from medical school curricula, even though it is recognized as vital by medical students and residents alike. Here, we evaluate the current DS landscape in medical education and illustrate its impact in medicine through examples in pathology classification and sepsis detection. We also explore reasons for the exclusion of DS and propose solutions to integrate it into existing medical education frameworks.

Indexed as

Clinical informaticsData scienceEvidence-based medicineMedical education

Identifiers

PMID39758456
PMCPMC11699019

What OpenQuestion holds

Textmetadata
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.