Evidence map›Paper›PMID 42799994›Full record

ReviewScandinavian journal of primary health care2026

Chest auscultation - tradition and expectations

Hasse Melbye, Carl Edvard Rudebeck, Hans Pasterkamp

Abstract readReview
In one paragraph

Review in Scandinavian journal of primary health care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Hasse MelbyeGeneral Practice Research Unit, Department of Community Medicine, Faculty of Health Sciences, UIT the Arctic University of Norway, Tromsø, Norway.ORCID 0000-0002-9773-3141
Carl Edvard RudebeckUiT Norges arktiske universitet, Västervik, Sweden.ORCID 0009-0006-7912-2140
Hans PasterkampDepartment of Pediatrics and Child Health, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada.ORCID 0000-0001-8611-2895

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AI-assisted digital stethoscopes can classify heart and lung sounds with accuracy comparable to or exceeding that of the average clinician and help the physician in the diagnostic process. With this essay we want to discuss benefits and downsides of this new technology. Will proficiency in auscultation, which brings joy and pride to many stethoscope users, be suffering when interpretation of chest sounds is taken over by AI? And how will recommendations from AI in the diagnostic process influence decision making and the patient-doctor relationship? A tendency toward deskilling of auscultation proficiency can be counteracted when AI-assisted interpretation is used as a reflective tool, comparing machine output against clinical perception to sharpen diagnostic acuity. This concept of a collaboration of humans and AI will be important with regard to keeping AI-algorithms trustworthy. We still need more research on heart and lung sounds, to gain a detailed understanding of the clinical significance of various sound characteristics. The smart stethoscope will be useful for this research. Better knowledge will benefit not only algorithm development but also clinicians using traditional stethoscopes. The traditional stethoscope will probably prevail as the main instruments for chest auscultation in foreseeable future. Smart stethoscopes may become useful tools in the education of their users.

Indexed as

Artificial IntelligenceAuscultationHeart AuscultationHeart SoundsRespiratory SoundsStethoscopesAlgorithmsHumansAuscultationchest diseasesheart soundslung soundsstethoscope

Identifiers

PMID42799994
PMCPMC13618091

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.