ArticleAcademic medicine : journal of the Association of American Medical Colleges2023
To Operate or Not? Balancing Advanced Imaging, Machine Learning, and the Doctor-Patient Relationship in Complex Clinical Decision Making.
Article in Academic medicine : journal of the Association of American Medical Colleges, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed, 5 citations in OpenAlex.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
Advances in high-resolution, cross-sectional imaging have changed the practice of medicine. These innovations have clearly benefited patient care yet have also led to a decreased dependence on the art of medicine, with its emphasis on obtaining a thoughtful history and thorough physical examination to elicit the same diagnosis that imaging provides. What remains to be determined is how physicians can balance these technological advances with their own ability to use clinical experience and judgment. This can be seen not only with the use of high-level imaging but also with the increasing use of machine-learning models throughout medicine. The authors contend that these should be seen not as a replacement for the physician, but as another tool in their arsenal in determining management decisions. These issues are salient for surgeons, who, given the serious undertaking required to operate on a person, must develop trust-based relationship with their patients. Navigating this new field brings with it several ethical conundrums that must be addressed, with the final goal being to provide optimal patient care without sacrificing the human element involved, from either the physician or the patient. The authors examine these less-than-simple challenges, which will continue to develop as physicians use the increasing amount of machine-based knowledge available to them.
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What OpenQuestion holds
Registered trials
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.