ReviewPostepy dermatologii i alergologii2021
Artificial intelligence in medicine and dermatology.
Review in Postepy dermatologii i alergologii, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Artificial Intelligence Models in the Diagnosis of Adult-Onset Dementia Disorders: A Review.Bioengineering (Basel, Switzerland) · 2022Review
- A study of attitudes among Polish dermatologists and dermatology trainees regarding modern technologies in medicine.Postepy dermatologii i alergologii · 2022Article
- Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Syria: A cross-sectional online survey.Frontiers in artificial intelligence · 2022Article
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As technology advances rapidly and vast amounts of data are collected, artificial intelligence (AI) is increasing its presence in our lives. Medicine is a major focus point of AI developers. There are examples of algorithms on par with medical professionals, the most prominent case being skin cancer recognition. However, advancement involves the necessity to adapt to technology and to patients utilizing it on a daily basis. What is more, patients present growing trust towards machine-aided health care. Dermatology is a potent field for AI use as visual data are easy to collect, hold a lot of information and are paramount for diagnosis.
Indexed as
Identifiers
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.