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The Use of Artificial Intelligence (AI) in the Radiology Field: What Is the State of Doctor-Patient Communication in Cancer Diagnosis?
Derevianko, Alexandra; Pizzoli, Silvia Francesca Maria; Pesapane, Filippo; Rotili, Anna; Monzani, Dario; Grasso, Roberto; Cassano, Enrico; Pravettoni, Gabriella.
Afiliación
  • Derevianko A; Applied Research Division for Cognitive and Psychological Science, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Pizzoli SFM; Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy.
  • Pesapane F; Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20139 Milan, Italy.
  • Rotili A; Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20139 Milan, Italy.
  • Monzani D; Department of Psychology, Educational Science and Human Movement, University of Palermo, 90128 Palermo, Italy.
  • Grasso R; Applied Research Division for Cognitive and Psychological Science, IEO European Institute of Oncology IRCCS, 20141 Milan, Italy.
  • Cassano E; Department of Oncology and Hemato-Oncology, University of Milan, 20122 Milan, Italy.
  • Pravettoni G; Breast Imaging Division, IEO European Institute of Oncology IRCCS, 20139 Milan, Italy.
Cancers (Basel) ; 15(2)2023 Jan 12.
Article en En | MEDLINE | ID: mdl-36672417
ABSTRACT

BACKGROUND:

In the past decade, interest in applying Artificial Intelligence (AI) in radiology to improve diagnostic procedures increased. AI has potential benefits spanning all steps of the imaging chain, from the prescription of diagnostic tests to the communication of test reports. The use of AI in the field of radiology also poses challenges in doctor-patient communication at the time of the diagnosis. This systematic review focuses on the patient role and the interpersonal skills between patients and physicians when AI is implemented in cancer diagnosis communication.

METHODS:

A systematic search was conducted on PubMed, Embase, Medline, Scopus, and PsycNet from 1990 to 2021. The search terms were ("artificial intelligence" or "intelligence machine") and "communication" "radiology" and "oncology diagnosis". The PRISMA guidelines were followed.

RESULTS:

517 records were identified, and 5 papers met the inclusion criteria and were analyzed. Most of the articles emphasized the success of the technological support of AI in radiology at the expense of patient trust in AI and patient-centered communication in cancer disease. Practical implications and future guidelines were discussed according to the results.

CONCLUSIONS:

AI has proven to be beneficial in helping clinicians with diagnosis. Future research may improve patients' trust through adequate information about the advantageous use of AI and an increase in medical compliance with adequate training on doctor-patient diagnosis communication.
Palabras clave

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Systematic_reviews Idioma: En Revista: Cancers (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Italia

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Systematic_reviews Idioma: En Revista: Cancers (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Italia