Physician-Machine Interaction in the Decision Making Process.

decision support machine learning user interaction

Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
16 Jun 2020
Historique:
entrez: 24 6 2020
pubmed: 24 6 2020
medline: 26 8 2020
Statut: ppublish

Résumé

We propose an approach to decision support systems (DSS) that starts with the user first making their own unassisted decision αU and providing this decision as an input to the algorithm. Then, if the decision based of machine learning (ML) disagrees with the user's initial decision, it iteratively works with the user to converge to a common decision or at least make the user reconsider input values that are inconsistent with αU. We provide a detailed description of this approach along with examples, and then discuss potential benefits and limitations of this approach.

Identifiants

pubmed: 32570409
pii: SHTI200185
doi: 10.3233/SHTI200185
doi:

Types de publication

Journal Article

Langues

eng

Pagination

372-376

Auteurs

Saveli Goldberg (S)

Radiation Oncology Department, Massachusetts General Hospital, Boston, MA, USA.

Anatoly Temkin (A)

Department of Computer Science, Boston University Metropolitan College, MA, USA.

Benjamin Weisburd (B)

Broad Institute, Cambridge, MA, USA.

Articles similaires

Exploring blood-brain barrier passage using atomic weighted vector and machine learning.

Yoan Martínez-López, Paulina Phoobane, Yanaima Jauriga et al.
1.00
Blood-Brain Barrier Machine Learning Humans Support Vector Machine Software
Humans Medical Futility Turkey Qualitative Research Terminal Care

Understanding the role of machine learning in predicting progression of osteoarthritis.

Simone Castagno, Benjamin Gompels, Estelle Strangmark et al.
1.00
Humans Disease Progression Machine Learning Osteoarthritis
Humans Artificial Intelligence Neoplasms Prognosis Image Processing, Computer-Assisted

Classifications MeSH