Literature DB >> 32006241

Artificial intelligence: Who is responsible for the diagnosis?

Emanuele Neri1, Francesca Coppola2, Vittorio Miele3, Corrado Bibbolino4, Roberto Grassi5.   

Abstract

The aim of the paper is to find an answer to the question "Who or what is responsible for the benefits and harms of using artificial intelligence in radiology?" When human beings make decisions, the action itself is normally connected with a direct responsibility by the agent who generated the action. You have an effect on others, and therefore, you are responsible for what you do and what you decide to do. But if you do not do this yourself, but an artificial intelligence system, it becomes difficult and important to be able to ascribe responsibility when something goes wrong. The manuscript addresses the following statements: (1) using AI, the radiologist is responsible for the diagnosis; (2) radiologists must be trained on the use of AI since they are responsible for the actions of machines; (3) radiologists involved in R&D have the responsibility to guide the respect of rules for a trustworthy AI; (4) radiologist responsibility is at risk of validating the unknown (black box); (5) radiologist decision may be biased by the AI automation; (6)risk of a paradox: increasing AI tools to compensate the lack of radiologists; (7) need of informed consent and quality measures. Future legislation must outline the contours of the professional's responsibility, with respect to the provision of the service performed autonomously by AI, balancing the professional's ability to influence and therefore correct the machine, limiting the sphere of autonomy that instead technological evolution would like to recognize to robots.

Entities:  

Keywords:  Artificial Intelligence; Ethics; Radiology; Robotics

Mesh:

Year:  2020        PMID: 32006241     DOI: 10.1007/s11547-020-01135-9

Source DB:  PubMed          Journal:  Radiol Med        ISSN: 0033-8362            Impact factor:   3.469


  31 in total

1.  FLORA software: semi-automatic LGE-CMR analysis tool for cardiac lesions identification and characterization.

Authors:  Silvia Pradella; Lorenzo Nicola Mazzoni; Mayla Letteriello; Paolo Tortoli; Silvia Bettarini; Cristian De Amicis; Giulia Grazzini; Simone Busoni; Pierpaolo Palumbo; Giacomo Belli; Vittorio Miele
Journal:  Radiol Med       Date:  2022-04-18       Impact factor: 3.469

2.  Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs): a radiomic model to predict tumor grade.

Authors:  Giuditta Chiti; Giulia Grazzini; Federica Flammia; Benedetta Matteuzzi; Paolo Tortoli; Silvia Bettarini; Elisa Pasqualini; Vincenza Granata; Simone Busoni; Luca Messserini; Silvia Pradella; Daniela Massi; Vittorio Miele
Journal:  Radiol Med       Date:  2022-08-02       Impact factor: 6.313

Review 3.  A narrative review on current imaging applications of artificial intelligence and radiomics in oncology: focus on the three most common cancers.

Authors:  Simone Vicini; Chandra Bortolotto; Marco Rengo; Daniela Ballerini; Davide Bellini; Iacopo Carbone; Lorenzo Preda; Andrea Laghi; Francesca Coppola; Lorenzo Faggioni
Journal:  Radiol Med       Date:  2022-06-30       Impact factor: 6.313

Review 4.  Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature.

Authors:  Eleonora Bicci; Cosimo Nardi; Leonardo Calamandrei; Michele Pietragalla; Edoardo Cavigli; Francesco Mungai; Luigi Bonasera; Vittorio Miele
Journal:  Cancers (Basel)       Date:  2022-05-16       Impact factor: 6.575

Review 5.  Machine Learning for Renal Pathologies: An Updated Survey.

Authors:  Roberto Magherini; Elisa Mussi; Yary Volpe; Rocco Furferi; Francesco Buonamici; Michaela Servi
Journal:  Sensors (Basel)       Date:  2022-07-01       Impact factor: 3.847

Review 6.  Radiomics in medical imaging: pitfalls and challenges in clinical management.

Authors:  Roberta Fusco; Vincenza Granata; Giulia Grazzini; Silvia Pradella; Alessandra Borgheresi; Alessandra Bruno; Pierpaolo Palumbo; Federico Bruno; Roberta Grassi; Andrea Giovagnoni; Roberto Grassi; Vittorio Miele; Antonio Barile
Journal:  Jpn J Radiol       Date:  2022-03-28       Impact factor: 2.701

Review 7.  Dynamic contrast-enhanced (DCE) imaging: state of the art and applications in whole-body imaging.

Authors:  Domenico Albano; Federico Bruno; Andrea Agostini; Salvatore Alessio Angileri; Massimo Benenati; Giulia Bicchierai; Michaela Cellina; Vito Chianca; Diletta Cozzi; Ginevra Danti; Federica De Muzio; Letizia Di Meglio; Francesco Gentili; Giuliana Giacobbe; Giulia Grazzini; Irene Grazzini; Pasquale Guerriero; Carmelo Messina; Giuseppe Micci; Pierpaolo Palumbo; Maria Paola Rocco; Roberto Grassi; Vittorio Miele; Antonio Barile
Journal:  Jpn J Radiol       Date:  2021-12-24       Impact factor: 2.374

8.  Artificial Intelligence in Radiology-Ethical Considerations.

Authors:  Adrian P Brady; Emanuele Neri
Journal:  Diagnostics (Basel)       Date:  2020-04-17

9.  Implementation of artificial intelligence (AI) applications in radiology: hindering and facilitating factors.

Authors:  Lea Strohm; Charisma Hehakaya; Erik R Ranschaert; Wouter P C Boon; Ellen H M Moors
Journal:  Eur Radiol       Date:  2020-05-26       Impact factor: 5.315

Review 10.  Large Bowel Ischemia/Infarction: How to Recognize It and Make Differential Diagnosis? A Review.

Authors:  Francesca Iacobellis; Donatella Narese; Daniela Berritto; Antonio Brillantino; Marco Di Serafino; Susanna Guerrini; Roberta Grassi; Mariano Scaglione; Maria Antonietta Mazzei; Luigia Romano
Journal:  Diagnostics (Basel)       Date:  2021-05-30
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