Literature DB >> 30911986

The day when computers read between lines.

Kei Yamada1, Susumu Mori2.   

Abstract

There is a growing notion that artificial general intelligence (AGI) will replace some of the work done by trained professionals, including physicians. This idea, however, seems to have logical leap; herein, we discuss three problems that are significant barriers to this. First, the ground truth is difficult to provide in the majority of medical conditions. Second, the electronic medical record (EMR) only covers a portion of the information that is crucial for patient care. This makes the data in the EMR a suboptimum material for creation of AGI. Third, there are decision-making processes that cannot be captured in a way that computers can digest; portions of our thoughts, perceptions, intuitions, and inspirations cannot be translated into numbers or words.

Entities:  

Keywords:  Artificial general intelligence; Artificial intelligence; Computer-aided diagnosis; Electronic medical record; MRI

Mesh:

Year:  2019        PMID: 30911986     DOI: 10.1007/s11604-019-00833-3

Source DB:  PubMed          Journal:  Jpn J Radiol        ISSN: 1867-1071            Impact factor:   2.374


  2 in total

1.  Celebrating the beginning of international journal collaboration.

Authors:  Shinji Naganawa; Yukunori Korogi
Journal:  Jpn J Radiol       Date:  2020-01       Impact factor: 2.374

2.  Computed tomography angiography lightbulb sign: Characteristic enhancement pattern on neck computed tomography angiography in differentiating paraganglioma from schwannoma of the carotid space.

Authors:  Suradech Suthiphosuwan; Helin D Bai; Eugene Yu; Aditya Bharatha
Journal:  Neuroradiol J       Date:  2020-05-14
  2 in total

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