Literature DB >> 31023041

Artificial intelligence in service of medicine.

O El-Hassoun, L Maruscakova, Z Valaskova, M Bucova, S Polak, I Hulin.   

Abstract

The race to make the dream of artificial intelligence a reality comes parallel with the increasing struggle of health care systems to cope with information overload and translational pressure. It is clear that a shift in the way data is generated requires a shift in the way they are processed. This is where AI comes with great promises to solve the problem of volume versus applicability of information in science. In medicine, AI is showing exponential progress in the fields of predictive analysis and image recognition. These promises however, come with an intricate package of ethico-social, scientific and economic implications, towards which a reductionist approach leads to distorted and dramatic predictions. All this, in a time when the growing pressure on healthcare systems towards defensive medicine begs the question of the true need for AI for good medical practice.This article examines the concept and achievements of AI and attempts to offer a complex view on the realistic expectations from it in medicine, in the context of current practice (Ref. 38). Keywords: algorithms, artificial intelligence, image recognition, neural networks, predictive analysis.

Mesh:

Year:  2019        PMID: 31023041     DOI: 10.4149/BLL_2019_028

Source DB:  PubMed          Journal:  Bratisl Lek Listy        ISSN: 0006-9248            Impact factor:   1.278


  2 in total

Review 1.  Current applications of artificial intelligence combined with urine detection in disease diagnosis and treatment.

Authors:  Jun Tan; Feng Qin; Jiuhong Yuan
Journal:  Transl Androl Urol       Date:  2021-04

2.  Automated classification of cancer from fine needle aspiration cytological image use neural networks: A meta-analysis.

Authors:  Jian Huang; Dongcun Wang; Jiping Da
Journal:  Diagn Cytopathol       Date:  2020-06-12       Impact factor: 1.390

  2 in total

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