Artificial intelligence outperforms human students in conducting neurosurgical audits

Brzezicki, Maksymilian A.; Bridger, Nicholas E.; Kobetić, Matthew David; Ostrowski, Maciej; Grabowski, Waldemar; Gill, Simran; Neumann, Sandra

doi:10.1016/j.clineuro.2020.105732

Cited by 19 publications

(13 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The US Tampa General Hospital has deployed a similar technology at entrances to the hospital to conduct a facial thermal scan and detect other symptoms of COVID-19 including sweat and discoloration, as well as other autonomous monitoring of staff and patients that facilitates track and trace efforts and authorises and tracks access to restricted areas (HBR, 2020 [18]). A possible AI application for protecting health care providers involves intelligent robots developed by Boston Dynamics and MIT and deployed at the Brigham and Women's Hospital and Massachusetts General Hospital to perform tasks such as obtaining vital signs or delivering medications to patients in surge clinics and inpatient wards (Boston Dynamics, 2020 [19]).…”

Section: Ai Applications Are Also Emerging To Protect Health Care Providers From Sars-cov-2 Infectionmentioning

confidence: 99%

Laying the foundations for artificial intelligence in health

Hashiguchi

Slawomirski²,

Oderkirk

2021

OECD Health Working Papers

View full text Add to dashboard Cite

systems/health-working-papers.htm JT03477600 OFDE This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. 2  DELSA/HEA/WD/HWP(2021)5 OECD HEALTH WORKING PAPER NO. 128 UnclassifiedOECD Health Working Papers http://www.oecd.org/els/health-systems/health-working-papers.htm OECD Working Papers should not be reported as representing the official views of the OECD or of its member countries. The opinions expressed and arguments employed are those of the author(s).Working Papers describe preliminary results or research in progress by the author(s) and are published to stimulate discussion on a broad range of issues on which the OECD works. Comments on Working Papers are welcomed, and may be sent to health.contact@oecd.org. This series is designed to make available to a wider readership selected health studies prepared for use within the OECD. Authorship is usually collective, but principal writers are named. The papers are generally available only in their original language -English or Frenchwith a summary in the other. This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area.The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.

show abstract

Section: Ai Applications Are Also Emerging To Protect Health Care Providers From Sars-cov-2 Infectionmentioning

confidence: 99%

Laying the foundations for artificial intelligence in health

Hashiguchi

Slawomirski²,

Oderkirk

2021

OECD Health Working Papers

View full text Add to dashboard Cite

show abstract

“…; objects: cars, buildings, dogs, churches, statues, etc.) [3][4][5], automatic diagnosis and prognosis of diseases has even surpassed the performance of human experts in some domains [6][7][8], etc. This success, coupled with the increasing pervasiveness of powerful computing devices and the dramatic improvement in the user-friendliness of technology in general, is having a positive impact on inter-disciplinary research, with a growing interest in the application of modern computer science in other scientific fields, as well as in the arts and humanities [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Images of Roman Imperial Denarii: A Curated Data Set for the Evaluation of Computer Vision Algorithms Applied to Ancient Numismatics, and an Overview of Challenges in the Field

Arandjelović

Zachariou

2020

Sci

View full text Add to dashboard Cite

Automatic ancient Roman coin analysis only recently emerged as a topic of computer science research. Nevertheless, owing to its ever-increasing popularity, the field is already reaching a certain degree of maturity, as witnessed by a substantial publication output in the last decade. At the same time, it is becoming evident that research progress is being limited by a somewhat veering direction of effort and the lack of a coherent framework which facilitates the acquisition and dissemination of robust, repeatable, and rigorous evidence. Thus, in the present article, we seek to address several associated challenges. To start with, (i) we provide a first overview and discussion of different challenges in the field, some of which have been scarcely investigated to date, and others which have hitherto been unrecognized and unaddressed. Secondly, (ii) we introduce the first data set, carefully curated and collected for the purpose of facilitating methodological evaluation of algorithms and, specifically, the effects of coin preservation grades on the performance of automatic methods. Indeed, until now, only one published work at all recognized the need for this kind of analysis, which, to any numismatist, would be a trivially obvious fact. We also discuss a wide range of considerations which had to be taken into account in collecting this corpus, explain our decisions, and describe its content in detail. Briefly, the data set comprises 100 different coin issues, all with multiple examples in Fine, Very Fine, and Extremely Fine conditions, giving a total of over 650 different specimens. These correspond to 44 issuing authorities and span the time period of approximately 300 years (from 27 BC until 244 AD). In summary, the present article should be an invaluable resource to researchers in the field, and we encourage the community to adopt the collected corpus, freely available for research purposes, as a standard evaluation benchmark.

show abstract

“…It is no longer an exaggeration to say that computer vision is pervasive in everyday life: Face detection [1,2] has been a standard feature of digital cameras and smartphones for well over a decade, online image depositories are increasingly successful at categorizing images by their semantic content (scene: Beach, city, countryside, etc; objects: Cars, buildings, dogs, churches, statues, etc.) [3,4], automatic diagnosis and prognosis of diseases has even surpassed the performance of human experts in some domains [5][6][7], etc. This success, coupled with the increasing pervasiveness of powerful computing devices and the dramatic improvement in user-friendliness of technology in general, is having a positive impact on inter-disciplinary research, with a growing interest in the application of modern computer science in other scientific fields, as well as in the arts and humanities [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Images of Roman Imperial Denarii: A Curated Data Set for the Evaluation of Computer Vision Algorithms Applied to Ancient Numismatics, and an Overview of Challenges in the Field

Arandjelović¹,

Zachariou²

2020

Sci

View full text Add to dashboard Cite

Automatic ancient Roman coin analysis only recently emerged as a topic of computer science research. Nevertheless, owing to its ever-increasing popularity, the field is already reaching a certain degree of maturity, as witnessed by a substantial publication output in the last decade. At the same time, it is becoming evident that research progress is being limited by a somewhat veering direction of effort and the lack of a coherent framework which facilitates the acquisition and dissemination of robust, repeatable, and rigorous evidence. Thus, in the present article, we seek to address several associated challenges. To start with, (i) we provide a first overview and discussion of different challenges in the field, some of which have been scarcely investigated to date, and others which have hitherto been unrecognized and unaddressed. Secondly, (ii) we introduce the first data set, carefully curated and collected for the purpose of facilitating methodological evaluation of algorithms and, specifically, the effects of coin preservation grades on the performance of automatic methods. Indeed, until now, only one published work at all recognized the need for this kind of analysis, which, to any numismatist, would be a trivially obvious fact. We also discuss a wide range of considerations which had to be taken into account in collecting this corpus, explain our decisions, and describe its content in detail. Briefly, the data set comprises 100 different coin types, all with multiple examples in Fine, Very Fine, and Extremely Fine conditions, giving a total of over 650 different specimens. These correspond to 44 issuing authorities and span the time period of approximately 300 years (from 27 BC until 244 AD). In summary, the present article should be an invaluable resource to researchers in the field, and we encourage the community to adopt the collected corpus, freely available for research purposes, as a standard evaluation benchmark.

show abstract

Artificial intelligence outperforms human students in conducting neurosurgical audits

Cited by 19 publications

References 10 publications

Laying the foundations for artificial intelligence in health

Laying the foundations for artificial intelligence in health

Images of Roman Imperial Denarii: A Curated Data Set for the Evaluation of Computer Vision Algorithms Applied to Ancient Numismatics, and an Overview of Challenges in the Field

Images of Roman Imperial Denarii: A Curated Data Set for the Evaluation of Computer Vision Algorithms Applied to Ancient Numismatics, and an Overview of Challenges in the Field

Contact Info

Product

Resources

About