Artificial intelligence powers digital medicine

doi:10.1038/s41746-017-0012-2

Review

. 2018 Mar 14:1:5.

doi: 10.1038/s41746-017-0012-2. eCollection 2018.

Artificial intelligence powers digital medicine

Alexander L Fogel¹, Joseph C Kvedar^{2

3

4}

Affiliations

¹ 1Stanford University School of Medicine, Stanford, CA USA.
² 2Department of Dermatology, Massachusetts General Hospital, Boston, MA USA.
³ 3Harvard Medical School, Boston, MA USA.
⁴ 4Partners Connected Health, Partners Healthcare, Boston, MA USA.

PMID: 31304291
PMCID: PMC6548340
DOI: 10.1038/s41746-017-0012-2

Review

Artificial intelligence powers digital medicine

Alexander L Fogel et al. NPJ Digit Med. 2018.

. 2018 Mar 14:1:5.

doi: 10.1038/s41746-017-0012-2. eCollection 2018.

Authors

Alexander L Fogel¹, Joseph C Kvedar^{2

3

4}

Affiliations

¹ 1Stanford University School of Medicine, Stanford, CA USA.
² 2Department of Dermatology, Massachusetts General Hospital, Boston, MA USA.
³ 3Harvard Medical School, Boston, MA USA.
⁴ 4Partners Connected Health, Partners Healthcare, Boston, MA USA.

PMID: 31304291
PMCID: PMC6548340
DOI: 10.1038/s41746-017-0012-2

Abstract

Artificial intelligence (AI) has recently surpassed human performance in several domains, and there is great hope that in healthcare, AI may allow for better prevention, detection, diagnosis, and treatment of disease. While many fear that AI will disrupt jobs and the physician-patient relationship, we believe that AI can eliminate many repetitive tasks to clear the way for human-to-human bonding and the application of emotional intelligence and judgment. We review several recent studies of AI applications in healthcare that provide a view of a future where healthcare delivery is a more unified, human experience.

Keywords: Epidemiology.

PubMed Disclaimer

Conflict of interest statement

Competing interestsJoseph C. Kvedar is an advisor to Claritas Mindsciences, Wave Edge Capital, PureTech, and MD Revolution. The remaining author declares no competing financial interests.

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References

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[1] Stanford University. One Hundred Year Study onArtificial Intelligence. Online (2015).

[2] Stanford University. One Hundred Year Study onArtificial Intelligence. Online (2015).

[3] Darcy AM, Louie AK, Roberts LW. Machine learning and the profession of medicine. JAMA. 2016;315:551. doi: 10.1001/jama.2015.18421. - DOI - PubMed

[4] Darcy AM, Louie AK, Roberts LW. Machine learning and the profession of medicine. JAMA. 2016;315:551. doi: 10.1001/jama.2015.18421. - DOI - PubMed

[5] Grace, K., Salvatier, J., Dafoe, A., Zhang, B. & Evans, O. When will AI exceed human performance? Evidence from AI experts. arXiv. Online. (2017).

[6] Grace, K., Salvatier, J., Dafoe, A., Zhang, B. & Evans, O. When will AI exceed human performance? Evidence from AI experts. arXiv. Online. (2017).

[7] Abbo ED, Zhang Q, Zelder M, Huang ES. The increasing number of clinical items addressed during the time of adult primary care visits. J. Gen. Intern. Med. 2008;23:2058–2065. doi: 10.1007/s11606-008-0805-8. - DOI - PMC - PubMed

[8] Abbo ED, Zhang Q, Zelder M, Huang ES. The increasing number of clinical items addressed during the time of adult primary care visits. J. Gen. Intern. Med. 2008;23:2058–2065. doi: 10.1007/s11606-008-0805-8. - DOI - PMC - PubMed

[9] Annals of Medicine & Www Annfammed Tethered to the EHR: primary care physician work-load assessment using EHR event log data and time-motion observations. Ann. Fam. Med.1515, 419–426 (2017). - PMC - PubMed

[10] Annals of Medicine & Www Annfammed Tethered to the EHR: primary care physician work-load assessment using EHR event log data and time-motion observations. Ann. Fam. Med.1515, 419–426 (2017). - PMC - PubMed

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Artificial intelligence powers digital medicine

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Artificial intelligence powers digital medicine

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