Artificial intelligence-enabled decision support in nephrology.
Journal
Nature reviews. Nephrology
ISSN: 1759-507X
Titre abrégé: Nat Rev Nephrol
Pays: England
ID NLM: 101500081
Informations de publication
Date de publication:
07 2022
07 2022
Historique:
accepted:
16
03
2022
pubmed:
24
4
2022
medline:
24
6
2022
entrez:
23
4
2022
Statut:
ppublish
Résumé
Kidney pathophysiology is often complex, nonlinear and heterogeneous, which limits the utility of hypothetical-deductive reasoning and linear, statistical approaches to diagnosis and treatment. Emerging evidence suggests that artificial intelligence (AI)-enabled decision support systems - which use algorithms based on learned examples - may have an important role in nephrology. Contemporary AI applications can accurately predict the onset of acute kidney injury before notable biochemical changes occur; can identify modifiable risk factors for chronic kidney disease onset and progression; can match or exceed human accuracy in recognizing renal tumours on imaging studies; and may augment prognostication and decision-making following renal transplantation. Future AI applications have the potential to make real-time, continuous recommendations for discrete actions and yield the greatest probability of achieving optimal kidney health outcomes. Realizing the clinical integration of AI applications will require cooperative, multidisciplinary commitment to ensure algorithm fairness, overcome barriers to clinical implementation, and build an AI-competent workforce. AI-enabled decision support should preserve the pre-eminence of wisdom and augment rather than replace human decision-making. By anchoring intuition with objective predictions and classifications, this approach should favour clinician intuition when it is honed by experience.
Identifiants
pubmed: 35459850
doi: 10.1038/s41581-022-00562-3
pii: 10.1038/s41581-022-00562-3
pmc: PMC9379375
mid: NIHMS1828770
doi:
Types de publication
Journal Article
Review
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
452-465Subventions
Organisme : NIA NIH HHS
ID : RF1 AG058469
Pays : United States
Organisme : NIBIB NIH HHS
ID : R21 EB027344
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK127139
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS120924
Pays : United States
Organisme : NIA NIH HHS
ID : R56 AG058469
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH121923
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK121730
Pays : United States
Organisme : NIH HHS
ID : S10 OD026880
Pays : United States
Organisme : NIA NIH HHS
ID : RF1 AG059319
Pays : United States
Organisme : NIDDK NIH HHS
ID : K01 DK120784
Pays : United States
Organisme : NIGMS NIH HHS
ID : K23 GM140268
Pays : United States
Organisme : NIGMS NIH HHS
ID : R01 GM110240
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL155915
Pays : United States
Organisme : NIBIB NIH HHS
ID : R01 EB029699
Pays : United States
Organisme : NIDDK NIH HHS
ID : K23 DK124645
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK123078
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG011407
Pays : United States
Informations de copyright
© 2022. Springer Nature Limited.
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