Artificial Intelligence in Current Diabetes Management and Prediction.
Purpose Of Review: Artificial intelligence (AI) can make advanced inferences based on a large amount of data. The mainstream technologies of the AI boom in 2021 are machine learning (ML) and deep learning, which have made significant progress due to the increase in computational resources accompanie...
| Publicado en: | Current Diabetes Reports Vol. 21; no. 12; pp. 1 - 7 |
|---|---|
| Autores principales: | , , , , |
| Formato: | research review Journal Article |
| Publicado: |
Springer Nature
Dec2021
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=154921776&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 154921776 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15344827 3H8T jtl: Current Diabetes Reports issn: 15344827 maglogo: N pubinfo: dt: Dec2021 vid: 21 iid: 12 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 154921776 154921776 NLM34902070 154921776 10.1007/s11892-021-01423-2 NLM34902070 154921776 ppf: 1 ppct: 6 formats: tig: atl: Artificial Intelligence in Current Diabetes Management and Prediction. aug: au: Nomura, Akihiro Noguchi, Masahiro Kometani, Mitsuhiro Furukawa, Kenji Yoneda, Takashi affil: Department of Biomedical Informatics, CureApp Institute, Karuizawa, Japan sug: subj: Diabetes Mellitus Therapy Diabetes Mellitus Diagnosis Artificial Intelligence Human United States Comparative Studies Multicenter Studies Evaluation Research Validation Studies Scales ab: Purpose Of Review: Artificial intelligence (AI) can make advanced inferences based on a large amount of data. The mainstream technologies of the AI boom in 2021 are machine learning (ML) and deep learning, which have made significant progress due to the increase in computational resources accompanied by the dramatic improvement in computer performance. In this review, we introduce AI/ML-based medical devices and prediction models regarding diabetes.Recent Findings: In the field of diabetes, several AI-/ML-based medical devices and regarding automatic retinal screening, clinical diagnosis support, and patient self-management tool have already been approved by the US Food and Drug Administration. As for new-onset diabetes prediction using ML methods, its performance is not superior to conventional risk stratification models that use statistical approaches so far. Despite the current situation, it is expected that the predictive performance of AI will soon be maximized by a large amount of organized data and abundant computational resources, which will contribute to a dramatic improvement in the accuracy of disease prediction models for diabetes. pubtype: Academic Journal doctype: research review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|