| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
Achieving accurate estimates of fetal gestational age and personalised predictions of fetal growth based on data from an international prospective cohort study: a population-based machine learning study
|
Fung, Russell
|
|
|
2 |
7 |
p. e368-e375
|
artikel
|
| 2 |
A deep learning algorithm to detect anaemia with ECGs: a retrospective, multicentre study
|
Kwon, Joon-myoung
|
|
|
2 |
7 |
p. e358-e367
|
artikel
|
| 3 |
A deep neural network trained to interpret results from electrocardiograms: better than physicians?
|
Sinnecker, Daniel
|
|
|
2 |
7 |
p. e332-e333
|
artikel
|
| 4 |
Africa's COVID-19 health technologies' watershed moment
|
Adepoju, Paul
|
|
|
2 |
7 |
p. e346-e347
|
artikel
|
| 5 |
Artificial intelligence in health care: value for whom?
|
Zeitoun, Jean-David
|
|
|
2 |
7 |
p. e338-e339
|
artikel
|
| 6 |
Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study
|
Zhu, Hongling
|
|
|
2 |
7 |
p. e348-e357
|
artikel
|
| 7 |
Deep learning models to detect hidden clinical correlates
|
Ouyang, David
|
|
|
2 |
7 |
p. e334-e335
|
artikel
|
| 8 |
Deep learning using electrocardiographs
|
The Lancet Digital Health,
|
|
|
2 |
7 |
p. e331
|
artikel
|
| 9 |
Fetal growth and gestational age prediction by machine learning
|
Ananth, Cande V
|
|
|
2 |
7 |
p. e336-e337
|
artikel
|
| 10 |
Genotyping SARS-CoV-2 through an interactive web application
|
Maan, Hassaan
|
|
|
2 |
7 |
p. e340-e341
|
artikel
|
| 11 |
Sharing patient-level real-time COVID-19 data
|
Komorowski, Matthieu
|
|
|
2 |
7 |
p. e345
|
artikel
|
| 12 |
The European artificial intelligence strategy: implications and challenges for digital health
|
Cohen, I Glenn
|
|
|
2 |
7 |
p. e376-e379
|
artikel
|
| 13 |
The need for privacy with public digital contact tracing during the COVID-19 pandemic
|
Bengio, Yoshua
|
|
|
2 |
7 |
p. e342-e344
|
artikel
|
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