| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
Are CT-based exacerbation prediction models ready for use in chronic obstructive pulmonary disease?
|
Makimoto, Kalysta
|
|
|
5 |
2 |
p. e54-e55
|
artikel
|
| 2 |
Automated deep brain stimulation programming based on electrode location: a randomised, crossover trial using a data-driven algorithm
|
Roediger, Jan
|
|
|
5 |
2 |
p. e59-e70
|
artikel
|
| 3 |
Correction to Lancet Digit Health 2022; 4: e727–37
|
|
|
|
5 |
2 |
p. e58
|
artikel
|
| 4 |
Implementing automation in deep brain stimulation: has the time come?
|
Bonizzato, Marco
|
|
|
5 |
2 |
p. e52-e53
|
artikel
|
| 5 |
Interpretable deep learning model to predict the molecular classification of endometrial cancer from haematoxylin and eosin-stained whole-slide images: a combined analysis of the PORTEC randomised trials and clinical cohorts
|
Fremond, Sarah
|
|
|
5 |
2 |
p. e71-e82
|
artikel
|
| 6 |
Multiomics single timepoint measurements to predict severe COVID-19
|
Tegethoff, Sina A
|
|
|
5 |
2 |
p. e56
|
artikel
|
| 7 |
Multiomics single timepoint measurements to predict severe COVID-19 – Authors' reply
|
Garapati, Kishore
|
|
|
5 |
2 |
p. e57
|
artikel
|
| 8 |
Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study
|
Chaudhary, Muhammad F A
|
|
|
5 |
2 |
p. e83-e92
|
artikel
|
| 9 |
Secondary data for global health digitalisation
|
Näher, Anatol-Fiete
|
|
|
5 |
2 |
p. e93-e101
|
artikel
|
| 10 |
Technology for world elimination of neglected tropical diseases
|
The Lancet Digital Health,
|
|
|
5 |
2 |
p. e51
|
artikel
|
Tijdschrift beschrijving