| nr |
titel |
auteur |
tijdschrift |
jaar |
jaarg. |
afl. |
pagina('s) |
type |
| 1 |
A deep-learning model to assist thyroid nodule diagnosis and management
|
Zhang, Bin
|
|
|
3 |
7 |
p. e410
|
artikel
|
| 2 |
A deep-learning model to assist thyroid nodule diagnosis and management
|
Lee, Joon-Hyop
|
|
|
3 |
7 |
p. e409
|
artikel
|
| 3 |
A deep-learning model to assist thyroid nodule diagnosis and management – Authors' reply
|
Liu, Yihao
|
|
|
3 |
7 |
p. e411-e412
|
artikel
|
| 4 |
An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: a national validation cohort study in England
|
Nafilyan, Vahé
|
|
|
3 |
7 |
p. e425-e433
|
artikel
|
| 5 |
An integrated nomogram combining deep learning, Prostate Imaging–Reporting and Data System (PI-RADS) scoring, and clinical variables for identification of clinically significant prostate cancer on biparametric MRI: a retrospective multicentre study
|
Hiremath, Amogh
|
|
|
3 |
7 |
p. e445-e454
|
artikel
|
| 6 |
Association between change in cardiovascular risk scores and future cardiovascular disease: analyses of data from the Whitehall II longitudinal, prospective cohort study
|
Lindbohm, Joni V
|
|
|
3 |
7 |
p. e434-e444
|
artikel
|
| 7 |
Correction to Lancet Digit Health 2021; 3: e250–59
|
|
|
|
3 |
7 |
p. e413
|
artikel
|
| 8 |
Correction to Lancet Digit Health 2021; 3: e360–70
|
|
|
|
3 |
7 |
p. e413
|
artikel
|
| 9 |
Correction to Lancet Digit Health 2021; 3: e317–29
|
|
|
|
3 |
7 |
p. e413
|
artikel
|
| 10 |
Effectiveness of an mHealth system on access to eye health services in Kenya: a cluster-randomised controlled trial
|
Rono, Hillary
|
|
|
3 |
7 |
p. e414-e424
|
artikel
|
| 11 |
Race representation matters in cancer care
|
The Lancet Digital Health,
|
|
|
3 |
7 |
p. e408
|
artikel
|
| 12 |
The hopes and hazards of using personal health technologies in the diagnosis and prognosis of infections
|
Radin, Jennifer M
|
|
|
3 |
7 |
p. e455-e461
|
artikel
|
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