Eklund M

Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction.

Olsson H, Kartasalo K, Mulliqi N, ..., Spjuth O, Eklund M

Nat Commun 13 (1) 7761 [2022-12-15; online 2022-12-15]

DDLS Fellow Kimmo Kartasalo

Detection of perineural invasion in prostate needle biopsies with deep neural networks.

Kartasalo K, Ström P, Ruusuvuori P, ..., Eklund M, Egevad L

Virchows Arch. 481 (1) 73-82 [2022-07-00; online 2022-04-21]

DDLS Fellow Kimmo Kartasalo

Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using co-expression-based convolutional neural networks.

Weitz P, Wang Y, Kartasalo K, ..., Eklund M, Rantalainen M

Bioinformatics 38 (13) 3462-3469 [2022-06-27; online 2022-05-21]

DDLS Fellow Kimmo Kartasalo

Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge.

Bulten W, Kartasalo K, Chen PC, ..., Eklund M, PANDA challenge consortium

Nat. Med. 28 (1) 154-163 [2022-01-00; online 2022-01-13]

DDLS Fellow Kimmo Kartasalo

OpenPhi: an interface to access Philips iSyntax whole slide images for computational pathology.

Mulliqi N, Kartasalo K, Olsson H, ..., Eklund M, Ruusuvuori P

Bioinformatics 37 (21) 3995-3997 [2021-11-05; online 2021-08-07]

DDLS Fellow Kimmo Kartasalo

The importance of study design in the application of artificial intelligence methods in medicine.

Eklund M, Kartasalo K, Olsson H, Ström P

NPJ Digit Med 2 (-) 101 [2019-10-18; online 2019-10-18]

DDLS Fellow Kimmo Kartasalo