The utility of artificial intelligence in the assessment of prostate pathology. Egevad L, Strom P, Kartasalo K, Olsson H, Samaratunga H, Delahunt B, Eklund M. Histopathology 2020;76;790-792.

Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading. Egevad L, SwanbergD, Delahunt B, Strom P, Kartasalo K, Olsson H, Berney DM, Bostwick DG, Evans AJ, Humphrey PA, Iczkowski KA, Kench JG, Kristiansen G, Leite KRM, McKenney JK, Oxley J, Pan CC, Samaratunga H, Srigley JR, Takahashi H, Tsuzuki T, van der Kwast T, Varma M, Zhou M, Clements M, Eklund M. Virchows Arch 2020;477;777-786.

Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study. Strom P, Kartasalo K, Olsson H, Solorzano L, Delahunt B, Berney DM, Bostwick DG, Evans AJ, Grignon DJ, Humphrey PA, Iczkowski KA, Kench JG, Kristiansen G, van der Kwast TH, Leite KRM, McKenney JK, Oxley J, Pan CC, Samaratunga H, Srigley JR, Takahashi H, Tsuzuki T, Varma M, Zhou M, Lindberg J, Lindskog C, Ruusuvuori P, Wahlby C, Gronberg H, Rantalainen M, Egevad L, Eklund M. Lancet Oncol 2020;21;222-232.

Prognostic value of perineural invasion in prostate needle biopsies: a population-based study of patients treated by radical prostatectomy. Strom P, Nordstrom T, Delahunt B, Samaratunga H, Gronberg H, Egevad L, Eklund M. J Clin Pathol 2020;73;630-635.

Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists. Bulten W, Balkenhol M, BelingaJA, Brilhante A, Cakir A, Egevad L, Eklund M, Farre X, Geronatsiou K, Molinie V, Pereira G, Roy P, Saile G, Salles P, Schaafsma E, Tschui J, Vos AM, Panel IPIE, van Boven H, Vink R, van der Laak J, Hulsbergen-van der Kaa C, Litjens G. Mod Pathol 2021;34;660-671.

Interobserver reproducibility of perineural invasion of prostatic adenocarcinoma in needle biopsies. Egevad L, Delahunt B, Samaratunga H, Tsuzuki T, Olsson H, Strom P, Lindskog C, Hakkinen T, Kartasalo K, Eklund M, Ruusuvuori P. Virchows Arch 2021;478;1109-1116.

The emerging role of artificial intelligence in the reporting of prostate pathology. Egevad L, Delahunt B, Samaratunga H, Tsuzuki T, Yamamoto Y, Yaxley J, Ruusuvuori P, Kartasalo K, Eklund M. Pathology 2021;53;565-567.

Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps. Kartasalo K, Bulten W, Delahunt B, Chen PC, Pinckaers H, Olsson H, Ji X, Mulliqi N, Samaratunga H, Tsuzuki T, Lindberg J, Rantalainen M, Wahlby C, Litjens G, Ruusuvuori P, Egevad L, Eklund M. Eur Urol Focus 2021;7;687-691.

OpenPhi: An interface to access Philips iSyntax whole slide images for computational pathology. Mulliqi N, Kartasalo K, Olsson H, Ji X, Egevad L, Eklund M, Ruusuvuori P. Bioinformatics 2021.

Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer: the PANDA challenge. Bulten W, Cameron Chen PH, Ström P, Pinckaers H, Nagpal K, Cai Y, Steiner DF, van Boven H, Vink R, Hulsbergen-van de Kaa C, van der Laak J, Amin MB, Evans AJ, van der Kwast T, Allan R, Humphrey PA, Grönberg H, Samaratunga H, Delahunt B, Tsuzuki T, Häkkinen T, Egevad L, et al. Nature Medicine 2022; 28;154-163.

Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction. Olsson H, Kartasalo K, Mulliqi N, Capuccini M, Ruusuvuori P, Samaratunga H, Delahunt B, Lindskog C, Janssen EAM, Blilie A; ISUP Prostate Imagebase Expert Panel; Egevad L, Spjuth O, Eklund M. Nat Commun 2022;13;7761

Interobserver Reproducibility of Cribriform Cancer in Prostate Needle Biopsies. Egevad L et al, Histopathology (in press).

Challenges in grading of prostate cancer. Disagreement among expert pathologists and results of artificial intelligence assisted grading. Egevad L, Swanberg O, Delahunt B, Ström P, Kartasalo K, Olsson H, Berney D.M, Bostwick D.G, Evans A.J, Humphrey P.A, Iczkowski K.A, Kench J.G, Kristiansen G, Leite K.R.M, McKenney J, Oxley J, Pan C, Samaratunga H, Srigley J.R, Takahashi H, Tsuzuki T, van der Kwast T, Varma M, Zhou M, Clements M, and Eklund, M. Virchows Arch. 2020, 477(6):777-786

The importance of study design in the application of artificial intelligence methods in medicine. Eklund M, Kartasalo K, Olsson H, and Ström P. npj Digital Medicine, 2019, 2:101.