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Martin Eklund
Martin Eklund
Professor of Epidemiology, Karolinska Institutet
Verified email at ki.se
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Cited by
Cited by
Year
Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci
FR Schumacher, AA Al Olama, SI Berndt, S Benlloch, M Ahmed, ...
Nature genetics 50 (7), 928-936, 2018
7602018
Factors contributing to healthcare professional burnout during the COVID-19 pandemic: A rapid turnaround global survey
LA Morgantini, U Naha, H Wang, S Francavilla, Ö Acar, JM Flores, ...
PloS one 15 (9), e0238217, 2020
6712020
Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study
P Ström, K Kartasalo, H Olsson, L Solorzano, B Delahunt, DM Berney, ...
The Lancet Oncology 21 (2), 222-232, 2020
4462020
Prostate cancer screening in men aged 50–69 years (STHLM3): a prospective population-based diagnostic study
H Grönberg, J Adolfsson, M Aly, T Nordström, P Wiklund, Y Brandberg, ...
The lancet oncology 16 (16), 1667-1676, 2015
4072015
Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction
DV Conti, BF Darst, LC Moss, EJ Saunders, X Sheng, A Chou, ...
Nature genetics 53 (1), 65-75, 2021
2972021
Artificial intelligence for diagnosis and Gleason grading of prostate cancer: the PANDA challenge
W Bulten, K Kartasalo, PHC Chen, P Ström, H Pinckaers, K Nagpal, Y Cai, ...
Nature medicine 28 (1), 154-163, 2022
2472022
MRI-targeted or standard biopsy in prostate cancer screening
M Eklund, F Jäderling, A Discacciati, M Bergman, M Annerstedt, M Aly, ...
New England journal of medicine 385 (10), 908-920, 2021
2402021
Comparison between the four-kallikrein panel and prostate health index for predicting prostate cancer
T Nordström, A Vickers, M Assel, H Lilja, H Grönberg, M Eklund
European urology 68 (1), 139-146, 2015
2332015
Breast cancer screening in the precision medicine era: risk-based screening in a population-based trial
Y Shieh, M Eklund, L Madlensky, SD Sawyer, CK Thompson, ...
Journal of the National Cancer Institute 109 (5), djw290, 2017
2172017
Prostate-specific antigen (PSA) density in the diagnostic algorithm of prostate cancer
T Nordström, O Akre, M Aly, H Grönberg, M Eklund
Prostate cancer and prostatic diseases 21 (1), 57-63, 2018
2012018
External evaluation of 3 commercial artificial intelligence algorithms for independent assessment of screening mammograms
M Salim, E Wåhlin, K Dembrower, E Azavedo, T Foukakis, Y Liu, K Smith, ...
JAMA oncology 6 (10), 1581-1588, 2020
1922020
Introducing conformal prediction in predictive modeling. A transparent and flexible alternative to applicability domain determination
U Norinder, L Carlsson, S Boyer, M Eklund
Journal of chemical information and modeling 54 (6), 1596-1603, 2014
1842014
Effect of artificial intelligence-based triaging of breast cancer screening mammograms on cancer detection and radiologist workload: a retrospective simulation study
K Dembrower, E Wåhlin, Y Liu, M Salim, K Smith, P Lindholm, M Eklund, ...
The Lancet Digital Health 2 (9), e468-e474, 2020
1782020
Polygenic risk score improves prostate cancer risk prediction: results from the Stockholm-1 cohort study
M Aly, F Wiklund, J Xu, WB Isaacs, M Eklund, M D'Amato, J Adolfsson, ...
European urology 60 (1), 21-28, 2011
1552011
Bioclipse: an open source workbench for chemo-and bioinformatics
O Spjuth, T Helmus, EL Willighagen, S Kuhn, M Eklund, J Wagener, ...
BMC bioinformatics 8, 1-10, 2007
1522007
Comparison of a deep learning risk score and standard mammographic density score for breast cancer risk prediction
K Dembrower, Y Liu, H Azizpour, M Eklund, K Smith, P Lindholm, F Strand
Radiology 294 (2), 265-272, 2020
1292020
Population-based screening for cancer: hope and hype
Y Shieh, M Eklund, GF Sawaya, WC Black, BS Kramer, LJ Esserman
Nature reviews Clinical oncology 13 (9), 550-565, 2016
1232016
Aggregate cost of mammography screening in the United States: comparison of current practice and advocated guidelines
C O'Donoghue, M Eklund, EM Ozanne, LJ Esserman
Annals of internal medicine 160 (3), 145-153, 2014
1162014
Artificial intelligence assistance significantly improves Gleason grading of prostate biopsies by pathologists
W Bulten, M Balkenhol, JJA Belinga, A Brilhante, A Çakır, L Egevad, ...
Modern Pathology 34 (3), 660-671, 2021
1142021
Choosing feature selection and learning algorithms in QSAR
M Eklund, U Norinder, S Boyer, L Carlsson
Journal of Chemical Information and Modeling 54 (3), 837-843, 2014
1112014
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