Stebėti
Martin Eklund
Martin Eklund
Professor of Epidemiology, Karolinska Institutet
Patvirtintas el. paštas ki.se
Pavadinimas
Cituota
Cituota
Metai
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
7712018
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
6972020
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
4552020
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
4112015
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
3092021
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
2572022
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
2512021
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
2362015
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
2202017
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
2042018
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
2002020
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
1872020
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
1852014
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
1562011
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
1322020
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
1252016
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
1182014
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
1172021
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
1122014
Sistema negali atlikti operacijos. Bandykite vėliau dar kartą.
Straipsniai 1–20