| Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms T Schaffter, DSM Buist, CI Lee, Y Nikulin, D Ribli, Y Guan, W Lotter, Z Jie, ... JAMA network open 3 (3), e200265-e200265, 2020 | 367 | 2020 |
| Common and unique components of inhibition and working memory: an fMRI, within-subjects investigation F McNab, G Leroux, F Strand, L Thorell, S Bergman, T Klingberg Neuropsychologia 46 (11), 2668-2682, 2008 | 289 | 2008 |
| 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 | 224 | 2020 |
| 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 | 216 | 2020 |
| Toward robust mammography-based models for breast cancer risk A Yala, PG Mikhael, F Strand, G Lin, K Smith, YL Wan, L Lamb, K Hughes, ... Science Translational Medicine 13 (578), eaba4373, 2021 | 160 | 2021 |
| 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 | 140 | 2020 |
| Multi-institutional validation of a mammography-based breast cancer risk model A Yala, PG Mikhael, F Strand, G Lin, S Satuluru, T Kim, I Banerjee, ... Journal of Clinical Oncology 40 (16), 1732-1740, 2022 | 120 | 2022 |
| Artificial intelligence for breast cancer detection in screening mammography in Sweden: a prospective, population-based, paired-reader, non-inferiority study K Dembrower, A Crippa, E Colón, M Eklund, F Strand The Lancet Digital Health 5 (10), e703-e711, 2023 | 108 | 2023 |
| Phonological working memory with auditory presentation of pseudo-words—an event related fMRI Study F Strand, H Forssberg, T Klingberg, F Norrelgen Brain research 1212, 48-54, 2008 | 102 | 2008 |
| A multi-million mammography image dataset and population-based screening cohort for the training and evaluation of deep neural networks—the cohort of screen-aged women (CSAW) K Dembrower, P Lindholm, F Strand Journal of digital imaging 33 (2), 408-413, 2020 | 75 | 2020 |
| Optimizing risk-based breast cancer screening policies with reinforcement learning A Yala, PG Mikhael, C Lehman, G Lin, F Strand, YL Wan, K Hughes, ... Nature medicine 28 (1), 136-143, 2022 | 64 | 2022 |
| Identification of women at high risk of breast cancer who need supplemental screening M Eriksson, K Czene, F Strand, S Zackrisson, P Lindholm, K Lång, ... Radiology 297 (2), 327-333, 2020 | 58 | 2020 |
| Standalone AI for breast cancer detection at screening digital mammography and digital breast tomosynthesis: a systematic review and meta-analysis JH Yoon, F Strand, PAT Baltzer, EF Conant, FJ Gilbert, CD Lehman, ... Radiology 307 (5), e222639, 2023 | 54 | 2023 |
| Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL W Li, DC Newitt, J Gibbs, LJ Wilmes, EF Jones, VA Arasu, F Strand, ... NPJ breast cancer 6 (1), 63, 2020 | 54 | 2020 |
| The future of breast cancer screening: what do participants in a breast cancer screening program think about automation using artificial intelligence? O Jonmarker, F Strand, Y Brandberg, P Lindholm Acta radiologica open 8 (12), 2058460119880315, 2019 | 37 | 2019 |
| Range of radiologist performance in a population-based screening cohort of 1 million digital mammography examinations M Salim, K Dembrower, M Eklund, P Lindholm, F Strand Radiology 297 (1), 33-39, 2020 | 30 | 2020 |
| Novel mammographic image features differentiate between interval and screen-detected breast cancer: a case-case study F Strand, K Humphreys, A Cheddad, S Törnberg, E Azavedo, J Shepherd, ... Breast Cancer Research 18, 1-10, 2016 | 28 | 2016 |
| Patchdropout: Economizing vision transformers using patch dropout Y Liu, C Matsoukas, F Strand, H Azizpour, K Smith Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 24 | 2023 |
| Breast MRI during neoadjuvant chemotherapy: lack of background parenchymal enhancement suppression and inferior treatment response N Onishi, W Li, DC Newitt, RJ Harnish, F Strand, AAT Nguyen, VA Arasu, ... Radiology 301 (2), 295-308, 2021 | 21 | 2021 |
| Evaluation of combined artificial intelligence and radiologist assessment to interpret screening mammograms. JAMA Netw Open. 2020; 3 (3): e200265 T Schaffter, DSM Buist, CI Lee, Y Nikulin, D Ribli, Y Guan, W Lotter, Z Jie, ... | 21 | 2020 |
Kevin SmithAssociate Professor, KTH Royal Institute of Technology & Science for Life LaboratoryZweryfikowany adres z kth.se
