Tuomo Hartonen

Phone0294125545, 0504486355
Emailtuomo.hartonenhelsinkifi

PL 63 (Haartmaninkatu 8)
00014
Finland
PL 63 (Haartmaninkatu 8), B525b
HELSINGIN YLIOPISTO
Finland

Research activity per year

Fields of Science

3111 Biomedicine

9 Article
1 Meeting Abstract
1 Comment/debate
1 Conference article
More
- 1 Doctoral Thesis

A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk
Jermy, B., Läll, K., Wolford, B. N., Wang, Y., Zguro, K., Cheng, Y., Kanai, M., Kanoni, S., Yang, Z., Hartonen, T., Monti, R., Wanner, J., Youssef, O., Lippert, C., van Heel, D., Okada, Y., McCartney, D. L., Hayward, C., Marioni, R. E. & Furini, S. & 10 others, Renieri, A., Martin, A. R., Neale, B. M., Hveem, K., Mägi, R., Palotie, A., Heyne, H., Mars, N., Ganna, A. & Ripatti, S., 2024, In: Nature Communications. 15, 1, 14 p., 5007.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
Comparison of disease prediction ability and transferability of polygenic scores vs. EHR-based score across three biobank studies, 1,034,311 individuals, and 18 diseases
Hartonen, T., Detrois, K., Teder-Laving, M., Lall, K., Yang, Z., Magi, R., Ripatti, S. & Ganna, A., Dec 2024, In: European Journal of Human Genetics. 32, p. 1716-1716 1 p.
Research output: Contribution to journal › Meeting Abstract › peer-review
Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker
Vabalas, A., Hartonen, T., Vartiainen, P., Jukarainen, S., Viippola, E., Rodosthenous, R. S., Liu, A., Hägg, S., Perola, M. & Ganna, A., 2024, In: Nature Aging. 4, p. 1014–1027 22 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning
Monti, R., Eick, L., Hudjashov, G., Läll, K., Kanoni, S., Wolford, B. N., Wingfield, B., Pain, O., Wharrie, S., Jermy, B., McMahon, A., Hartonen, T., Heyne, H., Mars, N., Lambert, S., Hveem, K., Inouye, M., van Heel, D. A., Mägi, R. & Marttinen, P. & 3 others, Ripatti, S., Ganna, A. & Lippert, C., 21 Jun 2024, In: American Journal of Human Genetics. 111, 7, p. 1431-1447 17 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File
Data Resource Profile: Nationwide registry data for high-throughput epidemiology and machine learning (FinRegistry)
Finn Gen, Viippola, E., Kuitunen, S., Rodosthenous, R. S., Vabalas, A., Hartonen, T., Vartiainen, P., Demmler, J., Vuorinen, A.-L., Liu, A., Havulinna, A. S., Llorens, V., Detrois, K. E., Wang, F., Ferro, M., Karvanen, A., German, J., Jukarainen, S., Gracia-Tabuenca, J. & Hiekkalinna, T. & 20 others, Koskelainen, S., Kiiskinen, T., Lahtela, E., Lemmelä, S., Paajanen, T., Siirtola, H., Reeve, M. P., Kristiansson, K., Brunfeldt, M., Aavikko, M., Perola, M., Ganna, A., Kaprio, J., Mäkitie, A., Tienari, P., Hovatta, I., Arvas, M., Hyvärinen, K., Ritari, J. & Partanen, J., 2 Aug 2023, In: International Journal of Epidemiology. 52, 4, p. e195–e200 6 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
File

1 Active

Development and prospective validation of a deep learning model to detect abnormal clinical laboratory measurements in the entire Finnish population
Ganna, A. (Project manager), Burian, J. (Participant), Cajuso Pons, T. (Participant), Hartonen, T. (Participant) & Zhu, M. (Participant)
Suomen Akatemia Projektilaskutus
01/09/2024 → 31/08/2028
Project: Research Council of Finland: Academy Project

Tuomo Hartonen

Personal profile

Fields of Science

International and National Collaboration

Dive into details

A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk

Comparison of disease prediction ability and transferability of polygenic scores vs. EHR-based score across three biobank studies, 1,034,311 individuals, and 18 diseases

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning

Data Resource Profile: Nationwide registry data for high-throughput epidemiology and machine learning (FinRegistry)

Development and prospective validation of a deep learning model to detect abnormal clinical laboratory measurements in the entire Finnish population

Tuomo Hartonen

Personal profile

Fields of Science

International and National Collaboration

Publications

A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk

Comparison of disease prediction ability and transferability of polygenic scores vs. EHR-based score across three biobank studies, 1,034,311 individuals, and 18 diseases

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker

Evaluation of polygenic scoring methods in five biobanks shows larger variation between biobanks than methods and finds benefits of ensemble learning

Data Resource Profile: Nationwide registry data for high-throughput epidemiology and machine learning (FinRegistry)

Projects

Development and prospective validation of a deep learning model to detect abnormal clinical laboratory measurements in the entire Finnish population