Zobrazeno 1 - 10
of 143
pro vyhledávání: '"Tapio Pahikkala"'
Publikováno v:
BMC Bioinformatics, Vol 25, Iss 1, Pp 1-18 (2024)
Abstract The prediction of interactions between novel drugs and biological targets is a vital step in the early stage of the drug discovery pipeline. Many deep learning approaches have been proposed over the last decade, with a substantial fraction o
Externí odkaz:
https://doaj.org/article/1895d8144eab4277961995f33da5682e
Autor:
Parisa Movahedi, Valtteri Nieminen, Ileana Montoya Perez, Hiba Daafane, Dishant Sukhwal, Tapio Pahikkala, Antti Airola
Publikováno v:
IEEE Access, Vol 12, Pp 118637-118648 (2024)
Differentially private (DP) synthetic data has emerged as a potential solution for sharing sensitive individual-level biomedical data. DP generative models offer a promising approach for generating realistic synthetic data that aims to maintain the o
Externí odkaz:
https://doaj.org/article/d9c3a0691312462997bff20bffd13791
Autor:
Farhoud Hosseinpour, Ahmad Naebi, Seppo Virtanen, Tapio Pahikkala, Hannu Tenhunen, Juha Plosila
Publikováno v:
IEEE Access, Vol 9, Pp 152792-152802 (2021)
While the effectiveness of fog computing in Internet of Things (IoT) applications has been widely investigated in various studies, there is still a lack of techniques to efficiently utilize the computing resources in a fog platform to maximize Qualit
Externí odkaz:
https://doaj.org/article/0f252ff2db1a438eb308451a7bbb56d7
Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects
Autor:
Heli Julkunen, Anna Cichonska, Prson Gautam, Sandor Szedmak, Jane Douat, Tapio Pahikkala, Tero Aittokallio, Juho Rousu
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-11 (2020)
Combinatorial treatments have become a standard of care for various complex diseases including cancers. Here, the authors show that combinatorial responses of two anticancer drugs can be accurately predicted using factorization machines trained on la
Externí odkaz:
https://doaj.org/article/1dbe0a68db6948d0bdbef3a4f57cf4b3
Autor:
Riitta Mieronkoski, Elise Syrjälä, Mingzhe Jiang, Amir Rahmani, Tapio Pahikkala, Pasi Liljeberg, Sanna Salanterä
Publikováno v:
PLoS ONE, Vol 15, Iss 7, p e0235545 (2020)
The automatic detection of facial expressions of pain is needed to ensure accurate pain assessment of patients who are unable to self-report pain. To overcome the challenges of automatic systems for determining pain levels based on facial expressions
Externí odkaz:
https://doaj.org/article/03ca6422bd7f45ce9b8abf0935e5fc97
Autor:
Jussi Toivonen, Ileana Montoya Perez, Parisa Movahedi, Harri Merisaari, Marko Pesola, Pekka Taimen, Peter J Boström, Jonne Pohjankukka, Aida Kiviniemi, Tapio Pahikkala, Hannu J Aronen, Ivan Jambor
Publikováno v:
PLoS ONE, Vol 14, Iss 7, p e0217702 (2019)
PurposeTo develop and validate a classifier system for prediction of prostate cancer (PCa) Gleason score (GS) using radiomics and texture features of T2-weighted imaging (T2w), diffusion weighted imaging (DWI) acquired using high b values, and T2-map
Externí odkaz:
https://doaj.org/article/9a73bb362e4c4c12930ea10a6ebcf789
Autor:
Virpi Talman, Jaakko Teppo, Päivi Pöhö, Parisa Movahedi, Anu Vaikkinen, S. Tuuli Karhu, Kajetan Trošt, Tommi Suvitaival, Jukka Heikkonen, Tapio Pahikkala, Tapio Kotiaho, Risto Kostiainen, Markku Varjosalo, Heikki Ruskoaho
Publikováno v:
Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease, Vol 7, Iss 20 (2018)
Background The molecular mechanisms mediating postnatal loss of cardiac regeneration in mammals are not fully understood. We aimed to provide an integrated resource of mRNA, protein, and metabolite changes in the neonatal heart for identification of
Externí odkaz:
https://doaj.org/article/9482c6aaa55e4ff6836035f853b4f626
Autor:
Anna Cichonska, Balaguru Ravikumar, Elina Parri, Sanna Timonen, Tapio Pahikkala, Antti Airola, Krister Wennerberg, Juho Rousu, Tero Aittokallio
Publikováno v:
PLoS Computational Biology, Vol 13, Iss 8, p e1005678 (2017)
Due to relatively high costs and labor required for experimental profiling of the full target space of chemical compounds, various machine learning models have been proposed as cost-effective means to advance this process in terms of predicting the m
Externí odkaz:
https://doaj.org/article/7279e5f8bd5b43b087551e17292e5595
Autor:
Paavo Nevalainen, Aura Salmivaara, Jari Ala-Ilomäki, Samuli Launiainen, Juuso Hiedanpää, Leena Finér, Tapio Pahikkala, Jukka Heikkonen
Publikováno v:
Remote Sensing, Vol 9, Iss 12, p 1279 (2017)
The rut formation during forest operations is an undesirable phenomenon. A methodology is being proposed to measure the rut depth distribution of a logging site by photogrammetric point clouds produced by unmanned aerial vehicles (UAV). The methodolo
Externí odkaz:
https://doaj.org/article/8d51000e09cd48868ef7b9594634b0e5
Autor:
Sebastian Okser, Tapio Pahikkala, Antti Airola, Tapio Salakoski, Samuli Ripatti, Tero Aittokallio
Publikováno v:
PLoS Genetics, Vol 10, Iss 11, p e1004754 (2014)
Externí odkaz:
https://doaj.org/article/78e11b9c75764336959430dee0c652ce