Riku Klén

Are Quantitative Errors Reduced with Time-of-Flight Reconstruction When Using Imperfect MR-Based Attenuation Maps for F-18-FDG PET/MR Neuroimaging? (2022)

Applied Sciences

Lindén Jani, Teuho Jarmo, Klén Riku, Teräs Mika

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Evaluation of three methods for delineation and attenuation estimation of the sinus region in MR-based attenuation correction for brain PET-MR imaging (2022)

BMC Medical Imaging

Lindén Jani, Teuho Jarmo, Teräs Mika, Klén Riku

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Advanced pattern recognition tools for disease diagnosis (2022)

Subasi Abdulhamit, Panigrahi Siba Smarak, Patil Bhalchandra Sunil, Canbaz Abdullah, Klén Riku

(Kirjan tai muun kokoomateoksen osa (B2))

Development and evaluation of a machine learning-based in-hospital COVID-19 disease outcome predictor (CODOP): A multicontinental retrospective study (2022)

eLife

Klen Riku, Purohit Disha, Gomez-Huelgas Ricardo, Casas-Rojo Jose Manuel, Anton-Santos Juan Miguel, Nunez-Cortes Jesus Millan, Lumbreras Carlos, Ramos-Rincon Jose Manuel, Garcia Barrio Noelia, Pedrera-Jimenez Miguel, Lalueza Blanco Antonio, Martin-Escalante Maria Dolores, Rivas-Ruiz Francisco, Onieva-Garcia Maria angeles, Young Pablo, Ramirez Juan Ignacio, Titto Omonte Estela Edith, Gross Artega Rosmery, Canales Beltran Magdy Teresa, Valdez Pascual Ruben, Pugliese Florencia, Castagna Rosa, Huespe Ivan A., Boietti Bruno, Pollan Javier A., Funke Nico, Leiding Benjamin, Gomez-Varela David

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Classification of ischemia from myocardial polar maps in 15 O-H 2 O cardiac perfusion imaging using a convolutional neural network (2022)

Scientific Reports

Teuho Jarmo, Schultz Jussi, Klén Riku, Knuuti Juhani, Saraste Antti, Ono Naoaki, Kanaya Shigehiko

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Classification of ischemia from myocardial polar maps in 15 O-H 2 O cardiac perfusion imaging using a convolutional neural network (2022)

Scientific Reports

Teuho Jarmo, Schultz Jussi, Klén Riku, Knuuti Juhani, Saraste Antti, Ono Naoaki, Kanaya Shigehiko

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Artificial Intelligence to Improve Risk Prediction with Nuclear Cardiac Studies (2022)

Current Cardiology Reports

Juarez-Orozco Luis Eduardo, Klén Riku, Niemi Mikael, Ruijsink Bram, Daquarti Gustavo, van Es Rene, Benjamins Jan-Walter, Yeung Ming Wai, van der Harst Pim, Knuuti Juhani

(Vertaisarvioitu katsausartikkeli tieteellisessä aikakauslehdessä (A2))

Novel Classification of ischemia from myocardial polar maps in 15O–H2O cardiac perfusion imaging using a convolutional neural network (2022)

Scientific Reports

Teuho Jarmo, Schultz Jussi, Klén Riku, Knuuti Juhani, Saraste Antti, Ono Naoaki, Kanaya Shigehiko

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

Comparison of 12 Machine Learning Methods for Polar Map Classification in Cardiac Perfusion PET (2021)

IEEE Nuclear Science Symposium and Medical Imaging Conference, IEEE Nuclear Science Symposium and Medical Imaging Conference record

Teuho Jarmo, Schultz Jussi, Klén Riku, Saraste Antti, Ono Naoaki, Kanaya Shigehiko

(Vertaisarvioitu artikkeli konferenssijulkaisussa (A4))

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge (2021)

npj Digital Medicine

Sieberts SolveigK, Schaff Jennifer, Duda Marlena, Pataki Bálint Ármin, Sun Ming, Snyder Phil, Daneault Jean-Francois, Parisi Federico, Costante Gianluca, Rubin Udi, Banda Peter, Chae Yoree, Neto Elias Chaibub, Dorsey E Ray, Aydin Zafer, Chen Aipeng, Elo Laura L, Espino Carlos, Glaab Enrico, Goan Ethan, Golabchi Fatemeh Noushin, Görmez Yasin, Jaakkola Maria K, Jonnagaddala Jitendra, Klén Riku, Li Dongmei, McDaniel Christian, Perrin Dimitri, Perumal Thanneer M, Rad Nastaran Mohammadian, Rainaldi Erin, Sapienza Stefano, Schwab Patrick, Shokhirev Nikolai, Venäläinen Mikko S, Vergara-Diaz Gloria, Zhang Yuqian, Wang Yuanjian, Guan Yuanfang, Brunner Daniela, Bonato Paolo, Mangravite Lara M, Omberg Larsson; the Parkinson's Disease Digital Biomarker Challenge Consortium

(Vertaisarvioitu alkuperäisartikkeli tai data-artikkeli tieteellisessä aikakauslehdessä (A1))

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Are Quantitative Errors Reduced with Time-of-Flight Reconstruction When Using Imperfect MR-Based Attenuation Maps for F-18-FDG PET/MR Neuroimaging? (2022)

Evaluation of three methods for delineation and attenuation estimation of the sinus region in MR-based attenuation correction for brain PET-MR imaging (2022)

Advanced pattern recognition tools for disease diagnosis (2022)

Development and evaluation of a machine learning-based in-hospital COVID-19 disease outcome predictor (CODOP): A multicontinental retrospective study (2022)

Classification of ischemia from myocardial polar maps in 15 O-H 2 O cardiac perfusion imaging using a convolutional neural network (2022)

Classification of ischemia from myocardial polar maps in 15 O-H 2 O cardiac perfusion imaging using a convolutional neural network (2022)

Artificial Intelligence to Improve Risk Prediction with Nuclear Cardiac Studies (2022)

Novel Classification of ischemia from myocardial polar maps in 15O–H2O cardiac perfusion imaging using a convolutional neural network (2022)

Comparison of 12 Machine Learning Methods for Polar Map Classification in Cardiac Perfusion PET (2021)

Crowdsourcing digital health measures to predict Parkinson's disease severity: the Parkinson's Disease Digital Biomarker DREAM Challenge (2021)