90 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of TurkuFI13 papers
- Turku PET CentreFI5 papers
- Tampere UniversityFI4 papers
- University of JyväskyläFI4 papers
- Aalto UniversityFI3 papers
- Brno University of TechnologyCZ2 papers
- Central Finland Health Care DistrictFI2 papers
- TU WienAT2 papers
- University College LondonGB2 papers
- University of HelsinkiFI2 papers
- Åbo Akademi UniversityFI1 paper
- Agostino Gemelli University PolyclinicIT1 paper
18 papers
Quantitative evaluation of unsupervised clustering algorithms for dynamic total-body PET image analysis
Oona Rainio, Maria K. Jaakkola, Riku Klén
Background. Recently, dynamic total-body positron emission tomography (PET) imaging has become possible due to new scanner devices. While clustering algorithms have been proposed f…
AI for the prediction of early stages of Alzheimer's disease from neuroimaging biomarkers -- A narrative review of a growing field
Thorsten Rudroff, Oona Rainio, Riku Klén
Objectives: The objectives of this narrative review are to summarize the current state of AI applications in neuroimaging for early Alzheimer's disease (AD) prediction and to highl…
On the distribution of isometric log-ratio transformations under extra-multinomial count data
Noora Kartiosuo, Joni Virta, Jaakko Nevalainen +2
Compositional data arise when count observations are normalised into proportions adding up to unity. To allow use of standard statistical methods, compositional proportions can be…
Improving Performance in Colorectal Cancer Histology Decomposition using Deep and Ensemble Machine Learning
Fabi Prezja, Leevi Annala, Sampsa Kiiskinen +4
In routine colorectal cancer management, histologic samples stained with hematoxylin and eosin are commonly used. Nonetheless, their potential for defining objective biomarkers for…
Supporting Management of Gestational Diabetes with Comprehensive Self-Tracking: Mixed-Method Study of Wearable Sensors
Mikko Kytö, Saila Koivusalo, Heli Tuomonen +5
Gestational diabetes (GDM) poses a growing health risk to both pregnant women and their offspring. While telehealth interventions for GDM management have proven effective, they hav…
Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study
Patrick Saux, Pierre Bauvin, Violeta Raverdy +31
Background Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develo…
Hypothesis-driven mediation analysis for compositional data: an application to gut microbiome
Noora Kartiosuo, Jaakko Nevalainen, Olli Raitakari +2
Biological sequencing data consist of read counts, e.g. of specified taxa and often exhibit sparsity (zero-count inflation) and overdispersion (extra-Poisson variability). As most…
Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer
Liisa Petäinen, Juha P. Väyrynen, Pekka Ruusuvuori +3
Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of…
Stationary subspace analysis based on second-order statistics
Lea Flumian, Markus Matilainen, Klaus Nordhausen +1
In stationary subspace analysis (SSA) one assumes that the observable p-variate time series is a linear mixture of a k-variate nonstationary time series and a (p-k)-variate station…
Full feature selection for estimating KAP radiation dose in coronary angiographies and percutaneous coronary interventions
Visa Suomi, Jukka Järvinen, Tuomas Kiviniemi +2
In interventional cardiology (IC) the radiation dose variation is very significant, and its estimation has been difficult due to the complexity of the treatments. In order to tackl…
Virtual reality for 3D histology: multi-scale visualization of organs with interactive feature exploration
Kaisa Liimatainen, Leena Latonen, Masi Valkonen +2
Virtual reality (VR) enables data visualization in an immersive and engaging manner, and it can be used for creating ways to explore scientific data. Here, we use VR for visualizat…
High-intensity focused ultrasound therapy in the uterine fibroid: a clinical case study of poor heating efficacy
Visa Suomi, Antti Viitala, Teija Sainio +2
A clinical case study of high-intensity focused ultrasound (HIFU) treatment in the uterine fibroid was conducted. During the therapy, poor heating efficacy was observed which could…
Comprehensive feature selection for classifying the treatment outcome of high-intensity ultrasound therapy in uterine fibroids
Visa Suomi, Gaber Komar, Teija Sainio +3
The study aim was to utilise multiple feature selection methods in order to select the most important parameters from clinical patient data for high-intensity focused ultrasound (H…
Transurethral ultrasound therapy of the prostate in the presence of calcifications: A simulation study
Visa Suomi, Bradley Treeby, Jiri Jaros +6
Purpose: Transurethral ultrasound therapy is an investigational treatment modality which could potentially be used for the localized treatment of prostate cancer. One of the limiti…
Extracting conditionally heteroscedastic components using ICA
Jari Miettinen, Markus Matilainen, Klaus Nordhausen +1
In the independent component model, the multivariate data is assumed to be a mixture of mutually independent latent components, and in independent component analysis (ICA) the aim…
The effect of tissue physiological variability on transurethral ultrasound therapy of the prostate
Visa Suomi, Bradley Treeby, Jiri Jaros +3
Therapeutic ultrasound is an investigational modality which could potentially be used for minimally invasive treatment of prostate cancer. Computational simulations were used to st…
On the number of signals in multivariate time series
Markus Matilainen, Klaus Nordhausen, Joni Virta
We assume a second-order source separation model where the observed multivariate time series is a linear mixture of latent, temporally uncorrelated time series with some components…
Tournament Leave-pair-out Cross-validation for Receiver Operating Characteristic (ROC) Analysis
Ileana Montoya Perez, Antti Airola, Peter J. Boström +2
Receiver operating characteristic (ROC) analysis is widely used for evaluating diagnostic systems. Recent studies have shown that estimating an area under ROC curve (AUC) with stan…