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201 results on '"Roine, Antti"'

1. Forecasting mortality associated emergency department crowding

Author

Nevanlinna, Jalmari, Eidstø, Anna, Ylä-Mattila, Jari, Koivistoinen, Teemu, Oksala, Niku, Kanniainen, Juho, Palomäki, Ari, and Roine, Antti

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Applications
Abstract

Emergency department (ED) crowding is a global public health issue that has been repeatedly associated with increased mortality. Predicting future service demand would enable preventative measures aiming to eliminate crowding along with it's detrimental effects. Recent findings in our ED indicate that occupancy ratios exceeding 90% are associated with increased 10-day mortality. In this paper, we aim to predict these crisis periods using retrospective data from a large Nordic ED with a LightGBM model. We provide predictions for the whole ED and individually for it's different operational sections. We demonstrate that afternoon crowding can be predicted at 11 a.m. with an AUC of 0.82 (95% CI 0.78-0.86) and at 8 a.m. with an AUC up to 0.79 (95% CI 0.75-0.83). Consequently we show that forecasting mortality-associated crowding using anonymous administrative data is feasible.

Published
2024

2. Forecasting Emergency Department Crowding with Advanced Machine Learning Models and Multivariable Input

Author

Tuominen, Jalmari, Pulkkinen, Eetu, Peltonen, Jaakko, Kanniainen, Juho, Oksala, Niku, Palomäki, Ari, and Roine, Antti

Subjects
Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

Emergency department (ED) crowding is a significant threat to patient safety and it has been repeatedly associated with increased mortality. Forecasting future service demand has the potential patient outcomes. Despite active research on the subject, several gaps remain: 1) proposed forecasting models have become outdated due to quick influx of advanced machine learning models (ML), 2) amount of multivariable input data has been limited and 3) discrete performance metrics have been rarely reported. In this study, we document the performance of a set of advanced ML models in forecasting ED occupancy 24 hours ahead. We use electronic health record data from a large, combined ED with an extensive set of explanatory variables, including the availability of beds in catchment area hospitals, traffic data from local observation stations, weather variables, etc. We show that N-BEATS and LightGBM outpeform benchmarks with 11 % and 9 % respective improvements and that DeepAR predicts next day crowding with an AUC of 0.76 (95 % CI 0.69-0.84). To the best of our knowledge, this is the first study to document the superiority of LightGBM and N-BEATS over statistical benchmarks in the context of ED forecasting.

Published
2023

3. Early Warning Software for Emergency Department Crowding

Author

Tuominen, Jalmari, Koivistoinen, Teemu, Kanniainen, Juho, Oksala, Niku, Palomäki, Ari, and Roine, Antti

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

Emergency department (ED) crowding is a well-recognized threat to patient safety and it has been repeatedly associated with increased mortality. Accurate forecasts of future service demand could lead to better resource management and has the potential to improve treatment outcomes. This logic has motivated an increasing number of research articles but there has been little to no effort to move these findings from theory to practice. In this article, we present first results of a prospective crowding early warning software, that was integrated to hospital databases to create real-time predictions every hour over the course of 5 months in a Nordic combined ED using Holt-Winters' seasonal methods. We showed that the software could predict next hour crowding with a nominal AUC of 0.98 and 24 hour crowding with an AUC of 0.79 using simple statistical models. Moreover, we suggest that afternoon crowding can be predicted at 1 p.m. with an AUC of 0.84., Comment: 15 pages, 6 figures

Published
2023

10. Identification of Phospholipids Relevant to Cancer Tissue Using Differential Ion Mobility Spectrometry.

Author

Sioris, Patrik, Mäkelä, Meri, Kontunen, Anton, Karjalainen, Markus, Vehkaoja, Antti, Oksala, Niku, and Roine, Antti

Subjects
FISHER discriminant analysis, SUPPORT vector machines, SURGICAL smoke, SURGICAL instruments, GAS analysis
Abstract

Phospholipids are the main building components of cell membranes and are also used for cell signaling and as energy storages. Cancer cells alter their lipid metabolism, which ultimately leads to an increase in phospholipids in cancer tissue. Surgical energy instruments use electrical or vibrational energy to heat tissues, which causes intra- and extracellular water to expand rapidly and degrade cell structures, bursting the cells, which causes the formation of a tissue aerosol or smoke depending on the amount of energy used. This gas phase analyte can then be analyzed via gas analysis methods. Differential mobility spectrometry (DMS) is a method that can be used to differentiate malignant tissue from benign tissues in real time via the analysis of surgical smoke produced by energy instruments. Previously, the DMS identification of cancer tissue was based on a 'black box method' by differentiating the 2D dispersion plots of samples. This study sets out to find datapoints from the DMS dispersion plots that represent relevant target molecules. We studied the ability of DMS to differentiate three subclasses of phospholipids (phosphatidylcholine, phosphatidylinositol, and phosphatidylethanolamine) from a control sample using a bovine skeletal muscle matrix with a 5 mg addition of each phospholipid subclass to the sample matrix. We trained binary classifiers using linear discriminant analysis (LDA) and support vector machines (SVM) for sample classification. We were able to identify phosphatidylcholine, -inositol, and -ethanolamine with SVM binary classification accuracies of 91%, 73%, and 66% and with LDA binary classification accuracies of 82%, 74%, and 72%, respectively. Phosphatidylcholine was detected with a reliable classification accuracy, but ion separation setups should be adjusted in future studies to reliably detect other relevant phospholipids such as phosphatidylinositol and phosphatidylethanolamine and improve DMS as a microanalysis method and identify other phospholipids relevant to cancer tissue. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Rapid identification of pediatric brain tumors with differential mobility spectrometry.

Author

Haapala, Ilkka, Rauhameri, Anton, Mäkelä, Meri, Karjalainen, Markus, Kontunen, Anton, Mieskolainen, Markus, Haapasalo, Hannu, Roine, Antti, Oksala, Niku, Vehkaoja, Antti, Haapasalo, Joonas, and Nordfors, Kristiina

Subjects
CEREBELLAR tumors, BRAIN tumors, FROZEN tissue sections, FISHER discriminant analysis, SPECTROMETRY, CHILD patients, EPENDYMOMA
Abstract

Introduction: Brain tumors are a major source of disease burden in pediatric population, with the most common tumor types being pilocytic astrocytoma, ependymoma and medulloblastoma. In every tumor entity, surgery is the cornerstone of treatment, but the importance of gross-total resection and the corresponding patient prognosis is highly variant. However, real-time identification of pediatric CNS malignancies based on the histology of the frozen sections alone is especially troublesome. We propose a novel method based on differential mobility spectrometry (DMS) analysis for rapid identification of pediatric brain tumors. Methods: We prospectively obtained tumor samples from 15 pediatric patients (5 pilocytic astrocytomas, 5 ependymomas and 5 medulloblastomas). The samples were cut into 36 smaller specimens that were analyzed with the DMS. Results: With linear discriminant analysis algorithm, a classification accuracy (CA) of 70% was reached. Additionally, a 75% CA was achieved in a pooled analysis of medulloblastoma vs. gliomas. Discussion: Our results show that the DMS is able to differentiate most common pediatric brain tumor samples, thus making it a promising additional instrument for real-time brain tumor diagnostics. [ABSTRACT FROM AUTHOR]

Published
2024
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25. The Detection of Bacteria in the Maxillary Sinus Secretion of Patients With Acute Rhinosinusitis Using an Electronic Nose: A Pilot Study.

Author

Virtanen, Jussi, Roine, Antti, Kontunen, Anton, Karjalainen, Markus, Numminen, Jura, Oksala, Niku, Rautiainen, Markus, and Kivekäs, Ilkka

Subjects
*PILOT projects, *MAXILLARY sinus, *DISCRIMINANT analysis, *SINUSITIS, *RESEARCH funding, *SENSITIVITY & specificity (Statistics), *BACTERIA, *SPECTRUM analysis
Abstract

Objective: Detecting bacteria as a causative pathogen of acute rhinosinusitis (ARS) is a challenging task. Electronic nose technology is a novel method for detecting volatile organic compounds (VOCs) that has also been studied in association with the detection of several diseases. The aim of this pilot study was to analyze maxillary sinus secretion with differential mobility spectrometry (DMS) and to determine whether the secretion demonstrates a different VOC profile when bacteria are present. Methods: Adult patients with ARS symptoms were examined. Maxillary sinus contents were aspirated for bacterial culture and DMS analysis. k -Nearest neighbor and linear discriminant analysis were used to classify samples as positive or negative, using bacterial cultures as a reference. Results: A total of 26 samples from 15 patients were obtained. After leave-one-out cross-validation, k -nearest neighbor produced accuracy of 85%, sensitivity of 67%, specificity of 94%, positive predictive value of 86%, and negative predictive value of 84%. Conclusions: The results of this pilot study suggest that bacterial positive and bacterial negative sinus secretion release different VOCs and that DMS has the potential to detect them. However, as the results are based on limited data, further conclusions cannot be made. DMS is a novel method in disease diagnostics and future studies should examine whether the method can detect bacterial ARS by analyzing exhaled air. [ABSTRACT FROM AUTHOR]

Published
2023
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26. Bile-volatile organic compounds in the diagnostics of pancreatic cancer and biliary obstruction: A prospective proof-of-concept study

Author

Teränen, Ville, Nissinen, Samuli, Roine, Antti, Antila, Anne, Siiki, Antti, Vaalavuo, Yrjö, Kumpulainen, Pekka, Oksala, Niku, Laukkarinen, Johanna, Tampere University, Clinical Medicine, and Department of Gastroenterology

Subjects
Cancer Research, Oncology, 3121 Internal medicine, 3126 Surgery, anesthesiology, intensive care, radiology
Abstract

ObjectivesDetection of volatile organic compounds (VOCs) from bodily fluids with field asymmetric waveform ion mobility spectrometry (FAIMS) and related methods has been studied in various settings. Preliminary results suggest that it is possible to detect prostate, colorectal, ovarian and pancreatic cancer from urine samples. In this study, our primary aim was to differentiate pancreatic cancer from pancreatitis and benign tumours of the pancreas by using bile samples obtained during endoscopic retrograde cholangiopancreatography (ERCP). Secondarily, we aimed to differentiate all pancreatic region malignancies from all other kinds of benign causes of biliary obstruction.MethodsA bile sample was successfully aspirated from 94 patients during ERCP in Tampere University Hospital. Hospital and patient records were prospectively followed up for at least two years after ERCP. Bile samples were analysed using a Lonestar chemical analyser (Owlstone, UK) using an ATLAS sampling system and a split-flow box. Diagnoses and corresponding data from the analyses were matched and divided into two subcategories for comparison. Statistical analysis was performed using linear discriminant analysis, support vector machines, and 5-fold cross-validation.ResultsPancreatic cancers (n=8) were differentiated from benign pancreatic lesions (n=9) with a sensitivity of 100%, specificity of 77.8%, and correct rate of 88%. All pancreatic region cancers (n=19) were differentiated from all other kinds of benign causes of biliary obstruction (n=75) with corresponding values of 21.1%, 94.7%, and 80.7%. The sample size was too small to try to differentiate pancreatic cancers from adjacent cancers.ConclusionAnalysing bile VOCs using FAIMS shows promising capability in detecting pancreatic cancer and other cancers in the pancreatic area.

Published
2022

31. Method for the Intraoperative Detection of IDH Mutation in Gliomas with Differential Mobility Spectrometry

Author

Haapala, Ilkka, primary, Kondratev, Anton, additional, Roine, Antti, additional, Mäkelä, Meri, additional, Kontunen, Anton, additional, Karjalainen, Markus, additional, Laakso, Aki, additional, Koroknay-Pál, Päivi, additional, Nordfors, Kristiina, additional, Haapasalo, Hannu, additional, Oksala, Niku, additional, Vehkaoja, Antti, additional, and Haapasalo, Joonas, additional

Published
2022
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32. Detection of cultured breast cancer cells from human tumor-derived matrix by differential ion mobility spectrometry

Author

Lindfors, Lydia, primary, Sioris, Patrik, additional, Anttalainen, Anna, additional, Korelin, Katja, additional, Kontunen, Anton, additional, Karjalainen, Markus, additional, Naakka, Erika, additional, Salo, Tuula, additional, Vehkaoja, Antti, additional, Oksala, Niku, additional, Hytönen, Vesa, additional, Roine, Antti, additional, and Lepomäki, Maiju, additional

Published
2022
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40. 3-dimensional distribution of ore minerals from the Au-U Witwatersrand Supergroup using spectral X-ray computed micro tomography

Author

Sittner, Jonathan, Godinho, JoseR.A, Renno, Axel, Cnudde, Veerle, Merkulova, Margarita, Guy, Bradley, Boone, Marijn, De Schryver, Thomas, Van Loo, Denis, Roine, Antti, Liipo, Jussi, Sittner, Jonathan, Godinho, JoseR.A, Renno, Axel, Cnudde, Veerle, Merkulova, Margarita, Guy, Bradley, Boone, Marijn, De Schryver, Thomas, Van Loo, Denis, Roine, Antti, and Liipo, Jussi

Abstract

The Witwatersrand Supergroup in South Africa is not only the best-preserved sequence of Archean sedimentary rocks but also hosts the largest gold deposit on earth, yet discovered. The gold is situated in quartz-pebble conglomerates and is generally associated with a wide variety of minerals, including pyrite (FeS2), uraninite (UO2), pyrobitumen, base metal sulfides and phyllosilicates. Despite extensive research over the past 100 years, the origin of the gold is still debated with two models receiving most of the attention: the modified paleoplacer model and the hydrothermal models. The modified paleoplacer model assumes that detrital gold was transported into the host rock by fluvial processes, followed by a short-range mobilization (micrometer- to meter scale) by hydrothermal fluids that infiltrated the host rock. In the hydrothermal model, gold was introduced into the host rock by postdepositional hydrothermal fluids from an external source.To find new evidence for the origin of gold, we present new high-resolution 3-dimensional (3D) data based on the combination of X-ray computed micro tomography (micro-CT) and spectral X-ray computed micro tomography (Sp-CT). We combine both imaging techniques as micro-CT is an excellent tool for high resolution structural characterization and Sp-CT has the power to chemically identify a selection of minerals relevant in this study. Sp-CT is based on the analysis of X-ray absorption spectra, in particular specific K-edges, which assists in identification of chemical elements in a sample. Since most of the previous research of the Witwatersrand gold focus on 2-dimensional methods, the outcomes of this study will help to understand the 3D spatial and size distribution of the gold and provide morphological information about individual particles.This research has received funding from the European Institute of Innovation and Technology (EIT). This body of the European Union receives support from the European U

Published
2021

41. Spectral X-ray computed micro tomography: 3-dimensional chemical imaging

Author

Sittner, Jonathan, Godinho, Jose R. A., Renno, Axel D., Cnudde, Veerle, Boone, Marijn, De Schryver, Thomas, Van Loo, Denis, Merkulova, Margarita, Roine, Antti, Liipo, Jussi, Sittner, Jonathan, Godinho, Jose R. A., Renno, Axel D., Cnudde, Veerle, Boone, Marijn, De Schryver, Thomas, Van Loo, Denis, Merkulova, Margarita, Roine, Antti, and Liipo, Jussi

Abstract

We present a new approach to 3-dimensional chemical imaging based on X-ray computed micro tomography (CT), which enables the analysis of the internal elemental chemistry. The method uses a conventional laboratory-based CT scanner equipped with a semiconductor detector (CdTe). Based on the X-ray absorption spectra, elements in a sample can be distinguished by their specific K-edge energy. The capabilities and performance of this new approach are illustrated with different experiments, i.e. single pure element particle measurements, element differentiation in mixtures, and mineral differentiation in a natural rock sample. The results show that the method can distinguish elements with K-edges in the range of 20 to 160 keV, this corresponds to an element range from Ag to U. Furthermore, the spectral information allows a distinction between materials, which show little variation in contrast in the reconstructed CT image.

Published
2021

42. Spectral X-ray computed micro tomography: 3-dimensional chemical imaging

Author

Hydrogeology, Environmental hydrogeology, Sittner, Jonathan, Godinho, Jose R. A., Renno, Axel D., Cnudde, Veerle, Boone, Marijn, De Schryver, Thomas, Van Loo, Denis, Merkulova, Margarita, Roine, Antti, Liipo, Jussi, Hydrogeology, Environmental hydrogeology, Sittner, Jonathan, Godinho, Jose R. A., Renno, Axel D., Cnudde, Veerle, Boone, Marijn, De Schryver, Thomas, Van Loo, Denis, Merkulova, Margarita, Roine, Antti, and Liipo, Jussi

Published
2021

43. 3-dimensional distribution of ore minerals from the Au-U Witwatersrand Supergroup using spectral X-ray computed micro tomography

Author

Hydrogeology, Environmental hydrogeology, Sittner, Jonathan, Godinho, JoseR.A, Renno, Axel, Cnudde, Veerle, Merkulova, Margarita, Guy, Bradley, Boone, Marijn, De Schryver, Thomas, Van Loo, Denis, Roine, Antti, Liipo, Jussi, Hydrogeology, Environmental hydrogeology, Sittner, Jonathan, Godinho, JoseR.A, Renno, Axel, Cnudde, Veerle, Merkulova, Margarita, Guy, Bradley, Boone, Marijn, De Schryver, Thomas, Van Loo, Denis, Roine, Antti, and Liipo, Jussi

Published
2021

45. Spectral X-ray computed micro tomography: a tool for 3-dimensional chemical imaging

Author

Sittner, Jonathan, primary, Merkulova, Margarita, additional, Godinho, Jose Ricardo da Assuncao, additional, Renno, Axel, additional, Cnudde, Veerle, additional, Boone, Marijn, additional, De Schryver, Thomas, additional, Van Loo, Denis, additional, Roine, Antti, additional, Liipo, Jussi, additional, Guy, Bradley Martin, additional, and Dewaele, Stijn, additional

Published
2021
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46. Process model based environmental footprints of copper smelting

Author

Sarwar, Golam, Roine, Antti, Kemian tekniikan korkeakoulu, Louhi-Kultanen, Marjatta, Alexander, Christina, Sarwar, Golam, Roine, Antti, Kemian tekniikan korkeakoulu, Louhi-Kultanen, Marjatta, and Alexander, Christina

Abstract

Copper is an important metal with many uses in today’s society. The demand for copper is increasing and to meet this demand it is necessary to provide profitable technologies for its production. However, in present-day markets, it is not enough to consider the economic factors alone in an investment, but environmental aspects also have to be taken into account. In this area, regarding copper production and its technologies, there still exists room for improvement. In particular, the smelting phase of the production process has been observed to be harmful to the environment. One way to study the environmental aspects of these production processes is a Life Cycle Assessment (LCA) analysis tool. In this work, the environmental issues related to copper smelting as well as their relationship to technological differences were studied. A process model based LCA procedure was developed for Outotec to calculate and evaluate the environmental footprint of seven process models based on seven different copper smelting technologies. To do this, HSC Sim and openLCA software packages were utilized. In addition, a database was developed to be shared via a collaboration server for users in Outotec. In the future, the developed LCA procedure together with the above-mentioned software packages as well as databases can be used to conduct similar sustainability projects. Further, the information obtained from the projects can be used to develop the technologies to be more environmentally friendly. The results were calculated in two scenarios. In Scenario 1 only the smelter was taken into account. In Scenario 2 the pre-processing of raw materials and the impact of energy generation were also considered. Scenario 2 data was compared across different geographical locations, namely China, Chile, and Germany, with global averages as reference values. The functional unit used in all the LCA analysis was the production of one metric ton of copper in blister copper. The results showed clear dif, Kupari on tärkeä metalli nykypäivän yhteiskunnassa monien erilaisten käyttötarkoituksiensa vuoksi. Kuparin kysyntä kasvaa koko ajan, minkä vuoksi on tärkeää tarjota markkinoille taloudellista teknologiaa koskien kuparintuotantoa. Nykypäivänä taloudellisuus ei kuitenkaan ole ainoa tekijä teknologioiden vertailuissa, vaan ympäristövaikutuksilla on myös iso rooli. Kuparin tuotannolla ja sen teknologioilla on vielä parannettavaa tällä saralla. Erityisesti kuparinsulatuksen on havaittu olevan haitallinen ympäristölle. Yksi tapa tutkia kuparinsulatuksen ympäristöjalanjälkeä on käyttää niin sanottua elinkaariarviointi menetelmää (Life Cycle Assessment, LCA). Työssä tutkittiin kuparisulatukseen liittyviä ympäristöongelmia ja erityisesti sitä, miten ne vaihtelevat eri teknologioiden välillä. Prosessimalli-pohjainen elinkaariarviointi menettelytapa kehitettiin Outotecille, jotta seitsemän eri teknologiaan perustuvien prosessimallien ympäristöjalanjäljet pystyttiin laskemaan. Laskennassa käytettiin apuna HSC Sim- ja openLCA-ohjelmistoja. Osana menettelytavan kehitystä oli myös tietokannan kokoaminen liittyen malleihin, joka voidaan jakaa Outotecin sisäisille käyttäjille niin kutsutun yhteiskäyttöpalvelimen kautta. Tulevaisuudessa tarkoitus on käyttää tässä työssä kehitettyä elinkaariarviointi menettelytapaa, yllämainittuja ohjelmistoja sekä sisäistä tietokantaa samanlaisissa kestävän kehityksen projekteissa. Näiden lisäksi tietoa, jota koko työssä ja menettelytavan kehityksessä saatiin, voidaan käyttää teknologioiden kehittämiseksi enemmän ympäristöystävällisiksi. Työn tulokset laskettiin kahdessa eri skenaariossa. Skenaario 1 ottaa huomioon vain kuparisulaton. Skenaario 2 ottaa huomioon myös raaka-aineiden esikäsittelyn, kuten valmistuksen sekä energian tuotannon. Skenaario 2:ssa tutkittiin myös datan muuttumista sulaton sijainnin muuttuessa (Kiina, Chile, Saksa). Laskennassa hyödynnettiin lisäksi globaaleja keskiarvoja vertailukohteena sijainnista riippuvalle datalle. Elinka

Published
2020

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