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540 results on '"Juhola, Martti"'

10. Machine learning classification of psychiatric data associated with compensation claims for patient injuries

Author

Juhola, Martti, Nikkanen, Tommi, Niemi, Juho, Welling, Maiju, Kampman, Olli, Juhola, Martti, Nikkanen, Tommi, Niemi, Juho, Welling, Maiju, and Kampman, Olli

Abstract

Background: Adverse events are common in health care. In psychiatric treatment, compensation claims for patient injuries appear to be less common than in other medical specialties. The most common types of patient injury claims in psychiatry include diagnostic flaws, unprevented suicide, or coercive treatment deemed as unnecessary or harmful. Objectives: The objective was to study whether it is possible to form different categories of patient injury types associated with the psychiatric evaluations of compensation claims and to base machine learning classification on these categories. Further, the binary classification of positive and negative decisions for compensation claims was the other objective. Methods: Finnish psychiatric specialist evaluations for the compensation claims of patient injuries were classified into six different categories called classes applying the machine learning methods of artificial intelligence. In addition, another classification of the same data into two classes was performed to test whether it was possible to classify data cases according to their known decisions, either accepted or declined compensation claim. Results: The former classification task produced relatively good classification results subject to separating between different classes. Instead, the latter was more complex. However, classification accuracies of both tasks could be improved by using the generation of artificial data cases in the preprocessing phase before classifications. This preprocessing improved the classification accuracy of six classes up to 88% when the method of random forests was used for classification and that of the binary classification to 89%. Conclusion The results show that the objectives defined were possible to solve reasonably.

Published
2023
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12. DAGSVM vs. DAGKNN: An Experimental Case Study with Benthic Macroinvertebrate Dataset

Author

Joutsijoki, Henry, Juhola, Martti, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, and Perner, Petra, editor

Published
2012
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13. Comparing the One-vs-One and One-vs-All Methods in Benthic Macroinvertebrate Image Classification

Author

Joutsijoki, Henry, Juhola, Martti, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, and Perner, Petra, editor

Published
2011
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14. Self-Organising Maps in Document Classification: A Comparison with Six Machine Learning Methods

Author

Saarikoski, Jyri, Laurikkala, Jorma, Järvelin, Kalervo, Juhola, Martti, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Dobnikar, Andrej, editor, Lotrič, Uroš, editor, and Šter, Branko, editor

Published
2011
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18. On Document Classification with Self-Organising Maps

Author

Saarikoski, Jyri, Järvelin, Kalervo, Laurikkala, Jorma, Juhola, Martti, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Kolehmainen, Mikko, editor, Toivanen, Pekka, editor, and Beliczynski, Bartlomiej, editor

Published
2009
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28. Neural Network Recognition of Otoneurological Vertigo Diseases with Comparison of Some Other Classification Methods

Author

Juhola, Martti, Laurikkala, Jorma, Viikki, Kati, Auramo1, Yrjö, Kentala, Erna, Pyykkö, Ilmari, Goos, G., editor, Hartmanis, J., editor, van Leeuwen, J., editor, Carbonell, J. G., editor, Siekmann, J., editor, Horn, Werner, editor, Shahar, Yuval, editor, Lindberg, Greger, editor, Andreassen, Steen, editor, and Wyatt, Jeremy, editor

Published
1999
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49. Creating and exploiting a comparable corpus in cross-language information retrieval

Author

Talvensaari, Tuomas, Laurikkala, Jorma, Jarvelin, Kalervo, Juhola, Martti, and Keskustalo, Heikki

Subjects
Algorithm, Algorithms -- Usage, Information storage and retrieval -- Analysis, Query languages -- Usage
Abstract

We present a method for creating a comparable text corpus from two document collections in different languages. The collections can be very different in origin. In this study, we build a comparable corpus from articles by a Swedish news agency and a U.S. newspaper. The keys with best resolution power were extracted from the documents of one collection, the source collection, by using the relative average term frequency (RATF) value. The keys were translated into the language of the other collection, the target collection, with a dictionary-based query translation program. The translated queries were run against the target collection and an alignment pair was made if the retrieved documents matched given date and similarity score criteria. The resulting comparable collection was used as a similarity thesaurus to translate queries along with a dictionary-based translator. The combined approaches outperformed translation schemes where dictionary-based translation or corpus translation was used alone. General Terms: Algorithms, Languages Additional Key Words and Phrases: Cross-language information retrieval, comparable corpora,query translation DOI = 10.1145/1198296.1198300

Published
2007

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