Abstract: The construction of a neural network-based decision support system for the diagnosis of... more Abstract: The construction of a neural network-based decision support system for the diagnosis of acute abdominal pain was investigated. Different neural network algorithms were compared to define the optimal algorithms for this diagnostic classification problem. ...
ABSTRACT There is growing appreciation of the importance of understanding the student perspective... more ABSTRACT There is growing appreciation of the importance of understanding the student perspective in Higher Education (HE) at both institutional and international levels. This is particularly important in Science, Technology, Engineering and Mathematics subjects such as Computer Science (CS) and Engineering in which industry needs are high but so are student dropout rates. An important factor to consider is the management of students’ initial expectations of university study and career. This paper reports on a study of CS first-year students’ expectations across three European countries using qualitative data from student surveys and essays. Expectation is examined from both short-term (topics to be studied) and long-term (career goals) perspectives. Tackling these issues will help paint a picture of computing education through students’ eyes and explore their vision of its and their role in society. It will also help educators prepare students more effectively for university study and to improve the student experience.
Acute appendicitis is the most common cause of acute abdomen requiring surgical intervention. The... more Acute appendicitis is the most common cause of acute abdomen requiring surgical intervention. The clinical diagnosis of acute appendicitis is not always easy due to variable symptomatology, particularly at the onset. The contributions of history-taking and physical examination in the diagnosis of acute appendicitis was studied in connection with the Research Committee of the World Organization of Gastroenterology (OMGE) survey of acute abdominal pain. Especially the suitability of diagnostic parameters in the construction of an expert system for automatic decision making was studied. The results clearly show that it is possible to construct an expert system for automatic decision making in the diagnosis of acute appendicitis.
Studies in health technology and informatics, 1997
Three statistical classification methods: discriminant analysis, logistic regression analysis and... more Three statistical classification methods: discriminant analysis, logistic regression analysis and cluster analysis were compared with the back-propagation neural network algorithm in the diagnosis of acute appendicitis. The differences in the classification accuracy, which were evaluated with the receiver operating characteristic (ROC) curve were small, though discriminant analysis and back-propagation showed slightly better results than the other methods. The agreement of the methods on the diagnosis increased the accuracy of the classification, so that the number of misclassified cases reduced. The back-propagation neural network offers a good choice for statistical classification methods, but it was not found to be better than them. The use of several methods and their agreement as the basis of the diagnosis seems to give the best results for this diagnostic classification problem.
The use of an artificial neural network system was studied in the diagnosis of acute abdominal pa... more The use of an artificial neural network system was studied in the diagnosis of acute abdominal pain, especially acute appendicitis, with patients from Finland and Germany. Separate Learning Vector Quantization (LVQ) neural networks were trained with a training set from each database and also with a combined database. Each neural network was evaluated separately with a test set of cases from each database. With the combined database different neighborhood methods were compared to find the optimal choice for this decision-making problem. The acute appendicitis cases of the Finnish test data set were classified well with all the networks, but the cases of the German test set were difficult to classify for the Finnish network. The use of larger neighborhoods increased the sensitivity of the classification by nearly 10%. The differences in the results of the Finnish and German databases suggest that there are differences in the data collection or patient populations between centers. Ther...
Proceedings of the 13th Koli Calling International Conference on Computing Education Research - Koli Calling '13, 2013
ABSTRACT This paper reports an ongoing study on CS freshmen at two universities in Finland. The g... more ABSTRACT This paper reports an ongoing study on CS freshmen at two universities in Finland. The goal of this report is to describe what kind of students decide to study computer science; what are students' programming background, expectations and perceptions regarding their studies and future work life. We collected data from 190 students from two universities at the beginning of the first study year. The results draw a picture of students' who have mainly positive and trusting perceptions of the IT field and who have high expectations of their success at their studies. We will discuss the results, especially the students' heterogeneous programming background and some gender differences, in more detail and consider how we could and should take those into consideration in our curriculum and teaching.
In this study different substitution methods for the replacement of missing data values were insp... more In this study different substitution methods for the replacement of missing data values were inspected for the use of these cases in a neural network based decision support system for acute appendicitis. The leucocyte count had the greatest number of missing values and was used in the analyses. Four different methods were compared: substituting means, random values, nearest neighbour and a neural network. There were great differences in the substituted leucocyte count values between different methods and only nearest neighbour and neural network agreed about most of the cases. The importance of the substitution method for the final diagnostic classification of the patients by the neural network based decision support system was found to be small.
International journal of bio-medical …, Jan 1, 1996
Four different neural network algorithms, binary adaptive resonance theory (ART1), self-organizin... more Four different neural network algorithms, binary adaptive resonance theory (ART1), self-organizing map, learning vector quantization and back-propagation, were compared in the diagnosis of acute appendicitis with different parameter groups. The results show that supervised learning algorithms learning vector quantization and back-propagation were better than unsupervised algorithms in this medical decision making problem. The best results were obtained with the learning vector quantization. The self-organizing map algorithm showed good specificity, but this was in conjunction with lower sensitivity. The best parameter group was found to be the clinical signs. It seems beneficial to design a decision support system which uses these methods in the decision making process.
Abstract: The construction of a neural network-based decision support system for the diagnosis of... more Abstract: The construction of a neural network-based decision support system for the diagnosis of acute abdominal pain was investigated. Different neural network algorithms were compared to define the optimal algorithms for this diagnostic classification problem. ...
ABSTRACT There is growing appreciation of the importance of understanding the student perspective... more ABSTRACT There is growing appreciation of the importance of understanding the student perspective in Higher Education (HE) at both institutional and international levels. This is particularly important in Science, Technology, Engineering and Mathematics subjects such as Computer Science (CS) and Engineering in which industry needs are high but so are student dropout rates. An important factor to consider is the management of students’ initial expectations of university study and career. This paper reports on a study of CS first-year students’ expectations across three European countries using qualitative data from student surveys and essays. Expectation is examined from both short-term (topics to be studied) and long-term (career goals) perspectives. Tackling these issues will help paint a picture of computing education through students’ eyes and explore their vision of its and their role in society. It will also help educators prepare students more effectively for university study and to improve the student experience.
Acute appendicitis is the most common cause of acute abdomen requiring surgical intervention. The... more Acute appendicitis is the most common cause of acute abdomen requiring surgical intervention. The clinical diagnosis of acute appendicitis is not always easy due to variable symptomatology, particularly at the onset. The contributions of history-taking and physical examination in the diagnosis of acute appendicitis was studied in connection with the Research Committee of the World Organization of Gastroenterology (OMGE) survey of acute abdominal pain. Especially the suitability of diagnostic parameters in the construction of an expert system for automatic decision making was studied. The results clearly show that it is possible to construct an expert system for automatic decision making in the diagnosis of acute appendicitis.
Studies in health technology and informatics, 1997
Three statistical classification methods: discriminant analysis, logistic regression analysis and... more Three statistical classification methods: discriminant analysis, logistic regression analysis and cluster analysis were compared with the back-propagation neural network algorithm in the diagnosis of acute appendicitis. The differences in the classification accuracy, which were evaluated with the receiver operating characteristic (ROC) curve were small, though discriminant analysis and back-propagation showed slightly better results than the other methods. The agreement of the methods on the diagnosis increased the accuracy of the classification, so that the number of misclassified cases reduced. The back-propagation neural network offers a good choice for statistical classification methods, but it was not found to be better than them. The use of several methods and their agreement as the basis of the diagnosis seems to give the best results for this diagnostic classification problem.
The use of an artificial neural network system was studied in the diagnosis of acute abdominal pa... more The use of an artificial neural network system was studied in the diagnosis of acute abdominal pain, especially acute appendicitis, with patients from Finland and Germany. Separate Learning Vector Quantization (LVQ) neural networks were trained with a training set from each database and also with a combined database. Each neural network was evaluated separately with a test set of cases from each database. With the combined database different neighborhood methods were compared to find the optimal choice for this decision-making problem. The acute appendicitis cases of the Finnish test data set were classified well with all the networks, but the cases of the German test set were difficult to classify for the Finnish network. The use of larger neighborhoods increased the sensitivity of the classification by nearly 10%. The differences in the results of the Finnish and German databases suggest that there are differences in the data collection or patient populations between centers. Ther...
Proceedings of the 13th Koli Calling International Conference on Computing Education Research - Koli Calling '13, 2013
ABSTRACT This paper reports an ongoing study on CS freshmen at two universities in Finland. The g... more ABSTRACT This paper reports an ongoing study on CS freshmen at two universities in Finland. The goal of this report is to describe what kind of students decide to study computer science; what are students' programming background, expectations and perceptions regarding their studies and future work life. We collected data from 190 students from two universities at the beginning of the first study year. The results draw a picture of students' who have mainly positive and trusting perceptions of the IT field and who have high expectations of their success at their studies. We will discuss the results, especially the students' heterogeneous programming background and some gender differences, in more detail and consider how we could and should take those into consideration in our curriculum and teaching.
In this study different substitution methods for the replacement of missing data values were insp... more In this study different substitution methods for the replacement of missing data values were inspected for the use of these cases in a neural network based decision support system for acute appendicitis. The leucocyte count had the greatest number of missing values and was used in the analyses. Four different methods were compared: substituting means, random values, nearest neighbour and a neural network. There were great differences in the substituted leucocyte count values between different methods and only nearest neighbour and neural network agreed about most of the cases. The importance of the substitution method for the final diagnostic classification of the patients by the neural network based decision support system was found to be small.
International journal of bio-medical …, Jan 1, 1996
Four different neural network algorithms, binary adaptive resonance theory (ART1), self-organizin... more Four different neural network algorithms, binary adaptive resonance theory (ART1), self-organizing map, learning vector quantization and back-propagation, were compared in the diagnosis of acute appendicitis with different parameter groups. The results show that supervised learning algorithms learning vector quantization and back-propagation were better than unsupervised algorithms in this medical decision making problem. The best results were obtained with the learning vector quantization. The self-organizing map algorithm showed good specificity, but this was in conjunction with lower sensitivity. The best parameter group was found to be the clinical signs. It seems beneficial to design a decision support system which uses these methods in the decision making process.
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Papers by Erkki Pesonen