Bronchopulmonary Dysplasia Prediction using Logistic Regression

Wajs, Wieslaw; Stoch, P.; Kruczek, Piotr

doi:10.1109/isda.2006.18

Cited by 3 publications

(1 citation statement)

References 9 publications

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“…The test consisted of challenging patients by conducting a 30 min room-air trial if the patient was on <30 % oxygen or was >96 % saturated on >30 % [3]. Extreme prematurity in very-low birth-weigh infants and implementation of general patient care strategies such as ventilator management, oxygen administration, and their associated response have played a role in the prevalence of BPD [5].…”

Section: Introductionmentioning

confidence: 99%

Statistical Method for the Problem of Bronchopulmonary Dysplasia Classification in Pre-mature Infants

Wajs

Wojtowicz

Wais

et al. 2016

Intelligent Decision Technologies 2016

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The problem of data classification with a statistical method is presented in the paper. Described classification method enables calculation of probability of disease incidence. A case of disease incidence is described with two parameters expressed in real numbers. The case can belong to a known set of cases where the disease occurred or to the set where the disease did not occur. A method for calculating probability with which a given case belongs to the set labeled as "1" or "0" is proposed. Source data used in the paper come from medical databases and are original. The algorithm of the method was checked on clinical cases. Correlation method was used for generating respective statistics. The calculated correlation at a level of 0.8 is indicative of disease occurrence, whereas the correlation coefficient at a level of 0.0 is indicative of the lack of disease. This property is used in the classification algorithm. It is frequent in the clinical practice that we have one test case and we try to determine whether or not that case describes symptoms of liability to the disease. Classification is related with the occurrence of Bronchopulmonary dysplasia, which is analyzed in a 3 to 4 week period preceding the disease incidence.

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Section: Introductionmentioning

confidence: 99%

Statistical Method for the Problem of Bronchopulmonary Dysplasia Classification in Pre-mature Infants

Wajs

Wojtowicz

Wais

et al. 2016

Intelligent Decision Technologies 2016

View full text Add to dashboard Cite

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Artificial intelligence in medicine

1995

Artificial Intelligence in Medicine

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In this paper we describe how we generated written explanations to 'indirect users' of a knowledge-based system in the domain of drug prescription. We call 'indirect users' the intended recipients of explanations, to distinguish them from the prescriber (the 'direct' user) who interacts with the system. The Explanation Generator was designed after several studies about indirect users' information needs and physicians' explanatory attitudes in this domain. It integrates text planning techniques with ATN-based surface generation. A double modeling component enables adapting the information content, order and style to the indirect user to whom explanation is addressed. Several examples of computer-generated texts are provided, and they are contrasted with the physicians' explanations to discuss advantages and limits of the approach adopted.

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