Automatic construction of rule-based ICD-9-CM coding systems

Background: In this paper we focus on the problem of automatically constructing ICD-9-CM coding systems for radiology reports. ICD-9-CM codes are used for billing purposes by health institutes and are assigned to clinical records manually following clinical treatment. Since this labeling task requires expert knowledge in the field of medicine, the process itself is costly and is prone to errors as human annotators have to consider thousands of possible codes when assigning the right ICD-9-CM labels to a document. In this study we use the datasets made available for training and testing automated ICD-9-CM coding systems by the organisers of an International Challenge on Classifying Clinical Free Text Using Natural Language Processing in spring 2007. The challenge itself was dominated by entirely or partly rule-based systems that solve the coding task using a set of hand crafted expert rules. Since the feasibility of the construction of such systems for thousands of ICD codes is indeed questionable, we decided to examine the problem of automatically constructing similar rule sets that turned out to achieve a remarkable accuracy in the shared task challenge. Results: Our results are very promising in the sense that we managed to achieve comparable results with purely hand-crafted ICD-9-CM classifiers. Our best model got a 90.26 % F measure on the training dataset and an 88.93 % F measure on the challenge test dataset, using the micro-averaged Fβ=1 measure, the official evaluatio

Factors Relating to Managerial Stereotypes: The Role of Gender of the Employee and the Manager and Management Gender Ratio

Several studies have shown that the traditional stereotype of a "good" manager being masculine and male still exists. The recent changes in the proportion of women and female managers in organizations could affect these two managerial stereotypes, leading to a stronger preference for feminine characteristics and female leaders. This study examines if the gender of an employee, the gender of the manager, and the management gender ratio in an organization are related to employees' managerial stereotypes. 3229 respondents working in various organizations completed an electronic questionnaire. The results confirm our hypotheses that, although the general stereotype of a manager is masculine and although most prefer a man as a manager, female employees, employees with a female manager, and employees working in an organization with a high percentage of female managers, have a stronger preference for feminine characteristics of managers and for female managers. Moreover, we find that proximal variables are much stronger predictors of these preferences than more distal variables. Our study suggests that managerial stereotypes could change as a result of personal experiences and changes in the organizational context. The results imply that increasing the proportion of female managers is an effective way to overcome managerial stereotyping. This study examines the influence on managerial stereotypes of various proximal and distal factors derived from theory among a large group of employees (in contrast to students)