A pilot study of subjective well-being in colorectal cancer patients and their caregivers

Background: Traditional endpoints in oncology are based on measuring the tumor size and combining this with a time factor. Current studies with immunotherapy show that even when median survival is unaltered, a significant proportion of patients can achieve prolonged survival. Objective tumor response does not always mean “overall” improvement, especially if toxicity is harsh. Novel agents are significantly expensive, and it is therefore crucial to measure the impact on “quality” of life, in addition to “quantity”. Materials and methods: We studied the preferences and experiences of cancer patients and their caregivers, measuring subjective well-being (SWB) ratings, EQ5D descriptions and time trade-off preferences. Results: We studied 99 patients and 88 caregivers. Life satisfaction ratings were similar between the two groups, but daily mood was significantly lower in caregivers (P<0.1). Anxiety/depression affected SWB, while pain and mobility did not. Positive thoughts about health were associated with better daily moods in both groups, and stage IV cancer was associated with lower life satisfaction. Cancer in remission was associated with better daily moods, but, interestingly, not with patient life satisfaction. Patients with better daily mood and positive thoughts about family were less willing to “trade-off” life years. Conclusion: Caregivers are as anxious or depressed as patients, and report similar levels of life satisfaction but lower daily mood. A focus on SWB could provide a valid assessment of treatment benefit. Given the interesting results of this pilot study, we suggest a larger study should be conducted, measuring SWB over time

Peak Car effects on scheme appraisal

Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική

A survey of temporal knowledge discovery paradigms and methods

With the increase in the size of data sets, data mining has recently become an important research topic and is receiving substantial interest from both academia and industry. At the same time, interest in temporal databases has been increasing and a growing number of both prototype and implemented systems are using an enhanced temporal understanding to explain aspects of behavior associated with the implicit time-varying nature of the universe. This paper investigates the confluence of these two areas, surveys the work to date, and explores the issues involved and the outstanding problems in temporal data mining

Linguistic Markers of Influence in Informal Interactions

There has been a long standing interest in understanding `Social Influence' both in Social Sciences and in Computational Linguistics. In this paper, we present a novel approach to study and measure interpersonal influence in daily interactions. Motivated by the basic principles of influence, we attempt to identify indicative linguistic features of the posts in an online knitting community. We present the scheme used to operationalize and label the posts with indicator features. Experiments with the identified features show an improvement in the classification accuracy of influence by 3.15%. Our results illustrate the important correlation between the characteristics of the language and its potential to influence others.Comment: 10 pages, Accepted in NLP+CSS workshop for ACL (Association for Computational Linguistics) 201

Using Markov Chains for link prediction in adaptive web sites

The large number of Web pages on many Web sites has raised navigational problems. Markov chains have recently been used to model user navigational behavior on the World Wide Web (WWW). In this paper, we propose a method for constructing a Markov model of a Web site based on past visitor behavior. We use the Markov model to make link predictions that assist new users to navigate the Web site. An algorithm for transition probability matrix compression has been used to cluster Web pages with similar transition behaviors and compress the transition matrix to an optimal size for efficient probability calculation in link prediction. A maximal forward path method is used to further improve the efficiency of link prediction. Link prediction has been implemented in an online system called ONE (Online Navigation Explorer) to assist users' navigation in the adaptive Web site