A Probabilistic Approach to Predict Peers' Performance in P2P Networks

The problem of encouraging trustworthy behavior in P2P online communities by managing peers' reputations has drawn a lot of attention recently. However, most of the proposed solutions exhibit the following two problems: huge implementation overhead and unclear trust related model semantics. In this paper we show that a simple probabilistic technique, maximum likelihood estimation namely, can reduce these two problems substantially when employed as the feedback aggregation strategy. Thus, no complex exploration of the feedback is necessary. Instead, simple, intuitive and e#cient probabilistic estimation methods su#ce

A novel computer based expert decision making model for prostate cancer disease management

PubMedID: 16280831Purpose: We propose a strategic, computer based, prostate cancer decision making model based on the analytic hierarchy process. We developed a model that improves physician-patient joint decision making and enhances the treatment selection process by making this critical decision rational and evidence based. Materials and Methods: Two groups (patient and physician-expert) completed a clinical study comparing an initial disease management choice with the highest ranked option generated by the computer model. Participants made pairwise comparisons to derive priorities for the objectives and subobjectives related to the disease management decision. The weighted comparisons were then applied to treatment options to yield prioritized rank lists that reflect the likelihood that a given alternative will achieve the participant treatment goal. Aggregate data were evaluated by inconsistency ratio analysis and sensitivity analysis, which assessed the influence of individual objectives and subobjectives on the final rank list of treatment options. Results: Inconsistency ratios less than 0.05 were reliably generated, indicating that judgments made within the model were mathematically rational. The aggregate prioritized list of treatment options was tabulated for the patient and physician groups with similar outcomes for the 2 groups. Analysis of the major defining objectives in the treatment selection decision demonstrated the same rank order for the patient and physician groups with cure, survival and quality of life being more important than controlling cancer, preventing major complications of treatment, preventing blood transfusion complications and limiting treatment cost. Analysis of sub-objectives, including quality of life and sexual dysfunction, produced similar priority rankings for the patient and physician groups. Concordance between initial treatment choice and the highest weighted model option differed between the groups with the patient group having 59% concordance and the physician group having only 42% concordance. Conclusions: This study successfully validated the usefulness of a computer based prostate cancer management decision making model to produce individualized, rational, clinically appropriate disease management decisions without physician bias. Copyright © 2005 by American Urological Association

Excess type 2 diabetes in African-American women and men aged 40-74 and socioeconomic status: evidence from the Third National Health and Nutrition Examination Survey

OBJECTIVE—To examine whether socioeconomic status (SES) explains differences in the prevalence of type 2 diabetes between African-American and non-Hispanic white women and men.
DESIGN—Cross sectional study of diabetes prevalence, SES, and other risk factors ascertained by physical examination and interview.
SETTING—Interviews were conducted in subjects' homes; physical examinations were conducted in mobile examination centres.
PARTICIPANTS—961 African-American women, 1641 non-Hispanic white women, 839 African-American men and 1537 non-Hispanic white men, aged 40 to 74 years, examined in the Third National Health and Nutrition Examination Survey (NHANES III), a representative sample of the non-institutionalised civilian population of the United States, 1988-1994.
MAIN RESULTS—Among women, African-American race/ethnicity was associated with an age adjusted odds ratio of 1.76 (95% confidence intervals 1.21, 2.57), which was reduced to 1.42 (95% confidence intervals 0.95, 2.13) when poverty income ratio was controlled. Controlling for education or occupational status had minimal effects on this association. When other risk factors were controlled, race/ethnicity was not significantly associated with type 2 diabetes prevalence. Among men, the age adjusted odds ratio associated with African-American race/ethnicity was 1.43 (95% confidence intervals 1.03, 1.99). Controlling for SES variables only modestly affected the odds ratio for African/American race/ethnicity among men, while adjusting for other risk factors increased the racial/ethnic differences.
CONCLUSIONS—Economic disadvantage may explain much of the excess prevalence of type 2 diabetes among African-American women, but not among men.


Keywords: diabetes mellitus; ethnic groups; socioeconomic factor