Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

Machine Learning : A Probabilistic Perspective

Secret History: Return of the Black Death Channel 4, 7-8pm In 1348 the Black Death swept through London, killing people within days of the appearance of their first symptoms. Exactly how many died, and why, has long been a mystery. This Secret History documentary follows experts as they pick through the evidence and reveal why the plague killed on such a scale. And they ask, what might be coming next?

Medscape

Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース)

Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy).

Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables.

Results: We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples.

Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.

/pdf/mendelian-randomization-with-invalid-instruments-effect-1pqi6rglyj.pdf

Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

Optimal estimation and inference for both the minimizer and minimum of a convex regression function under the white noise and nonparametric regression models are studied in a non-asymptotic local minimax framework, where the performance of a procedure is evaluated at individual functions. Fully adaptive and computationally efficient algorithms are proposed and sharp minimax lower bounds are given for both the estimation accuracy and expected length of confidence intervals for the minimizer and minimum. The non-asymptotic local minimax framework brings out new phenomena in simultaneous estimation and inference for the minimizer and minimum. We establish a novel Uncertainty Principle that provides a fundamental limit on how well the minimizer and minimum can be estimated simultaneously for any convex regression function. A similar result holds for the expected length of the confidence intervals for the minimizer and minimum.

Estimation and Inference for Minimizer and Minimum of Convex Functions: Optimality, Adaptivity, and Uncertainty Principles

Re: Guido Dalbagni, Kinjal Vora, Matthew Kaag, et al. Clinical outcome in a contemporary series of restaged patients with clinical T1 bladder cancer. Eur Urol 2009;56:903-10.

Prostatitis syndrome classification is mainly based on clinical and laboratory or instrumental characteristics. The NIH classification of prostatitis syndromes includes four different main categories: (1) acute bacterial prostatitis; (2) chronic bacterial prostatitis; (3) chronic prostatitis/chronic pelvic pain syndrome, (3a) inflammatory, (3b) noninflammatory; and (4) asymptomatic inflammatory prostatitis. This classification seems to be able to objectively characterize patients according to specific criteria but inefficient to determine the effects of different types of treatment on patient symptoms. On the other hand, the UPOINT classification has a six-point system as follows: U- urinary symptoms, P- psychological symptoms, O- organspecific symptoms (such as the prostate), I- infection-related symptoms, N- neurologic/systemic symptoms, and T- tenderness in the muscles and pelvic floor symptoms. In the case of chronic abacterial prostatitis, the UPOINT phenotyping allows to orient appropriate treatments and to demonstrate encouraging results in terms of clinical response and therapeutic success.

Classification of Prostatitis: What Is the Clinical Usefulness?

Human papillomavirus (HPV) is a very resistant, ubiquitous and sexually transmitted virus that can survive in the environment without a host. HPV is involved in the genesis of cervical cancer in women. Men are usually seen as potential vectors for infection through sexual intercourse but not as final targets of the disease with clinical manifestations that include genital condylomata and some cancers such as penile, oral/neck, anal and, more recently, bladder cancer. On the other hand, aside the evidence of genital condylomata, specific criteria for diagnosis in asymptomatic subjects are still missing to determine both the presence of viral DNA (infection) and the possible role of HPV in the cell transformation to cancer. The prevalence of HPV in males ranges from 7 to 45 %. The quadrivalent vaccine against HPV has proved to be effective in preventing external genital lesions in 90.4 % males aged 16–26 years (95 % CI 69.2–98.1). It has also proved to be effective in preventing precancerous anal lesions in 77.5 % (95 % CI 39.6–93.3) of cases in a per-protocol analysis and in 91.7 % (95 % CI: 44.6–99.8) of cases in a post hoc analysis. Another aspect to highlight is the association between HPV infection and male infertility, probably due to the viral adhesion on the spermatozoa wall. However, several studies on this topic are currently in process. Recently, for prevention purposes the vaccination of 12-year-old males against HPV was recommended. As it has done already for females, a facilitated access to vaccination for males (by price reductions) should be implemented as well. More campaigns to raise awareness through all institutional channels are needed, not only regarding anogenital warts but for HPV-related diseases in general, to achieve adequate vaccine coverage in female cohorts and to reduce HPV-related morbidity.

HPV Infection in Male

Adherence to the international guidelines is important to align the clinical practice and avoid the spreading of antibiotic resistance. The survey outlines that the misuse and overuse of antibiotics are major problems; the analysis of clinical evidence confirms that glycosaminoglycan therapy is a valuable therapeutic approach to prevent the recurrence of the episodes of urinary tract infections and to limit the onset of antibiotic resistance. Urinary tract infections (UTIs) have a significant impact on patient’s quality of life and society. Antibiotic therapy is the primary approach for the management of UTIs; however, it has major limits in the prevention of recurrent UTIs (rUTIs), also increasing the risk of development of multidrug-resistant micro-organisms. The aim of this paper is to discuss the European Association of Urology guidelines for the management of UTIs/rUTIs, the level of adherence to these recommendations, and the available evidence on the use of glycosaminoglycans (GAGs) as a possible alternative treatment to prevent rUTIs. This narrative review and expert meeting report is based on a literature search concerning the currently available UTI guidelines, the results of a survey administered to 227 urologists, and the opinion of an expert panel in the field of UTIs. Results obtained from the literature search showed that adherence to guidelines is not optimal. The survey demonstrated that antibiotics remain one of the treatments of UTIs. However, most of the urologists are aware of the problem caused by the resistance to antibiotics and prefer alternative methods for the prophylaxis of UTIs. Considering the alternative methods, the authors concluded that GAG therapy is highly effective in preventing rUTIs. Adherence to the international guidelines is important to align the clinical practice and avoid the spreading of antibiotic resistance. The survey outlines that the misuse and overuse of antibiotics are major problems; an analysis of clinical evidence confirms that GAG therapy is a valuable therapeutic approach to prevent the recurrence of episodes of UTIs and to limit the onset of antibiotic resistance. Although antibiotic therapy is primarily used for the management of urinary tract infections (UTIs), misuse and overuse of antibiotics are of concern. Adherence to the international guidelines is important to prevent the spreading of antibiotic resistance. Clinical evidence confirms that the use of glycosaminoglycans is a valuable therapeutic approach to prevent UTI recurrence and limit the onset of antibiotic resistance. 

https://doi.org/10.1016/j.euros.2022.07.009

Adherence to European Association of Urology Guidelines and State of the Art of Glycosaminoglycan Therapy for the Management of Urinary Tract Infections: A Narrative Review and Expert Meeting Report

T. Tony Cai

Papers

Estimation and Inference for Minimizer and Minimum of Convex Functions: Optimality, Adaptivity, and Uncertainty Principles

Re: Guido Dalbagni, Kinjal Vora, Matthew Kaag, et al. Clinical outcome in a contemporary series of restaged patients with clinical T1 bladder cancer. Eur Urol 2009;56:903-10.

Classification of Prostatitis: What Is the Clinical Usefulness?

HPV Infection in Male

Adherence to European Association of Urology Guidelines and State of the Art of Glycosaminoglycan Therapy for the Management of Urinary Tract Infections: A Narrative Review and Expert Meeting Report