Computer-assisted Approaches Research Articles

Reduction in alcohol consumption and health status

This study investigated the association between alcohol consumption and health status using cross-sectional national survey data. MEASUREMENTS AND DESIGN: This study relied upon self-report data collected by the 2004 and 2007 Australian National Drug Strategy Household (NDSH) surveys. Households were selected using a multi-stage, stratified-area, random sample design. Both surveys used combinations of the drop-and-collect and computer-assisted telephone interview approaches. Respondents were questioned about their current and past drinking, the presence of formal diagnosis for specific diseases (heart disease, type 2 diabetes, hypertension, cancer, anxiety, depression) and self-perceived general health status. Associations between drinking status, the presence of diagnoses and self-perceptions of general health status among respondents aged 18+ and 45+ were assessed using multivariate logistic regression. Males and females aged 18 years or older and resident in Australia. The sample sizes for the 2004 and 2007 NDSH surveys were 24, 109 and 23, 356, respectively. Respondents with a diagnosis of diabetes, hypertension and anxiety were more likely to have reduced or stopped alcohol consumption in the past 12 months. The likelihood of having reduced or ceased alcohol consumption in the past 12 months increased as perceived general health status declined from excellent to poor. Experience of ill health is associated with subsequent reduction or cessation of alcohol consumption. This may at least partly underlie the observed 'J-shape' function relating alcohol consumption to premature mortality.

Quantifying Word Use to Study Health Literacy in Doctor–Patient Communication

Most health literacy research to date has assessed health literacy using either general reading tests or text-based appraisals of reading and numeracy skills, yet the definition of health literacy includes domains beyond reading ability. Effective oral communication between doctor and patient is an important component of health literacy, but only recently have efforts been made to develop measures that tap into domains beyond those that can be assessed with text-based measures. Focusing on oral exchange, this article describes computer-assisted approaches to quantifying word use and the development of three word-use measures that can be used to study health literacy in transcripts of clinical encounters. The measures can be used to assess either the expressed literacy level of patients or the aural literacy demands made by doctors. Importantly, the computer-assisted quantitative measures described here make it possible for word use to be analyzed at a level of detail that human raters would be hard pressed to attain.

Natural Products in Structure-Assisted Design of Molecular Cancer Therapeutics

Since the late 1990's, novel insights into molecular biology and carcinogenesis enabled the rational design of mechanism-based anticancer therapeutics. The large number of natural product (NP)-derived drugs currently under clinical evaluation and the recent approval of temsirolimus (Torisel) as a first mTOR protein kinase inhibitor indicate that NPs have to be considered not only as a seminal source of cytotoxic, but also as a source of molecularly targeted agents. Whereas molecular modeling is well established as an important and successful method to discover and rationalize bioactivities in medicinal chemistry research, its application has also proven to be also a powerful tool in the field of NPs. This review highlights the impact of computer-assisted approaches on NPs as molecularly targeted anticancer drugs. Examples of applications are provided focusing on innovative targets such as protein kinases, tumour vasculature, epigenetic modulators, heat shock protein (Hsp) 90, and direct apoptosis enhancers.

Histopathological image analysis: a review.

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe.

Assessment of self-reported sexual behavior and condom use among female sex workers in India using a polling box approach: a preliminary report.

The accuracy of behavioral data related to risk for HIV and other sexually transmitted infections is prone to misreporting because of social desirability effects. Because computer-assisted approaches are not always feasible, a noncomputerized interview method for reducing social desirability effects is needed. The previous performance of alternative methods has been limited to aggregate data or constrained by the simplicity of dichotomous-only responses. We designed and tested a "polling box" method for case-attributable, multiple-response survey items in a low literacy population. A cross-sectional survey was conducted with 812 female sex workers in Andhra Pradesh, India. For a subset of questions embedded in a face-to-face survey questionnaire, every third participant was provided graphical response cards upon which to mark their answer and place in a polling box outside the view of the interviewer. Multiple logistic regression analysis was used to test for response differences to questions about socially undesirable, socially desirable, or sensitivity-neutral behaviors in the 2 interview methods. Polling box participants demonstrated higher reporting of risky sexual behaviors and lower reporting of condom use, with no conclusive response patterns among sensitivity-neutral items. Our findings suggest that the polling box approach provides a promising technique for improving the accurate reporting of sensitive behaviors among a low-literacy population in a resource poor setting. Additional research is needed to test logistical adaptations of the polling box approach.

Towards automated segmentation of forest inventory polygons on high spatial resolution satellite imagery

High spatial resolution satellite imagery, with pixel sizes of one metre or less, are increasingly available. These data provide an accessible and flexible source of information for forest inventory purposes. In addition, the digital nature of these data provides an opportunity for automated and computer-assisted approaches for forest stand delineation to be considered. Specifically, automation has the potential to realize cost savings by minimizing the time required for manual delineation of forest stands; however, inappropriate automation could result in increased costs due to time-consuming revisions of automated delineations. The aim of this research is to present, through example, investigations of an automated segmentation approach for delineating homogeneous forest stands on high spatial resolution satellite imagery. An evaluation of the suitability of IKONOS 1-m panchromatic data for this application is also presented, along with several key issues that must be considered regarding automated segmentation approaches. Key words: forest inventory, segmentation, automation, IKONOS, high spatial resolution satellite, photo interpretation, stand delineation, object

Measuring Political Debate on the Chinese Internet Forum

This paper addresses the methodological issue of how to quantify and measure seemingly chaotic, crude and impulsive online interactions in Chinese Internet forums, which have played an increasingly important role in shaping the country’s political spectrum. It introduces an integrated research methodology, designed and developed specifically in a four-year project conducted by this author on the Chinese Internet forums, the first of its kind which scrutinises the interactive content of 14 major political forums in China and overseas over a one-year period, consisting of over 450,000 postings. Using commercial and self-developed online content analysis tools, this methodology features a series of computer-assisted data collection, quantitative analysis, and qualitative approaches. It investigates first from a wide range of mega data extracted online to capture the general dynamics of the Chinese Forum. It then focuses on the selected categories of text data to delineate the linkage of global connectivity among forum networks and reveal the spectrum of discourse and pattern of deliberation. The paper, which conceptualises Chinese Internet forums as discursive public spaces mediated by the new online conversational media, aims to establish a series of applicable methods to study the publicly accessed interactive content of online political talk in the global network of the Chinese Internet.

From Musical Grammars to Music Cognition in the 1980s and 1990s: Highlights of the History of Computer-Assisted Music Analysis

While approaches that had already established historical precedents – computer-assisted analytical approaches drawing on statistics and information theory – developed further, many research projects conducted during the 1980s aimed at the development of new methods of computer-assisted music analysis. Some projects discovered new possibilities related to using computers to simulate human cognition and perception, drawing on cognitive musicology and Artificial Intelligence, areas that were themselves spurred on by new technical developments and by developments in computer program design. The 1990s ushered in revolutionary methods of music analysis, especially those drawing on Artificial Intelligence research. Some of these approaches started to focus on musical sound, rather than scores. They allowed music analysis to focus on how music is actually perceived. In some approaches, the analysis of music and of music cognition merged. This article provides an overview of computer-assisted music analysis of the 1980s and 1990s, as it relates to music cognition. Selected approaches are being discussed.

MicroARN, ARN C/D et empreinte génomique parentale

Experimental and computer-assisted approaches have led us to identify hundreds of small non-coding RNA (ncRNAs) whose genes - clustered at two chromosomal domains (the DLK1-GTl2 region/human 15q11q13 and the SNURF-SNRPN/human 14q32 loc) - are subjected to genomic imprinting. Here, we discuss their genomic organization, their expression pattern and their potential functions.

Lifestyle interventions in cancer survivors: designing programs that meet the needs of this vulnerable and growing population.

In the world today, there are roughly 25 million cancer survivors. Although the increasing numbers of survivors testifies to the success of early detection and treatment, there is a downside. Cancer survivors are at increased risk for second cancers, other forms of comorbidity (e.g., cardiovascular disease, diabetes, osteoporosis), and functional decline. Lifestyle factors, such as a healthy diet, regular exercise, and smoking cessation may prevent these conditions and improve survivors' quality of life. Data also are accumulating to suggest that healthful lifestyle practices and successful weight management may prevent progressive or recurrent disease. Previous surveys conducted among both adult and pediatric cancer survivors indicate that most survivors have high levels of interest in diet and exercise interventions. Additionally, survivors who smoke report high levels of interest in interventions aimed at smoking cessation. Many factors, such as intervention timing and duration and channels of delivery, must be carefully considered in developing interventions that best meet the needs of this vulnerable population. Total transparency also is necessary in reporting the results of trials to ensure the inclusion of information regarding proportional accrual, attrition, and study sample sociodemographic characteristics to move toward the development of interventions most likely to gain broad-scale acceptance and adherence. Home-based interventions that rely on telephone counseling, mailed materials, or computer-assisted approaches offer promising means of reaching the geographically dispersed population of cancer survivors. More research is necessary to develop interventions that can reach and effectively promote long-term behavior change in this ever-increasing population.

Integrated in Silico Tools for Exploiting the Natural Products’ Bioactivity

Whereas computational methods for molecular design are well established in medicinal chemistry research, their application in the field of natural products is still not exhaustively explored. This article gives a short introduction into both the potential for the application of computer-assisted approaches, such as pharmacophore modelling, virtual screening, docking, and neural networking to efficiently access the bioactive metabolites, and the requirements and limitations related to this specific field. The challenge is which selection criteria and/or multiple filtering tools to apply for a target-oriented isolation of potentially bioactive secondary metabolites. Application examples are provided where in silico tools and classical methods used by natural product scientists are used in an effort to maximize their efficacy in drug discovery. Thus, integrated computer-assisted strategies may help to process the huge amount of available structural and biological information in a reasonably short time for a straightforward search of bioactive natural products.

Small non-coding RNAs and genomic imprinting

Experimental and computer-assisted approaches have led to the identification of hundreds of imprinted small RNA genes, mainly clustered in two chromosomal domains (human 15q11→q13 and 14q32 loci). The genes are only detected in placental mammals and belong to the C/D RNA and microRNA gene families. These are small non-coding RNAs involved in RNA-guided post-transcriptional RNA modifications and RNA-mediated gene silencing, respectively. Here, we discuss their potential functions and report the identification of novel small RNA genes lying within (or nearby) known imprinted chromosomal domains.

Computer technology in detection and staging of prostate carcinoma: A review

After two decades of increasing interest and research activity, computer-assisted diagnostic approaches are reaching the stage where more routine deployment in clinical practice is becoming a possibility [Kruppinski, E.A., 2004. Computer-aided detection in clinical environment: Benefits and challenges for radiologists. Radiology 231, 7–9]. This is particularly the case in the analysis of mammographic images [Helvie, M.A., Hadjiiski, L., Makariou, E., Chan, H.P., Petrick, N., Sahiner, B., Lo, S.C., Freedman, M., Adler, D., Bailey, J., Blane, C., Hoff, D., Hunt, K., Joynt, L., Klein, K., Paramagul, C., Patterson, S.K., Roubidoux, M.A., 2004. Sensitivity of noncommercial computer-aided detection system for mammographic breast cancer detection: pilot clinical trial. Radiology 231, 208–214] and in the detection of pulmonary nodules [Reeves, A.P., Kostis, W.J., 2000. Computer-aided diagnosis for lung cancer. Radiol. Clin. North Am. 38, 497–509]. However, similar approaches can be applied more widely with the promise of increasing clinical utility in other areas. We review how computer-aided approaches may be applied in the diagnosis and staging of prostatic cancer. The current status of computer technology is reviewed, covering artificial neural networks for detection and staging, computerised biopsy simulation and computer-assisted analysis of ultrasound and magnetic resonance images.

Pharmacophore Modeling, Docking, and Principal Component Analysis Based Clustering: Combined Computer-Assisted Approaches To Identify New Inhibitors of the Human Rhinovirus Coat Protein

The development and application of a sophisticated virtual screening and selection protocol to identify potential, novel inhibitors of the human rhinovirus coat protein employing various computer-assisted strategies are described. A large commercially available database of compounds was screened using a highly selective, structure-based pharmacophore model generated with the program Catalyst. A docking study and a principal component analysis were carried out within the software package Cerius and served to validate and further refine the obtained results. These combined efforts led to the selection of six candidate structures, for which in vitro anti-rhinoviral activity could be shown in a biological assay.

Computerized analysis of mesothelioma on CT scans

Computed tomography (CT) has become an essential tool for monitoring the progression of mesothelioma tumor or a patient's response to treatment. Despite the accepted role of CT for the evaluation of mesothelioma, however, the current standard practice remains the manual measurement of tumor extent on CT scans. The process of manual measurement acquisition is tedious and subject to inconsistency. We have quantitatively assessed the variability of manual mesothelioma measurements both in baseline CT scans and in the context of tumor response classification across temporally sequential scans. To facilitate the acquisition of mesothelioma measurements, we have developed and evaluated computerized methods for the assessment of mesothelioma tumor thickness on CT scans; we anticipate that such computer-assisted approaches will make the radiologic assessment of mesothelioma more efficient, thus facilitating the establishment of improved clinical protocols.

DOCUMENTATION IN BRONCHOLOGY

With the performance of more endoscopic procedures and newly developed diagnostic and therapeutic modalities, a wealth of information around the actual procedure is created. To date, accepted guidelines for standardized documentation are lacking. The authors present recommendations for minimal guidelines that may help to facilitate good documentation and also address future developments that will be possible with the help of computer-assisted approaches.

Methods and systems to detect adverse drug reactions in hospitals.

Detection of adverse drug reactions (ADRs) in hospitals offers the chance to detect serious ADRs resulting in hospitalisation and ADRs occurring in hospitalised patients, i.e. patients with high comorbidity and receiving drugs that are administered only in hospitals. The most commonly applied methods involve stimulated spontaneous reporting of doctors and nurses, comprehensive collection by trained specialists and, more recently, computer-assisted approaches using routine data from hospital information systems. The different methods of ADR detection used result in different rates and types of ADRs and, consequently, in different drug classes being responsible for these ADRs. Another factor influencing the results of surveys is the interpretation of the term ADR, where some authors adhere to the strict definition of the World Health Organization and many others include intended and unintended poisoning as well as errors in prescribing and dispensing, thus referring to adverse drug events. Depending on the method used for screening of patients, a high number of possible ADRs and only few definite ADRs are found, or vice versa. These variations have to be taken into account when comparing the results of further analyses performed with these data. ADR rates and incidences in relation to the number of drugs prescribed or patients exposed have been calculated in only a few surveys and projects, and this interesting pharmacoepidemiological approach deserves further study. In addition, the pharmacoeconomic impact of ADRs, either resulting in hospitalisation or prolonging hospital stay, has been estimated using different approaches. However, a common standardised procedure for such calculations has not yet been defined. Although detection of ADRs in hospitals offers the opportunity to detect severe ADRs of newly approved drugs, these ADRs are still discovered by spontaneous reporting systems. The prospects offered by electronic hospital information systems as well as implementation of pharmacoepidemiological approaches increases the possibilities and the value of ADR detection in hospitals.

The Berlin "protein structure factory" initiative: a technology-oriented approach to structural genomics.

The Ernst Schering Research Foundation Workshop 34 on Data Mining in Structural Biology: Signal Transduction and Beyond, which served as the basis for this volume, coincided almost perfectly with the public announcement of a “working draft” of the human genome sequence (Macilwaine 2000). This major publicity event followed closely completion of the DNA sequencing of the two smallest human chromosomes (Dunham et al. 1999; Hattori et al. 2000). In addition, a rapidly growing number of DNA sequences representing complete genomes from all kingdoms of life is known. It is anticipated that these landmark achievements will have a major impact on medicine and pharmacology (Roses 2000; Sander 2000). However, new insight does not flow directly from genomic sequences: Computer-assisted (Bork and Eisenberg 1998; Enright et al. 1999; Marcotte et al. 1999; Sali 1999; Eisenberg et al. 2000) and experimental approaches (Gerhold et al. 1999; Lockhart and Winzeler 2000; Oliver 2000; Pandey and Mann 2000; Roberts et al. 2000; Uetz et al. 2000) need to be developed and are, indeed, being developed in order to complement the vast amount of genomic information with the corresponding data pertaining to the gene products and their interactions.

A Comparison of Computer-Assisted Psychotherapy and Cognitive-Behavioral Therapy in Groups

This study is the first independent, randomized controlled study in a clinical setting of a computer-assisted therapy program (Therapeutic Learning Program; TLP) developed to permit individualized therapy in a group setting. This software differs from other computer-assisted approaches in that targets for change are chosen by the patient rather than determined by the software. TLP was compared to a standard cognitive-behavioral treatment in 109 patients with 6-month follow-up. Although both treatments were associated with a significant reduction in symptoms of anxiety and depression at posttreatment and follow-up, no differences were found between treatments with respect to patient-rated satisfaction and effectiveness, clinician ratings of improvement, and scores on measures of anxiety and depression. At treatment midpoint patients tended to give more neutral ratings of satisfaction and treatment effectiveness of the TLP treatment, perhaps suspending judgment about this more novel treatment until its completion. It is concluded that at least one form of computer-assisted psychotherapy is as effective and acceptable to patients in a clinical setting as standard short-term cognitive-behavioral therapy conducted by experienced clinicians.

NMR Characterization of Copolymers That Exhibit Nonsymmetric Compositional Heterogeneity

The perturbed first-order Markovian model has been developed for copolymers that exhibit nonsymmetric chemical compositional distribution. An exponentially modified Gaussian function is first used to approximate the distribution. The theoretical probability expressions for the comonomer diads, triads, and tetrads are derived. Using these expressions, one can analyze the observed NMR data and fit them to the perturbed Markovian model. The formalism given herein is next extended to the general case of an arbitrary chemical composition distribution. Computer programs have been written to facilitate the analyses, and examples are given to illustrate the use of these computer-assisted approaches.