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PubMed2001

UMIN--key information infrastructure for the Japanese medical community.

University hospital Medical Information Network (UMIN) was established in 1989 as a collaborative project of national university hospitals in Japan funded by the Ministry of Education, Science, Sports, and Culture, and it started its Internet-based service for medical professionals in 1995. Since then, many services including those for academic societies and research groups have been added. Currently, due to batch registration of the members of large academic societies, the number of registered users and Web accesses are rapidly increasing (about 87,000 registered users and 4,500,000 page views in November, 2000). More than one hundred homepages of academic societies and research groups (including forty- two member-only ones) and one thousand mailing lists are operated. More than one hundred thirty academic societies collect abstracts using the UMIN server. All the Internet-based clinical and epidemiological research projects in Japan are now under way using UMIN. The characteristics of UMIN are its large variety of services and large number of user accounts of medical professionals, which are beneficial to both users and information service providers. UMIN is now important for some medical specialties and will be so for further ones in the future. UMIN is, in fact, evolving into a collaborative project of the Japanese medical community and is considered as its key information infrastructure.

Hospitals, University↗
PubMed1984

[Strategy for the formation of human resources in biomedical basic sciences].

The author describes the strategy followed in the Higher Institute of Medical Sciences of Havana for manpower training in basic biomedical sciences. This strategy is based on the Government's general policy for scientific development, and has resulted in the establishment of a network of centers of higher education and research institutes employing more than 3,800 professional and technical staff. Four-year specialization courses have been devised for physicians and dentists, and master's programs for which nonmedical professionals may apply. A system for the obtaining of scientific degrees has been structured together with an extensive program of graduate courses and training. The author comments on the excellent results obtained from the planned, efficient use of bilateral agreements with institutions in other countries and of the possibilities for training and qualification of specialists, the experience in which has already been offered to less developed countries.

Cuba↗
PubMed1995

[Brain and behavior].

The author briefly reviews the milestones in recent developments in brain and behaviour research. The psychological and physiological disciplines have developed in parallell, with mutual benefit to both areas of research. Cognitive models in psychology, and taxonomy based on psychological analyses, have been instrumental in formulating proper hypotheses in brain research. Data from brain and behaviour research have confirmed cognitive models and taxonomy in cognitive science and in ethological studies of animals. A complex, multidisciplinary and multi-factorial concept of a self-regulating central nervous network emerges, to replace earlier concepts of single neurons functioning in simple reflex chains.

Animals↗
PubMed2003

Prediction of survival in surgical unresectable lung cancer by artificial neural networks including genetic polymorphisms and clinical parameters.

Lung cancer, a common malignancy in Taiwan, involves multiple factors, including genetics and environmental factors. The survival time is very short once cancer is diagnosed as being in advanced stage and surgically unresectable. Therefore, a good model of prediction of disease outcome is important for a treatment plan. We investigated the survival time in advanced lung cancer by using computer science from the genetic polymorphism of the p21 and p53 genes in conjunction with patients' general data. We studied 75 advanced and surgical unresectable lung cancer patients. The prediction of survival time was made by comparing real data obtained from follow-up periods with data generated by an artificial neural network (ANN). The most important input variable was the clinical staging of lung cancer patients. The second and third most important variables were pathological type and responsiveness to treatment, respectively. There were 25 neurons in the input layer, four neurons in the hidden layer-1, and one neuron in the output layer. The predicted accuracy was 86.2%. The average survival time was 12.44 +/- 7.95 months according to real data and 13.16 +/- 1.77 months based on the ANN results. ANN provides good prediction results when clinical parameters and genetic polymorphisms are considered in the model. It is possible to use computer science to integrate the genetic polymorphisms and clinical parameters in the prediction of disease outcome. Data mining provides a promising approach to the study of genetic markers for advanced lung cancer.

Adult↗
PubMed2001

Translation of nutritional sciences into medical education: the Nutrition Academic Award Program.

For the past 40 y the scientific community has decried the inadequacy of the training of physicians and other health professionals in the subject of human nutrition. In 1997 the National Heart, Lung, and Blood Institute developed the Nutrition Academic Award (NAA) Program, an initiative to improve nutrition training across a network of US medical schools. The purpose of this funding, which began in 1998, is to support the development and enhancement of nutrition curricula for medical students, residents, and practicing physicians to learn principles and practice skills in nutrition. The NAA recipients developed the Nutrition Curricular Guide for Training Physicians, a plan to incorporate clinical guidelines into physician practice skills, create educational and assessment practice tools, and evaluate curricula, materials, and teaching tools. Dissemination of NAA activities and materials will be facilitated by a national website, presentations and publications, and consultants and advisors from the NAA nutrition education programs. The NAA Program constitutes a major new effort to enhance nutrition knowledge and skills among health care providers and to effectively apply the science of human nutrition to clinical medicine. This article describes the purpose and aims of the NAA Program, the organizational structure of the network of recipients, a profile of the recipients and individual programs at 21 medical schools, the various strategies to overcome barriers in training physicians in human nutrition, and collaborative and dissemination efforts.

Awards and Prizes↗
PubMed2026

Molecular targeted therapy in combination with chemotherapy for the treatment of platinum-resistant/refractory ovarian cancer (PROC): a systematic review and network meta-analysis.

BACKGROUND: Although single-agent chemotherapy is the most common approach for treating platinum-resistant or refractory ovarian cancer (PROC), there is growing evidence that combining molecular targeted agents with chemotherapy is beneficial, especially for certain patient groups. However, the most effective combination regimen remains elusive. OBJECTIVES: This Bayesian network meta-analysis (NMA) aims to identify the best combination therapy for PROC. METHODS: Relevant studies were searched in PubMed, EMBASE, Web of Science and the Cochrane Central Register of Controlled Trials from their inception until October 2024. The primary outcomes were overall survival (OS), progression-free survival (PFS) and adverse events (AEs). Statistical analyses were performed using the GEMTC package (1.0-2) and R 4.2.0. This review was registered in PROSPERO (CRD42023428414). RESULTS: Our analysis of 22 randomized controlled trials (RCTs) (n = 3408) demonstrated that chemotherapy combinations with bevacizumab (hazard ratio (HR) = 0.52-0.65), sorafenib (HR = 0.65, 95% confidence interval (CI): 0.45-0.93) or adavosertib (HR = 0.56, 95%CI: 0.35-0.90) significantly improved OS and PFS versus chemotherapy alone. Notably, adavosertib + gemcitabine was associated with an increased risk of grade 3-4 AEs (relative risk (RR) = 1.8, 95%CI: 1.3-2.7), but these were generally manageable. CONCLUSIONS: Bevacizumab-based combinations demonstrate consistent benefits across multiple regimens for PROC. Paclitaxel + bevacizumab emerges as the optimal balance of efficacy and safety. Topotecan + sorafenib could be an alternative for patients who are ineligible for anti-angiogenic therapy.

Humans↗
PubMed2005

Harnessing genomics to improve health in the Eastern Mediterranean Region - an executive course in genomics policy.

BACKGROUND: While innovations in medicine, science and technology have resulted in improved health and quality of life for many people, the benefits of modern medicine continue to elude millions of people in many parts of the world. To assess the potential of genomics to address health needs in EMR, the World Health Organization's Eastern Mediterranean Regional Office and the University of Toronto Joint Centre for Bioethics jointly organized a Genomics and Public Health Policy Executive Course, held September 20th-23rd, 2003, in Muscat, Oman. The 4-day course was sponsored by WHO-EMRO with additional support from the Canadian Program in Genomics and Global Health. The overall objective of the course was to collectively explore how to best harness genomics to improve health in the region. This article presents the course findings and recommendations for genomics policy in EMR. METHODS: The course brought together senior representatives from academia, biotechnology companies, regulatory bodies, media, voluntary, and legal organizations to engage in discussion. Topics covered included scientific advances in genomics, followed by innovations in business models, public sector perspectives, ethics, legal issues and national innovation systems. RESULTS: A set of recommendations, summarized below, was formulated for the Regional Office, the Member States and for individuals.* Advocacy for genomics and biotechnology for political leadership;* Networking between member states to share information, expertise, training, and regional cooperation in biotechnology; coordination of national surveys for assessment of health biotechnology innovation systems, science capacity, government policies, legislation and regulations, intellectual property policies, private sector activity;* Creation in each member country of an effective National Body on genomics, biotechnology and health to:- formulate national biotechnology strategies- raise biotechnology awareness- encourage teaching and training of biotechnology- devise integration of biotechnology within national health systems. CONCLUSION: The recommendations provide the basis for a road map for EMR to take steps to harness biotechnology for better and more equitable health. As a result of these recommendations, health ministers from the region, at the 50th Regional Committee Meeting held in October 2003, have urged Member States to establish national bodies of biotechnology to formulate a strategic vision for developing biotechnology in the service of the region's health. These efforts promise to raise the profile of genomics in EMR and increase regional cooperation in this exciting new field.

Editorial↗
PubMed2003

Special report on the political and social contexts of health: Part I. Introduction: objectives and purposes of the study.

This article introduces a series of research projects (carried out by the International Network on Social Inequalities and Health) focused on the impact of politics on policy and the consequences for health and quality of life, an area that has been understudied in the social science literature. The introduction describes the conceptual model that guided the research, centered on the study of how political parties and social agents (such as trade unions) affect social inequalities and mortality indicators through labor market and welfare state policies. The major theme of this research is whether political and social interventions matter in health policy and health outcomes. The introduction also describes the different types of research projects carried out by the International Network at the national levels (among OECD countries) and at the regional and local levels (in the United Kingdom, Italy, Germany, Spain, and Sweden). This Journal issue presents the multinational study and the U.K. case study; the next issue will include the Italian, German, Spanish, and Swedish case studies and the summary and conclusions.

Developed Countries↗
PubMed1998

Addressing the health information needs of rural Missouri health care providers: an IAIMS assistant experience.

A one-year internship at the University of Missouri-Columbia offered an opportunity for a health sciences librarian to contribute to Integrated Advanced Information Management Systems (IAIMS) activities and take information management ideas back home. The IAIMS Assistant addressed information access issues. The Assistant helped to develop and administer a "Rural Provider Questionnaire" to assess the information needs of rural Missouri health care providers. The Health Sciences Library developed a Web page to bring together services and information resources in response to the perceived needs of health care providers associated with the Health Sciences Center. The article discusses the librarians' role in IAIMS initiatives.

Community Networks↗
PubMed2026

The efficacy of non-invasive brain stimulation interventions in obsessive-compulsive disorder management: A network meta-analysis of randomized controlled trials.

Non-invasive brain stimulation (NIBS) has been widely used as an alternative treatment for obsessive compulsive disorder (OCD). However, the most effective NIBS parameters are unclear. To compare the efficacy of NIBS in OCD. We conducted a systematic review and network meta-analyses (NMA) to combine direct and indirect comparisons of NIBS.Systematic searches were conducted in Cochrane CENTRAL, EMBASE, PubMed, and Web of Science from inception to June 20, 2025. Forty-two randomized sham-controlled trials (n = 1456) were included. All statistical analyses were conducted with R statistical software. Bayesian NMAs mainly using the BUGSnet package and gemtc package. Five NIBS protocols produced statistically significant reductions in Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores compared with sham stimulation: high-frequency rTMS over the FzFCz (Hf-rTMS-FzFCz; MD -11.77, 95% CrI -20.62 to -3.09), low-frequency rTMS over F3F4 (Lf-rTMS-F3F4; MD -9.93, 95% CrI -18.07 to -1.65), low-frequency rTMS over FCz (Lf-rTMS-FCz; MD -3.25, 95% CrI -6.06 to -0.40), high-frequency deep TMS over FzFC (Hf-dTMS-FzFC; MD -6.48, 95% CrI -12.32 to -0.50), and 2 mA anodal tDCS over F3 with cathodal over Fp2 (MD -9.34, 95% CrI -16.01 to -3.03).For secondary outcomes, high-frequency deep rTMS over FzFCz produced the largest reduction both in depressive symptoms (SMD -1.24, 95% CrI -1.92 to -0.55) and anxiety scores (SMD -1.88, 95% CrI -2.62 to -1.11), but had no effect on Clinical Global Impression-Severity (CGI-S) scores.Specific NIBS protocols are safe and effective adjunctive treatments for OCD, with promising yet inconclusive improvements in comorbid depressive symptoms. Further high-quality, head-to-head trials are needed.

Humans↗
PubMed1995

NASA high performance computing, communications, image processing, and data visualization-potential applications to medicine.

High-speed information processing technologies being developed and applied by the Jet Propulsion Laboratory for NASA and Department of Defense mission needs have potential dual-uses in telemedicine and other medical applications. Fiber optic ground networks connected with microwave satellite links allow NASA to communicate with its astronauts in Earth orbit or on the moon, and with its deep space probes billions of miles away. These networks monitor the health of astronauts and or robotic spacecraft. Similar communications technology will also allow patients to communicate with doctors anywhere on Earth. NASA space missions have science as a major objective. Science sensors have become so sophisticated that they can take more data than our scientists can analyze by hand. High performance computers--workstations, supercomputer and massively parallel computers are being used to transform this data into knowledge. This is done using image processing, data visualization and other techniques to present the data--one's and zero's in forms that a human analyst can readily relate to and understand. Medical sensors have also explored in the in data output--witness CT scans, MRI, and ultrasound. This data must be presented in visual form and computers will allow routine combination of many two dimensional MRI images into three dimensional reconstructions of organs that then can be fully examined by physicians. Emerging technologies such as neural networks that are being "trained" to detect craters on planets or incoming missiles amongst decoys can be used to identify microcalcification in mammograms.

Image Interpretation, Computer-Assisted↗
PubMed2006

Neural networks for longitudinal studies in Alzheimer's disease.

OBJECTIVE: Alzheimer's disease affects a growing population of elderly people today. The predictions about the course of the disease is a key component of health care decision making for patients with Alzheimer's. The physician's prognosis and predicted trajectory of cognitive decline often form the basis of treatment and health care decisions taken by patients and their families. These predictions are difficult to make because of the high variability and non-linearity exhibited by individual patterns of cognitive decline. This paper presents a new method of predicting the course of a disease using longitudinal data collected through multiple clinic visits. Longitudinal databases are similar to temporal databases, with some important differences--data is collected at irregular time intervals that are patient specific and also a varying number of observations are made for each patient, depending upon the number of times the patient visited the clinic. We propose a new type of neural network called the mixed effects neural network (MENN) model that can incorporate this type of longitudinal information. MATERIAL AND METHODS: We have used longitudinal data on 704 subjects enrolled at the Layton aging and research center (LAARC) at Oregon Health and Science University. A back-propagation algorithm, modified for longitudinal data is used to obtain the weight parameters of the MENN. The modified back-propagation algorithm is further embedded in an iterative procedure that estimates the noise variance and the parameters that capture the longitudinal (temporal) correlation structure. RESULTS: We have compared the performance of the MENN with linear mixed effects models and standard neural networks (NN). MENN show better performance (misclassification rate = 0.13 and relative MSE = 0.35) as compared to standard NN (misclassification rate = 0.34 and relative MSE = 2.74) and linear mixed effects models (misclassification rate = 0.14 and relative MSE = 0.4). CONCLUSION: The results show that this method can be a useful tool for predicting non-linear disease trajectories and uncovering significant prognostic factors in longitudinal databases.

Aged↗