Analyzing Digital Image by Deep Learning for Melanoma Diagnosis

Image classi cation is an important task in many medical applications, in order to achieve an adequate diagnostic of di erent le- sions. Melanoma is a frequent kind of skin cancer, which most of them can be detected by visual exploration. Heterogeneity and database size are the most important di culties to overcome in order to obtain a good classi cation performance. In this work, a deep learning based method for accurate classi cation of wound regions is proposed. Raw images are fed into a Convolutional Neural Network (CNN) producing a probability of being a melanoma or a non-melanoma. Alexnet and GoogLeNet were used due to their well-known e ectiveness. Moreover, data augmentation was used to increase the number of input images. Experiments show that the compared models can achieve high performance in terms of mean ac- curacy with very few data and without any preprocessing.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Training Residents to Employ Self-efficacy-enhancing Interviewing Techniques: Randomized Controlled Trial of a Standardized Patient Intervention

Current interventions to enhance patient self-efficacy, a key mediator of health behavior, have limited primary care application. To explore the effectiveness of an office-based intervention for training resident physicians to use self-efficacy-enhancing interviewing techniques (SEE IT). Randomized controlled trial. Family medicine and internal medicine resident physicians (N = 64) at an academic medical center. Resident use of SEE IT (a count of ten possible behaviors) was coded from audio recordings of the physician-patient portion of two standardized patient (SP) instructor training visits and two unannounced post-training SP visits, all involving common physical and mental health conditions and behavior change issues. One post-training SP visit involved health conditions similar to those experienced in training, while the other involved new conditions. Experimental group residents demonstrated significantly greater use of SEE IT than controls, starting after the first training visit and sustained through the final post-training visit. The mean effect of the intervention was significant [adjusted incidence rate ratio for increased use of SEE IT = 1.94 (95% confidence interval = 1.34, 2.79; p < 0.001)]. There were no significant effects of resident gender, race/ethnicity, specialty, training level, or SP health conditions. SP instructors can teach resident physicians to apply SEE IT during SP office visits, and the effects extend to health conditions beyond those used for training. Future studies should explore the effects of the intervention on practicing physicians, physician use of SEE IT during actual patient visits, and its influence on patient health behaviors and outcomes

Telemonitoring for Patients With Chronic Heart Failure: A Systematic Review

Background Telemonitoring, the use of communication technology to remotely monitor health status, is an appealing strategy for improving disease management. Methods and Results We searched Medline databases, bibliographies, and spoke with experts to review the evidence on telemonitoring in heart failure patients. Interventions included: telephone-based symptom monitoring (n = 5), automated monitoring of signs and symptoms (n = 1), and automated physiologic monitoring (n = 1). Two studies directly compared effectiveness of 2 or more forms of telemonitoring. Study quality and intervention type varied considerably. Six studies suggested reduction in all-cause and heart failure hospitalizations (14% to 55% and 29% to 43%, respectively) or mortality (40% to 56%) with telemonitoring. Of the 3 negative studies, 2 enrolled low-risk patients and patients with access to high quality care, whereas 1 enrolled a very high-risk Hispanic population. Studies comparing forms of telemonitoring demonstrated similar effectiveness. However, intervention costs were higher with more complex programs ($8383 per patient per year) versus less complex programs ($1695 per patient per year). Conclusion The evidence base for telemonitoring in heart failure is currently quite limited. Based on the available data, telemonitoring may be an effective strategy for disease management in high-risk heart failure patients

Effects of increase in temperature and open water on transmigration and access to health care by the Nenets reindeer herders in northern Russia

Background . The indigenous Nenets reindeer herders in northern Russia annually migrate several hundred kilometers between summer and winter pastures. In the warming climate, ice-rich permafrost and glaciers are being significantly reduced and will eventually disappear from parts of the Arctic. The emergent changes in hydrological cycles have already led to substantial increases in open water that stays unfrozen for longer periods of time. This environmental change has been reported to compromise the nomadic Nenets’ traditional way of life because the presence of new water in the tundra reduces the Nenets’ ability to travel by foot, sled, or motor vehicle from the summer transitory tundra campsites in order to access healthcare centers in villages. New water can also impede their access to family and community at other herder camps and in the villages. Although regional and global models predicting hydrologic changes due to climate changes exist, the spatial resolution of these models is too coarse for studying how increases in open water affect health and livelihoods. To anticipate the full health impact of hydrologic changes, the current gap between globally forecasted scenarios and locally forecasted hydrologic scenarios needs to be bridged. Objectives . We studied the effects of the autumn temperature anomalies and increases in open water on health care access and transmigration of reindeer herders on the Kanin Peninsula. Design . Correlational and time series analyses were completed. Methods . The study population consisted of 370 full-time, nomadic reindeer herders. We utilized clinical visit records, studied surface temperature anomalies during autumn migrations, and used remotely sensed imagery to detect water bodies. Spearman correlation was used to measure the relationship between temperature anomalies and the annual arrival of the herders at the Nes clinic for preventive and primary care. Piecewise regression was used to model change in mean autumnal temperature anomalies over time. We also created a water body product to detect inter-annual changes in water area. Results . Correlation between arrivals to the Nes clinic and temperature anomalies during the fall transmigration (1979–2011) was r = 0.64, p = 0.0004; 95% CI (0.31; 0.82). Regression analysis estimated that mean temperature anomalies during the fall migration in September–December were stochastically stationary pre-1991 and have been rising significantly (p < 0.001) since then. The rate of change was estimated at +0.1351°C/year, SE = 0.0328, 95% CI (+0.0694, +0.2007). The amount of detected water fluctuated significantly interannually (620–800 km2). Conclusions . Later arrival of freezing temperatures in the autumn followed by the earlier spring thaws and more open water delay transmigration and reduce herders’ access to health care. The recently observed delays in arrival to the clinic are likely related to the warming trend and to concomitant hydrologic changes

Hybrid copula mixed models for combining case-control and cohort studies in meta-analysis of diagnostic tests

Copula mixed models for trivariate (or bivariate) meta-analysis of diagnostic test accuracy studies accounting (or not) for disease prevalence have been proposed in the biostatistics literature to synthesize information. However, many systematic reviews often include case-control and cohort studies, so one can either focus on the bivariate meta-analysis of the case-control studies or the trivariate meta-analysis of the cohort studies, as only the latter contains information on disease prevalence. In order to remedy this situation of wasting data we propose a hybrid copula mixed model via a combination of the bivariate and trivariate copula mixed model for the data from the case-control studies and cohort studies, respectively. Hence, this hybrid model can account for study design and also due to its generality can deal with dependence in the joint tails. We apply the proposed hybrid copula mixed model to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma

Predicting complete loss to follow-up after a health-education program: number of absences and face-to-face contact with a researcher

<p>Abstract</p> <p>Background</p> <p>Research on health-education programs requires longitudinal data. Loss to follow-up can lead to imprecision and bias, and <it>complete </it>loss to follow-up is particularly damaging. If that loss is predictable, then efforts to prevent it can be focused on those program participants who are at the highest risk. We identified predictors of complete loss to follow-up in a longitudinal cohort study.</p> <p>Methods</p> <p>Data were collected over 1 year in a study of adults with chronic illnesses who were in a program to learn self-management skills. Following baseline measurements, the program had one group-discussion session each week for six weeks. Follow-up questionnaires were sent 3, 6, and 12 months after the baseline measurement. A person was classified as completely lost to follow-up if none of those three follow-up questionnaires had been returned by two months after the last one was sent.</p> <p>We tested two hypotheses: that complete loss to follow-up was directly associated with the number of absences from the program sessions, and that it was less common among people who had had face-to-face contact with one of the researchers. We also tested predictors of data loss identified previously and examined associations with specific diagnoses.</p> <p>Using the unpaired t-test, the U test, Fisher's exact test, and logistic regression, we identified good predictors of complete loss to follow-up.</p> <p>Results</p> <p>The prevalence of complete loss to follow-up was 12.2% (50/409). Complete loss to follow-up was directly related to the number of absences (odds ratio; 95% confidence interval: 1.78; 1.49-2.12), and it was inversely related to age (0.97; 0.95-0.99). Complete loss to follow-up was less common among people who had met one of the researchers (0.51; 0.28-0.95) and among those with connective tissue disease (0.29; 0.09-0.98). For the multivariate logistic model the area under the ROC curve was 0.77.</p> <p>Conclusions</p> <p>Complete loss to follow-up after this health-education program can be predicted to some extent from data that are easy to collect (age, number of absences, and diagnosis). Also, face-to-face contact with a researcher deserves further study as a way of increasing participation in follow-up, and health-education programs should include it.</p

The devil is in the detail - a multifactorial intervention to reduce blood pressure in co-existing diabetes and chronic kidney disease: a single blind, randomized controlled trial

<p>Abstract</p> <p>Background</p> <p>About 30-60% of individuals are non-adherent to their prescribed medications and this risk increases as the number of prescribed medications increases. This paper outlines the development of a consumer-centred <it>Me</it>dicine <it>S</it>elf-<it>M</it>anagement <it>I</it>ntervention (MESMI), designed to improve blood pressure control and medication adherence in consumers with diabetes and chronic kidney disease recruited from specialist outpatients' clinics.</p> <p>Methods</p> <p>We developed a multifactorial intervention consisting of Self Blood Pressure Monitoring (SBPM), medication review, a twenty-minute interactive Digital Versatile Disc (DVD), and follow-up support telephone calls to help consumers improve their blood pressure control and take their medications as prescribed. The intervention is novel in that it has been developed from analysis of consumer and health professional views, and includes consumer video exemplars in the DVD. The primary outcome measure was a drop of 3-6 mmHg systolic blood pressure at three months after completion of the intervention. Secondary outcome measures included: assessment of medication adherence, medication self-efficacy and general wellbeing. Consumers' adherence to their prescribed medications was measured by manual pill count, self-report of medication adherence, and surrogate biochemical markers of disease control.</p> <p>Discussion</p> <p>The management of complex health problems is an increasing component of health care practice, and requires interventions that improve patient outcomes. We describe the preparatory work and baseline data of a single blind, randomized controlled trial involving consumers requiring cross-specialty care with a follow-up period extending to 12 months post-baseline.</p> <p>Trial Registration</p> <p>The trial was registered with the Australian and New Zealand Clinical Trials Register (ACTRN12607000044426).</p

Access to primary care for socio-economically disadvantaged older people in rural areas: exploring realist theory using structural equation modelling in a linked dataset

Background: Realist approaches seek to answer questions such as ‘how?’, ‘why?’, ‘for whom?’, ‘in what circumstances?’ and ‘to what extent?’ interventions ‘work’ using context-mechanism-outcome (CMO) configurations. Quantitative methods are not well-established in realist approaches, but structural equation modelling (SEM) may be useful to explore CMO configurations. Our aim was to assess the feasibility and appropriateness of SEM to explore CMO configurations and, if appropriate, make recommendations based on our access to primary care research. Our specific objectives were to map variables from two large population datasets to CMO configurations from our realist review looking at access to primary care, generate latent variables where needed, and use SEM to quantitatively test the CMO configurations. Methods: A linked dataset was created by merging individual patient data from the English Longitudinal Study of Ageing and practice data from the GP Patient Survey. Patients registered in rural practices and who were in the highest deprivation tertile were included. Three latent variables were defined using confirmatory factor analysis. SEM was used to explore the nine full CMOs. All models were estimated using robust maximum likelihoods and accounted for clustering at practice level. Ordinal variables were treated as continuous to ensure convergence. Results: We successfully explored our CMO configurations, but analysis was limited because of data availability. Two hundred seventy-six participants were included. We found a statistically significant direct (context to outcome) or indirect effect (context to outcome via mechanism) for two of nine CMOs. The strongest association was between ‘ease of getting through to the surgery’ and ‘being able to get an appointment’ with an indirect mediated effect through convenience (proportion of the indirect effect of the total was 21%). Healthcare experience was not directly associated with getting an appointment, but there was a statistically significant indirect effect through convenience (53% mediated effect). Model fit indices showed adequate fit. Conclusions: SEM allowed quantification of CMO configurations and could complement other qualitative and quantitative techniques in realist evaluations to support inferences about strengths of relationships. Future research exploring CMO configurations with SEM should aim to collect, preferably continuous, primary data

Varicella susceptibility and transmission dynamics in Slovenia

<p>Abstract</p> <p>Background</p> <p>A cross-sectional, age-stratified study was conducted to determine varicella-zoster seroprevalence and force of infection in Slovenia.</p> <p>Methods</p> <p>3689 serum samples were tested for VZV IgG antibodies with an enzyme immunoassay. Semiparametric and parametric modelling were used to estimate the force of infection.</p> <p>Results</p> <p>Overall, 85.6% of serum samples were seropositive. Age-specific prevalence rose rapidly in preschool children and over 90% of 8 years old tested positive for VZV. However, 2.8% of serum samples among women of childbearing age were seronegative. Semiparametric modelling yielded force of infection estimates of 0.182 (95% CI 0.158-0.206), 0.367 (95% CI 0.285-0.448) and 0.008 (95% CI 0.0-0.032) for age groups 0.5- < 6, 6-11 and ≥12 years, respectively, and 0.175 (95% CI 0.147-0.202), 0.391 (95% CI 0.303-0.480) and 0.025 (95% CI 0.003-0.046) for age groups 0.5- < 5, 5-9 and ≥10 years, respectively.</p> <p>Conclusions</p> <p>Regardless of the age grouping used, the highest transmission occurred in children in their first years of school.</p

Expectations and needs of patients with a chronic disease toward self-management and eHealth for self-management purposes

Background: Self-management is considered as an essential component of chronic care by primary care professionals. eHealth is expected to play an important role in supporting patients in their self-management. For effective implementation of eHealth it is important to investigate patients’ expectations and needs regarding self-management and eHealth. The objectives of this study are to investigate expectations and needs of people with a chronic condition regarding self-management and eHealth for self-management purposes, their willingness to use eHealth, and possible differences between patient groups regarding these topics. Methods: Five focus groups with people with diabetes (n = 14), COPD (n = 9), and a cardiovascular condition (n = 7) were conducted in this qualitative research. Separate focus groups were organized based on patients’ chronic condition. The following themes were discussed: 1) the impact of the chronic disease on patients’ daily life; 2) their opinions and needs regarding self-management; and 3) their expectations and needs regarding, and willingness to use, eHealth for self-management purposes. A conventional content analysis approach was used for coding. Results: Patient groups seem to differ in expectations and needs regarding self-management and eHealth for self-management purposes. People with diabetes reported most needs and benefits regarding self-management and were most willing to use eHealth, followed by the COPD group. People with a cardiovascular condition mentioned having fewer needs for self-management support, because their disease had little impact on their life. In all patient groups it was reported that the patient, not the care professional, should choose whether or not to use eHealth. Moreover, participants reported that eHealth should not replace, but complement personal care. Many participants reported expecting feelings of anxiety by doing measurement themselves and uncertainty about follow-up of deviant data of measurements. In addition, many participants worried about the implementation of eHealth being a consequence of budget cuts in care. Conclusion: This study suggests that aspects of eHealth, and the way in which it should be implemented, should be tailored to the patient. Patients’ expected benefits of using eHealth to support self-management and their perceived controllability over their disease seem to play an important role in patients’ willingness to use eHealth for self-management purposes