The future of medical diagnostics: review paper

While histopathology of excised tissue remains the gold standard for diagnosis, several new, non-invasive diagnostic techniques are being developed. They rely on physical and biochemical changes that precede and mirror malignant change within tissue. The basic principle involves simple optical techniques of tissue interrogation. Their accuracy, expressed as sensitivity and specificity, are reported in a number of studies suggests that they have a potential for cost effective, real-time, in situ diagnosis.

Using Prior Information from the Medical Literature in GWAS of Oral Cancer Identifies Novel Susceptibility Variant on Chromosome 4-the AdAPT Method

Background: Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. Methods: We developed a method that searches through PubMed abstracts for pre-assigned keywords and key concepts, and uses this information to assign prior probabilities of association for each single nucleotide polymorphism (SNP) with the phenotype of interest - the Adjusting Association Priors with Text (AdAPT) method. Association results from a GWAS can subsequently be ranked in the context of these priors using the Bayes False Discovery Probability (BFDP) framework. We initially tested AdAPT by comparing rankings of known susceptibility alleles in a previous lung cancer GWAS, and subsequently applied it in a two-phase GWAS of oral cancer. Results: Known lung cancer susceptibility SNPs were consistently ranked higher by AdAPT BFDPs than by p-values. In the oral cancer GWAS, we sought to replicate the top five SNPs as ranked by AdAPT BFDPs, of which rs991316, located in the ADH gene region of 4q23, displayed a statistically significant association with oral cancer risk in the replication phase (per-rare-allele log additive p-value [p(trend)] = 2.5 x 10(-3)). The combined OR for having one additional rare allele was 0.83 (95% CI: 0.76-0.90), and this association was independent of previously identified susceptibility SNPs that are associated with overall UADT cancer in this gene region. We also investigated if rs991316 was associated with other cancers of the upper aerodigestive tract (UADT), but no additional association signal was found. Conclusion: This study highlights the potential utility of systematically incorporating prior knowledge from the medical literature in genome-wide analyses using the AdAPT methodology. AdAPT is available online (url: http://services.gate.ac.uk/lld/gwas/service/config).

Computer game-based and traditional learning method: a comparison regarding students’ knowledge retention

Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.

PRoSPer: perceptual similarity queries in medical CBIR systems through user profiles

In this paper, we present a novel approach to perform similarity queries over medical images, maintaining the semantics of a given query posted by the user. Content-based image retrieval systems relying on relevance feedback techniques usually request the users to label relevant/irrelevant images. Thus, we present a highly effective strategy to survey user profiles, taking advantage of such labeling to implicitly gather the user perceptual similarity. The profiles maintain the settings desired for each user, allowing tuning of the similarity assessment, which encompasses the dynamic change of the distance function employed through an interactive process. Experiments on medical images show that the method is effective and can improve the decision making process during analysis.

Treatment-resistant depression increases health costs and resource utilization

Objective: Major Depressive Disorder (MDD) is a debilitating condition with a marked social impact. The impact of MDD and Treatment-Resistant Depression (TRD+) within the Brazilian health system is largely unknown. The goal of this study was to compare resource utilization and costs of care for treatment-resistant MDD relative to non-treatment-resistant depression (TRD-). Methods: We retrospectively analyzed the records of 212 patients who had been diagnosed with MDD according to the ICD-10 criteria. Specific criteria were used to identify patients with TRD+. Resource utilization was estimated, and the consumption of medication was annualized. We obtained information on medical visits, procedures, hospitalizations, emergency department visits and medication use related or not to MDD. Results: The sample consisted of 90 TRD+ and 122 TRD-patients. TRD+ patients used significantly more resources from the psychiatric service, but not from non-psychiatric clinics, compared to TRD-patients. Furthermore, TRD+ patients were significantly more likely to require hospitalizations. Overall, TRD+ patients imposed significantly higher (81.5%) annual costs compared to TRD-patients (R$ 5,520.85; US$ 3,075.34 vs. R$ 3,042.14; US$ 1,694.60). These findings demonstrate the burden of MDD, and especially of TRD+ patients, to the tertiary public health system. Our study should raise awareness of the impact of TRD+ and should be considered by policy makers when implementing public mental health initiatives.

Understanding bias in geographic range size estimates

Aim Estimates of geographic range size derived from natural history museum specimens are probably biased for many species. We aim to determine how bias in these estimates relates to range size. Location We conducted computer simulations based on herbarium specimen records from localities ranging from the southern United States to northern Argentina. Methods We used theory on the sampling distribution of the mean and variance to develop working hypotheses about how range size, defined as area of occupancy (AOO), was related to the inter-specific distribution of: (1) mean collection effort per area across the range of a species (MC); (2) variance in collection effort per area across the range of a species (VC); and (3) proportional bias in AOO estimates (PBias: the difference between the expected value of the estimate of AOO and true AOO, divided by true AOO). We tested predictions from these hypotheses using computer simulations based on a dataset of more than 29,000 herbarium specimen records documenting occurrences of 377 plant species in the tribe Bignonieae (Bignoniaceae). Results The working hypotheses predicted that the mean of the inter-specific distribution of MC, VC and PBias were independent of AOO, but that the respective variance and skewness decreased with increasing AOO. Computer simulations supported all but one prediction: the variance of the inter-specific distribution of VC did not decrease with increasing AOO. Main conclusions Our results suggest that, despite an invariant mean, the dispersion and symmetry of the inter-specific distribution of PBias decreases as AOO increases. As AOO increased, range size was less severely underestimated for a large proportion of simulated species. However, as AOO increased, range size estimates having extremely low bias were less common.

Network-based stochastic semisupervised learning

Semisupervised learning is a machine learning approach that is able to employ both labeled and unlabeled samples in the training process. In this paper, we propose a semisupervised data classification model based on a combined random-preferential walk of particles in a network (graph) constructed from the input dataset. The particles of the same class cooperate among themselves, while the particles of different classes compete with each other to propagate class labels to the whole network. A rigorous model definition is provided via a nonlinear stochastic dynamical system and a mathematical analysis of its behavior is carried out. A numerical validation presented in this paper confirms the theoretical predictions. An interesting feature brought by the competitive-cooperative mechanism is that the proposed model can achieve good classification rates while exhibiting low computational complexity order in comparison to other network-based semisupervised algorithms. Computer simulations conducted on synthetic and real-world datasets reveal the effectiveness of the model.

Cardiometabolic risk reduction through lifestyle intervention programs in the Brazilian public health system

Public health strategies to reduce cardiovascular morbidity and mortality should focus on global cardiometabolic risk reduction. The efficacy of lifestyle changes to prevent type 2 diabetes have been demonstrated, but low-cost interventions to reduce cardiometabolic risk in Latin-America have been rarely reported. Our group developed 2 programs to promote health of high-risk individuals attending a primary care center in Brazil. This study compared the effects of two 9-month lifestyle interventions, one based on medical consultations (traditional) and another with 13 multi-professional group sessions in addition to the medical consultations (intensive) on cardiometabolic parameters. Adults were eligible if they had pre-diabetes (according to the American Diabetes Association) and/or metabolic syndrome (International Diabetes Federation criteria for Latin-America). Data were expressed as means and standard deviations or percentages and compared between groups or testing visits. A p-value < 0.05 was considered significant. Results: 180 individuals agreed to participate (35.0% men, mean age 54.7 ± 12.3 years, 86.1% overweight or obese). 83 were allocated to the traditional and 97 to the intensive program. Both interventions reduced body mass index, waist circumference and tumor necrosis factor-α. Only intensive program reduced 2-hour plasma glucose and blood pressure and increased adiponectin values, but HDL-cholesterol increased only in the traditional. Also, responses to programs were better in intensive compared to traditional program in terms of blood pressure and adiponectin improvements. No new case of diabetes in intensive but 3 cases and one myocardial infarction in traditional program were detected. Both programs induced metabolic improvement in the short-term, but if better results in the intensive are due to higher awareness about risk and self-motivation deserves further investigation. In conclusion, these low-cost interventions are able to minimize cardiometabolic risk factors involved in the progression to type 2 diabetes and/or cardiovascular disease.