Efficient image retrieval by fuzzy rules from boosting and metaheuristic

Fast content-based image retrieval is still a challenge for computer systems. We present a novel method aimed at classifying images by fuzzy rules and local image features. The fuzzy rule base is generated in the first stage by a boosting procedure. Boosting meta-learning is used to find the most representative local features. We briefly explore the utilization of metaheuristic algorithms for the various tasks of fuzzy systems optimization. We also provide a comprehensive description of the current best-performing DISH algorithm, which represents a powerful version of the differential evolution algorithm with effective embedded mechanisms for stronger exploration and preservation of the population diversity, designed for higher dimensional and complex optimization tasks. The algorithm is used to fine-tune the fuzzy rule base. The fuzzy rules can also be used to create a database index to retrieve images similar to the query image fast. The proposed approach is tested on a state-of-the-art image dataset and compared with the bag-of-features image representation model combined with the Support Vector Machine classification. The novel method gives a better classification accuracy, and the time of the training and testing process is significantly shorter. © 2020 Marcin Korytkowski et al., published by Sciendo.program of the Polish Minister of Science and Higher Education under the name "Regional Initiative of Excellence" in the years 2019-2022 [020/RID/2018/19

Evolutionary algorithm for content-based image search

Content-based image retrieval systems attempt to provide a means of searching for images in large repositories without using any information other than that contained in the image itself, usually in the form of low-level descriptors. Since these descriptors do not accurately represent the semantics of the image, evaluating the perceptual similarity between two images based only on them is not a trivial task. This paper describes an effective method for image recovery based on evolutionary computing techniques. The results are compared with those obtained by the classical approach of the movement of the query point and the rescheduling of the axes and by a technique based on self-organizing maps, showing a remarkably higher performance in the repositories

Carotid artery intima-media thickness in polycystic ovary syndrome: a systematic review and meta-analysis

Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disorder associated with cardiovascular disease (CVD) risk factors and metabolic disturbances. This systematic review and meta-analysis was conducted to determine whether carotid intima-media thickness (CIMT), a marker of subclinical atherosclerosis, is higher in women with PCOS compared with women without PCOS

Comparing the efficacy, safety, and utility of intensive insulin algorithms for a primary care practice

Diabetes management is firmly based within the primary care community. Landmark randomized, controlled trials have demonstrated that even modest reductions in glycated hemoglobin (HbA1c) can yield improvements in economic and medical end-points. Diabetes is a chronic, progressive disease associated with loss of pancreatic β-cell function. Therefore, most patients will eventually require insulin therapies in order to achieve their individualized targeted HbA1c as their β-cell function and mass wanes. Although clinicians understand the importance of early insulin initiation, there is little agreement as to when to introduce insulin as a therapeutic option. Once initiated, questions remain as to whether to allow the patients to self-titrate their dose or whether the dosing should be tightly regulated by the clinician. Physicians have many evidence-based basal insulin protocols from which to choose, all of which have been shown to drive HbA1c levels to the American Diabetes Association target of ≤7%. This article will discuss ways by which insulin therapies can be effectively introduced to patients within busy primary care practices. Published evidence-based basal insulin protocols will be evaluated for safety and efficacy

Development of a web-based insulin decision aid for the elderly: usability barriers and guidelines

In recent years, researchers have attempted to shift patient decision aids (PDAs) from paper-based to web-based to increase its accessibility. Insulin decision aids help diabetes patients, most of whom are elderly to make an informed decision to start insulin. However, the lack of usability guidelines applicable for such target group causes developers to struggle to answer the challenging question ‘How can such web service be made usable, and, ultimately, acceptable and accessible for elderly patients?’. Hence, the purpose of this study is to identify the common usability requirements that may facilitate good practices to empower elderly diabetes patients in utilizing a web-based insulin decision aid for their benefit. We set out an approach to use prototyping and retrospective think-aloud techniques to explore web usability barriers that elderly patients may encounter when using an insulin decision aid web site and use the feedback for improving the prototype. Usability requirements were captured iteratively through scoping, brainstorming, prototype, testing and evaluating. The study suggests that the insights from experts and users are equally important to assure the validity of the identified usability guidelines; they reflect the accessibility needs of the aging community while complementing the key requirements of an insulin decision aid. The study contributes to recommend web usability guidelines backed by a series of expert and user evaluations which could be a proactive resource to improve usability, acceptability and accessibility of online insulin decision aids for elderly with diabetes