Search

Machine learning models are widely applied across diverse fields, including nearly all segments of human activity. In healthcare, artificial intelligence techniques have revolutionized disease diagnosis, particularly in image classification. Although these models have achieved significant results, their lack of explainability has limited widespread adoption in clinical practice. In medical environments, understanding AI model decisions is essential not only for healthcare professionals' trust but also for regulatory compliance, patient safety, and accountability in case of failures. Glaucoma, a neurodegenerative eye disease, can lead to irreversible blindness, making early detection crucial for preventing vision loss. Automated glaucoma detection has been a focus of intensive research in computer vision, with numerous studies proposing the use of convolutional neural networks (CNNs) to analyze retinal fundus images and diagnose the disease automatically. However, these models often lack the necessary explainability, which is essential for ophthalmologists to understand and justify their decisions to patients. This paper explores and applies explainable artificial intelligence (XAI) techniques to different CNN architectures for glaucoma classification, comparing which explanation technique offers the best interpretive resources for clinical diagnosis. We propose a new approach, SCIM (SHAP-CAM Interpretable Mapping), which has shown promising results. The experiments were conducted with an ophthalmology specialist who highlighted that CAM-based interpretability, applied to the VGG16 and VGG19 architectures, stands out as the most effective resource for promoting interpretability and supporting diagnosis., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Recent efforts have focused on identifying multidisciplinary teams and detecting co-Authorship Networks based on exploring topic modeling to identify researchers' expertise. Though promising, none of these efforts perform a real-life evaluation of the quality of the built topics. This paper proposes a Semantic Academic Profiler ( SAP ) framework that allows summarizing articles written by researchers to automatically build research profiles and perform online evaluations regarding these built profiles. SAP exploits and extends state-of-the-art Topic Modeling strategies based on Cluwords considering n-grams and introduces a new visual interface able to highlight the main topics related to articles, researchers and institutions. To evaluate SAP's capability of summarizing the profile of such entities as well as its usefulness for supporting online assessments of the topics' quality, we perform and contrast two types of evaluation, considering an extensive repository of Brazilian curricula vitae: (1) an offline evaluation, in which we exploit a traditional metric (NPMI) to measure the quality of several data representations strategies including (i) TFIDF, (ii) TFIDF with Bi-grams, (iii) Cluwords, and (iv) CluWords with Bi-grams; and (2) an online evaluation through an A/B test where researchers evaluate their own built profiles. We also perform an online assessment of SAP user interface through a usability test following the SUS methodology. Our experiments indicate that the CluWords with Bi-grams is the best solution and the SAP interface is very useful. We also observed essential differences in the online and offline assessments, indicating that using both together is very important for a comprehensive quality evaluation. Such type of study is scarce in the literature and our findings open space for new lines of investigation in the Topic Modeling area., (© Akadémiai Kiadó, Budapest, Hungary 2022.)

Background: Knowledge is required for people to make health decisions. It can be conjectured that knowledge of physical activity recommended levels can be a step to behavior change. This study examined the knowledge of physical activity guidelines of adolescents who were completing the secondary school., Methods: A survey was conducted with 2718 students (1613 girls), aged 16 to 18 years (Mean = 17.2 ± 0.2 years). Gender and age were self-reported and socioeconomic status was calculated based on parental occupation. Students were asked about frequency, duration, and intensity of physical activity to achieve the recommended level. Chi-square was applied to the results., Results: 16.2% reported that physical activity should be practiced daily. For the duration component of the recommendation, 43.5% identified correctly that the minimum recommended is 60 min/day. The intensity component was correctly answered by 62.7%. Considering all the components of the recommendation, only 3.6% of the students were able to identify correctly the physical activity recommendation, with no differences between genders or among socioeconomic status., Conclusions: These results highlight the need for an effective communication strategy for disseminating the message to ensure that young people are aware of, and understand the physical activity guidelines.

High performance computing is experiencing a major paradigm shift with the introduction of accelerators, such as graphics processing units (GPUs) and Intel Xeon Phi (MIC). These processors have made available a tremendous computing power at low cost, and are transforming machines into hybrid systems equipped with CPUs and accelerators. Although these systems can deliver a very high peak performance, making full use of its resources in real-world applications is a complex problem. Most current applications deployed to these machines are still being executed in a single processor, leaving other devices underutilized. In this paper we explore a scenario in which applications are composed of hierarchical data flow tasks which are allocated to nodes of a distributed memory machine in coarse-grain, but each of them may be composed of several finer-grain tasks which can be allocated to different devices within the node. We propose and implement novel performance aware scheduling techniques that can be used to allocate tasks to devices. We evaluate our techniques using a pathology image analysis application used to investigate brain cancer morphology, and our experimental evaluation shows that the proposed scheduling strategies significantly outperforms other efficient scheduling techniques, such as Heterogeneous Earliest Finish Time - HEFT, in cooperative executions using CPUs, GPUs, and MICs. We also experimentally show that our strategies are less sensitive to inaccuracy in the scheduling input data and that the performance gains are maintained as the application scales.

Vaccine development for Plasmodium vivax malaria is underway. A model to assess the protective efficacy of vaccine candidates in humans is urgently needed. Given the lack of continuous P. vivax cultures, we developed a system to infect Anopheles albimanus mosquitoes using blood from P. vivax-infected patients and determined parameters for challenge of malaria-naive volunteers by mosquito bite. Absence of co-infections in parasitized blood was confirmed by tests consistent with blood bank screening. A total of 119 experiments were conducted using batches of 900-4,500 mosquitoes fed by an artificial membrane feeding method. Optimal conditions for mosquito probing and infection were determined. Presence of oocyst and sporozoites were assessed on Days 7-8 and 14-15, respectively, and conditions to choose batches of infected mosquitoes for sporozoite challenge were established. Procedures to infect volunteers took a 2-hour period including verification of inoculum dose. Anopheles albimanus mosquitoes represent a valuable resource for P. vivax sporozoite challenge of volunteers.

Malaria infection induces antibodies capable of suppressing the infectivity of gametocytes and gametes, however, little is known about the duration of the antibody response, the parasite specificity, and the role of complement. We report the analyses of the transmission-blocking (TB) activity of sera collected from 105 Plasmodium vivax-infected and 44 non-infected individuals from a malaria endemic region of Colombia, using a membrane feeding assay in Anopheles albimanus mosquitoes. In infected donors we found that TB activity was antibody dose dependent (35%), lasted for 2-4 months after infection, and in 70% of the cases different P. vivax wild isolates displayed differential susceptibility to blocking antibodies. Additionally, in a number of assays TB was complement-dependent. Twenty-seven percent of non-infected individuals presented TB activity that correlated with antibody titers. Studies here provide preliminary data on factors of great importance for further work on the development of TB vaccines.

A safe and reproducible Plasmodium vivax infectious challenge method is required to evaluate the efficacy of malaria vaccine candidates. Seventeen healthy Duffy (+) and five Duffy (-) subjects were randomly allocated into three (A-C) groups and were exposed to the bites of 2-4 Anopheles albimanus mosquitoes infected with Plasmodium vivax derived from three donors. Duffy (-) subjects were included as controls for each group. Clinical manifestations of malaria and parasitemia were monitored beginning 7 days post-challenge. All Duffy (+) volunteers developed patent malaria infection within 16 days after challenge. Prepatent period determined by thick smear, was longer for Group A (median 14.5 d) than for Groups B and C (median 10 d/each). Infected volunteers recovered rapidly after treatment with no serious adverse events. The bite of as low as two P. vivax-infected mosquitoes provides safe and reliable infections in malaria-naive volunteers, suitable for assessing antimalarial and vaccine efficacy trials.

Artificial membrane feeding (AMF) assays are used to determine malaria transmission-blocking activity in Anopheles. The purpose of this study was to determine the effect of the most widely used anticoagulants, EDTA and heparin, on development of the Plasmodium vivax sporogonic cycle. Blood samples collected from 60 patients carrying P. vivax infections were used to feed An. albimanus using AMF. Seven days after feeding, mosquitoes were dissected to assess mosquito infection. Mosquitoes fed with blood containing EDTA showed a lower mean oocyst number as compared with those fed blood with heparin. However, this effect was minimized upon reduction of EDTA concentrations in the serum. This result may be explained by the fact that microgametocytes require Ca(2+), Mn(2+), and Mg(+2) to activate enzymes important for exflagellation process and for motility of ookinetes. We therefore recommend that heparin be used as the anticoagulant of choice for blood used in AMF assays.

Plasmodium vivax transmission-blocking activity was assessed in sera from acutely infected patients from a malaria-endemic area in Colombia. We measured reduction in the number of oocysts that developed in the midguts of Anopheles albimanus mosquitoes artificially fed with blood from these patients. Of 88 mosquito batches that developed infections when parasites were mixed with normal AB human serum, one-third (36.4%) showed full transmission-blocking activity (>or= 90% inhibition) when mixed with autologous sera, 29.6% showed partial activity (50-89%), 17.0% did not block transmission (0-50%), and 17% did not enhance transmission. Transmission-blocking activity correlated with antibody titer by an immunofluorescent antibody test and decreased with the serial dilution of the sera. This activity disappeared at a 1:4 dilution in most sera tested. Afro-Colombian individuals showed lower activity than other ethnic groups and febrile patients produced stronger inhibition than those without fever.