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Background: The burden of musculoskeletal conditions continues to grow in low‐ and middle‐income countries. Among thousands of surgical outreach trips each year, few organizations electronically track patient data to inform real‐time care decisions and assess trip impact. We report the implementation of an electronic health record (EHR) system utilized at point of care during an orthopedic surgical outreach trip. Methods: In March 2023, we implemented an EHR on an orthopedic outreach trip to guide real‐time care decisions. We utilized an effectiveness‐implementation hybrid type 3 design to evaluate implementation success. Success was measured using outcomes adopted by the World Health Organization, including acceptability, appropriateness, feasibility, adoption, fidelity, and sustainability. Clinical outcome measures included adherence to essential quality measures and follow‐up numerical rating system (NRS) pain scores. Results: During the 5‐day outreach trip, 76 patients were evaluated, 25 of which underwent surgery beforehand. The EHR implementation was successful as defined by: mean questionnaire ratings of acceptability (4.26), appropriateness (4.12), feasibility (4.19), and adoption (4.33) at least 4.00, WHO behaviorally anchored rating scale ratings of fidelity (6.8) at least 5.00, and sustainability (80%) at least 60% follow‐up at 6 months. All clinical quality measures were reported in greater than 80% of cases with all measures reported in 92% of cases. NRS pain scores improved by an average of 2.4 points. Conclusions: We demonstrate successful implementation of an EHR for real‐time clinical use on a surgical outreach trip. Benefits of EHR utilization on surgical outreach trips may include improved documentation, minimization of medical errors, and ultimately improved quality of care. [ABSTRACT FROM AUTHOR]

Face Morphing Attacks pose a threat to the security of identity documents, especially with respect to a subsequent access control process, because they allow both involved individuals to use the same document. Several algorithms are currently being developed to detect Morphing Attacks, often requiring large data sets of morphed face images for training. In the present study, face embeddings are used for two different purposes: first, to pre-select images for the subsequent large-scale generation of Morphing Attacks, and second, to detect potential Morphing Attacks. Previous studies have demonstrated the power of embeddings in both use cases. However, we aim to build on these studies by adding the more powerful MagFace model to both use cases, and by performing comprehensive analyses of the role of embeddings in pre-selection and attack detection in terms of the vulnerability of face recognition systems and attack detection algorithms. In particular, we use recent developments to assess the attack potential, but also investigate the influence of morphing algorithms. For the first objective, an algorithm is developed that pairs individuals based on the similarity of their face embeddings. Different state-of-the-art face recognition systems are used to extract embeddings in order to pre-select the face images and different morphing algorithms are used to fuse the face images. The attack potential of the differently generated morphed face images will be quantified to compare the usability of the embeddings for automatically generating a large number of successful Morphing Attacks. For the second objective, we compare the performance of the embeddings of two state-of-the-art face recognition systems with respect to their ability to detect morphed face images. Our results demonstrate that ArcFace and MagFace provide valuable face embeddings for image pre-selection. Various open-source and commercial-off-the-shelf face recognition systems are vulnerable to the generated Morphing Attacks, and their vulnerability increases when image pre-selection is based on embeddings compared to random pairing. In particular, landmark-based closed-source morphing algorithms generate attacks that pose a high risk to any tested face recognition system. Remarkably, more accurate face recognition systems show a higher vulnerability to Morphing Attacks. Among the systems tested, commercial-off-the-shelf systems were the most vulnerable to Morphing Attacks. In addition, MagFace embeddings stand out as a robust alternative for detecting morphed face images compared to the previously used ArcFace embeddings. The results endorse the benefits of face embeddings for more effective image pre-selection for face morphing and for more accurate detection of morphed face images, as demonstrated by extensive analysis of various designed attacks. The MagFace model is a powerful alternative to the often-used ArcFace model in detecting attacks and can increase performance depending on the use case. It also highlights the usability of embeddings to generate large-scale morphed face databases for various purposes, such as training Morphing Attack Detection algorithms as a countermeasure against attacks. [ABSTRACT FROM AUTHOR]

The incidence of candidemia in healthcare centers is associated with high morbidity and mortality. Frequency varies significantly among regions, with some species being more prevalent than others in Latin America. In this study, 191 clinical Candida isolates were collected from a major hospital in Ecuador from January 2019 to February 2020 aiming to assess their prevalence and distribution. After data processing, 168 isolates characterized by the VITEK 2 system were subsequently identified by ITS sequencing. Results showed diverse Candida species distributions, with C. albicans and C. tropicalis being the most prevalent across different clinical sources. In hospitalized individuals, C. tropicalis (38%) and C. albicans (37%) were the most prevalent, followed by, C. parapsilosis (16%), C. glabrata (5%), and other non-Candida albicans (NCA) species (6%). Conversely, C. parapsilosis (48%), C. albicans (20%), and C. glabrata (14%), associated with candidemia, were the most common in blood and CSF. Additionally, uncommon NCA species such as C. haemulonii, C. kefyr, and C. pelliculosa were identified in Ecuador for the first time. Discrepancies in species identification were observed between the VITEK 2 system and ITS sequencing, coinciding at 85%. This highlights the need for ongoing surveillance and identification efforts in Ecuador's clinical and epidemiological settings. [ABSTRACT FROM AUTHOR]

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Gender classification on normalized iris images has been previously attempted with varying degrees of success. In these previous studies, it has been shown that occlusion masks may introduce gender information; occlusion masks are used in iris recognition to remove non-iris elements. When, the goal is to classify the gender using exclusively the iris texture, the presence of gender information in the masks may result in apparently higher accuracy, thereby not reflecting the actual gender information present in the iris. However, no measures have been taken to eliminate this information while preserving as much iris information as possible. We propose a novel method to assess the gender information present in the iris more accurately by eliminating gender information in the masks. This consists of pairing iris with similar masks and different gender, generating a paired mask using the OR operator, and applying this mask to the iris. Additionally, we manually fix iris segmentation errors to study their impact on the gender classification. Our results show that occlusion masks can account for 6.92% of the gender classification accuracy on average. Therefore, works aiming to perform gender classification using the iris texture from normalized iris images should eliminate this correlation. [ABSTRACT FROM AUTHOR]