UNASSIGNED: Candida albicans (C. albicans), an opportunistic pathogen, is implicated in the carcinogenesis of various cancers, thereby significantly impacting human health. This study conducts an in-depth analysis of the prevailing research dynamics concerning the relationship between C. albicans and cancer over the past decade, offering a comprehensive overview of the knowledge structure and emerging focal points in this field through bibliometric scrutiny.
UNASSIGNED: A methodical quantitative and visual scrutiny of pertinent literature from the Web of Science Core Collection (WoSCC) spanning the previous decade was carried out employing VOS Viewer and CiteSpace software.
UNASSIGNED: From January 1, 2014, to January 1, 2024, a comprehensive corpus of 1,259 articles was delineated. Prominent research institutions included the Egyptian Knowledge Bank, Cairo University, and King Saud University. The top three prolific countries were the United States, China, and India. Among the authors, Mohamed, Gehad G., Mahmoud, Walaa H., and Netea, Mihai G., emerged as the most prolific, with Pfaller, Ma being distinguished as the most frequently cited author. The journal Molecules published the highest number of articles, while PLoS One had the highest citation count. Nature had the highest impact factor. The research focal points in this field encompassed the interactions between C. albicans and cancer, the correlation with oral cancer, the underlying mechanisms of C. albicans carcinogenic potential, as well as antifungal and anticancer therapies.
UNASSIGNED: This investigation constitutes a pioneering bibliometric analysis elucidating the trends and advancements in research regarding the correlation between C. albicans and cancer. Said analyses uncover the prevailing research focal points and trends, offering insightful guidance for subsequent inquiry in this domain.
UNASSIGNED: https://www.webofscience.com/wos/woscc/summary/df33afba-f843-41e8-b932-cb3678eb8243-e92e7316/relevance/1.

UNASSIGNED: This manuscript undertakes a systematic examination of the research landscape concerning global Cryptococcus species and their dynamism with the host immune system spanning the past decade. It furnishes a detailed survey of leading knowledge institutions and critical focal points in this area, utilizing bibliometric analysis.
UNASSIGNED: VOSviewer and CiteSpace software platforms were employed to systematically analyze and graphically depict the relevant literature indexed in the WoSCC database over the preceding ten years.
UNASSIGNED: In the interval between October 1, 2013, and October 1, 2023, a corpus of 795 publications was amassed. The primary research institutions involved in this study include Duke University, the University of Minnesota, and the University of Sydney. The leading trio of nations, in terms of publication volume, comprises the United States, China, and Brazil. Among the most prolific authors are Casadevall, Arturo; Wormley, Floyd L., Jr.; and Olszewski, Michal A., with the most highly cited author being Perfect, Jr. The most esteemed journal is Mbio, while Infection and Immunity commands the highest citation frequency, and the Journal of Clinical Microbiology boasts the most significant impact factor. Present research foci encompass the intricate interactions between Cryptococcus pathogenesis and host immunity, alongside immune mechanisms, complications, and immunotherapies.
UNASSIGNED: This represents the first exhaustive scholarly review and bibliometric scrutiny of the evolving landscapes in Cryptococcus research and its interactions with the host immune system. The analyses delineated herein provide insights into prevailing research foci and trajectories, thus furnishing critical directions for subsequent inquiries in this domain.

Eye-hand coordination (EHC) is crucial to our daily activities, and its underlying mechanisms are being intensely studied. The analysis of simultaneous eye and hand movements can provide valuable insights into EHC, particularly for individuals struggling with dexterous control, such as might be caused by stroke or traumatic brain injuries. Despite advancements in motion-capture and eye tracking technologies, there is currently no automated method for visualizing concurrent eye- and hand-movement data. To address this need, we have developed a MATLAB-based dashboard designed for near instantaneous analysis and visualization of eye and hand-tracking data. This paper introduces the design of the dashboard and presents experimental results obtained from its application, leveraging simulated data inspired by our recent work in stroke. This testing suggests that our solution has the potential to significantly aid in understanding and investigating EHC by providing side-by-side and time-locked comparison of eye/hand movements along with their timing and spatio-temporal errors, offering novel opportunities for research and clinical applications.•Continuous eye movement data is collected throughout the experiment•Continuous hand movement data is collected throughout the experiment•Combine datasets and display time-locked eye-hand data in a single dashboard.

It is important to understand how to design AR content for surgical contexts to mitigate the risk of distracting the surgeons. In this work, we test information overlays for AR guidance during keyhole surgery. We performed a preliminary evaluation of a prototype, focusing on the effects of colour, opacity, and information representation. Our work contributes insights into the design of AR guidance in surgery settings and a foundation for future research on visualisation design for surgical AR.

OBJECTIVE: Medical researchers deal with a large amount of patient data to improve future treatment decisions and come up with new hypotheses. To facilitate working with a large database containing many patients and parameters, we propose a virtual data shelf, displaying the 3D anatomical surface models in an immersive VR environment.
METHODS: Thereby, different functionalities such as sorting, filtering and finding similar cases are included. To provide an appropriate layout and arrangement of 3D models that optimally supports working with the database, three layouts (flat, curved and spherical) and two distances are evaluated. A broad audience study with 61 participants was conducted to compare the different layouts based on their ease of interaction, to get an overview and to explore single cases. Medical experts additionally evaluated medical use cases.
RESULTS: The study revealed that the flat layout with small distance is significantly faster in providing an overview. Applying the virtual data shelf to the medical use case intracranial aneurysms, qualitative expert feedback with two neuroradiologists and two neurosurgeons was gathered. Most of the surgeons preferred the curved and spherical layouts.
CONCLUSIONS: Our tool combines benefits of two data management metaphors, resulting in an efficient way to work with a large database of 3D models in VR. The evaluation gives insight into benefits of layouts as well as possible use cases in medical research.

Nowadays, healthcare management systems are adopting various techniques that facilitate the achievement of the goals of evidence-based medical practice. This review explores different visualization techniques and their importance in healthcare contexts. We performed a thorough search on databases such as the SLD portal, PubMed, and Google Scholar to obtain relevant studies. We selected recent articles published between 2018 and 2021 on visualization techniques in healthcare. The field of healthcare generates massive volumes of data that require visualization techniques to make them easily comprehensible and to guide their efficient presentation. Visualization in healthcare involves the effective presentation of information through graphics, images, and videos. Big data systems handle a massive amount of information and require visualization techniques to present it in a comprehensible manner. The significance of visualization techniques in healthcare is not confined to healthcare practitioners and healthcare management but encompasses all the stakeholders; patients can benefit from the visualization of his/her data for a better understanding of their condition. In short, visualization techniques have demonstrated their benefits in the healthcare sector and can be extended to the payer and the patient. They have also had a positive impact on the quality of the healthcare provided as well as patient safety.

A third of all rapes in Stockholm, the capital of Sweden, take place in public outdoor places. Yet, little is known about the events that precede this type of sexual offence and less about the situational context of rape. This study aims to improve the understanding of the nature of situational conditions that immediately precede events of rape. Using medical records of 147 rape victims during 2012 and 2013, we constructed time- and place-specific records of the places women traveled through or spent time at, the activities they engaged in, and the people they interacted with sequentially over the course of the day when they were raped. The analysis uses visualization tools (VISUAL-TimePAcTS), Geographical Information Systems, and conditional logistic regression to identify place-, context-, and social interaction-related factors associated with the onset of rape. Results for this sample of cases reported to hospitals show that being outdoors was not necessarily riskier for women when compared with indoor public settings; some outdoor environments were actually protective, such as streets. Being in a risky social context and engaging in a risky activity before the event was associated with an increased risk of rape, and the risk escalated over the day. Among those women who never drank alcohol, the results were similar to what was observed in the overall sample, which suggests that risky social interaction and risky activity made independent contributions to the risk of rape. The article finishes with suggestions for rape prevention.

OBJECTIVE: Mining the electronic medical record (EMR) has the potential to deliver new medical knowledge about causal effects, which are hidden in statistical associations between different patient attributes. It is our goal to detect such causal mechanisms within current research projects which include e.g. the detection of determinants of imminent ICU readmission. An iterative statistical approach to examine each set of considered attribute pairs delivers potential answers but is difficult to interpret. Therefore, we aimed to improve the interpretation of the resulting matrices by the use of heat maps. We propose strategies to adapt heat maps for the search for associations and causal effects within routine EMR data.
METHODS: Heat maps visualize tabulated metric datasets as grid-like choropleth maps, and thus present measures of association between numerous attribute pairs clearly arranged. Basic assumptions about plausible exposures and outcomes are used to allocate distinct attribute sets to both matrix dimensions. The image then avoids certain redundant graphical elements and provides a clearer picture of the supposed associations. Specific color schemes have been chosen to incorporate preexisting information about similarities between attributes. The use of measures of association as a clustering input has been taken as a trigger to apply transformations which ensure that distance metrics always assume finite values and treat positive and negative associations in the same way. To evaluate the general capability of the approach, we conducted analyses of simulated datasets and assessed diagnostic and procedural codes in a large routine care dataset.
RESULTS: Simulation results demonstrate that the proposed clustering procedure rearranges attributes similar to simulated statistical associations. Thus, heat maps are an excellent tool to indicate whether associations concern the same attributes or different ones, and whether affected attribute sets conform to any preexisting relationship between attributes. The dendrograms help in deciding if contiguous sequences of attributes effectively correspond to homogeneous attribute associations. The exemplary analysis of a routine care dataset revealed patterns of associations that follow plausible medical constellations for several diseases and the associated medical procedures and activities. Cases with breast cancer (ICD C50), for example, appeared to be associated with radiation therapy (8-52). In cross check, approximately 60 percent of the attribute pairs in this dataset showed a strong negative association, which can be explained by diseases treated in a medical specialty which routinely does not perform the respective procedures in these cases. The corresponding diagram clearly reflects these relationships in the shape of coherent subareas.
CONCLUSIONS: We could demonstrate that heat maps of measures of association are effective for the visualization of patterns in routine care EMRs. The adjustable method for the assignment of attributes to image dimensions permits a balance between the display of ample information and a favorable level of graphical complexity. The scope of the search can be adapted by the use of pre-existing assumptions about plausible effects to select exposure and outcome attributes. Thus, the proposed method promises to simplify the detection of undiscovered causal effects within routine EMR data.