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Using combined data from the Relativistic Heavy Ion and Large Hadron Colliders, we constrain the shear and bulk viscosities of quark-gluon plasma (QGP) at temperatures of â¼150-350 MeV. We use Bayesian inference to translate experimental and theoretical uncertainties into probabilistic constraints for the viscosities. With Bayesian model averaging we propagate an estimate of the model uncertainty generated by the transition from hydrodynamics to hadron transport in the plasma's final evolution stage, providing the most reliable phenomenological constraints to date on the QGP viscosities.
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For a massless gas with a constant cross section in a homogeneous, isotropically expanding spacetime we reformulate the relativistic Boltzmann equation as a set of nonlinear coupled moment equations. For a particular initial condition this set can be solved exactly, yielding the first analytical solution of the Boltzmann equation for an expanding system. The nonequilibrium behavior of this relativistic gas can be mapped onto that of a homogeneous, static nonrelativistic gas of Maxwell molecules.
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PURPOSE: This editorial relates to a panel discussion during the CARS 2023 congress that addressed the question on how AI-based IT systems should be designed that record and (transparently) display a reproducible path on clinical decision making. Even though the software engineering approach suggested for this endeavor is of a generic nature, it is assumed that the listed design criteria are applicable to IT system development also for the domain of radiology and surgery. METHODS: An example of a possible design approach is outlined by illustrating on how to move from data, information, knowledge and models to wisdom-based decision making in the context of a conceptual GPT system design. In all these design steps, the essential requirements for system quality, information quality, and service quality may be realized by following the design cycle as suggested by A.R. Hevner, appropriately applied to AI-based IT systems design. RESULTS: It can be observed that certain state-of-the-art AI algorithms and systems, such as large language models or generative pre-trained transformers (GPTs), are becoming increasingly complex and, therefore, need to be rigorously examined to render them transparent and comprehensible in their usage for all stakeholders involved in health care. Further critical questions that need to be addressed are outlined and complemented with some suggestions, that a possible design framework for a stakeholder specific AI system could be a (modest) GPT based on a small language model. DISCUSSION: A fundamental question for the future remains whether society wants a quasi-wisdom-oriented healthcare system, based on data-driven intelligence with AI, or a human curated wisdom based on model-driven intelligence (with and without AI). Special CARS workshops and think tanks are planned to address this challenging question and possible new direction for assisting selected medical disciplines, e.g., radiology and surgery.
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Radiología , Humanos , Algoritmos , Toma de Decisiones Clínicas , Inteligencia ArtificialRESUMEN
Despite vast amount of money and research being channeled toward biomedical research, relatively little impact has been made on routine clinical practice. At the heart of this failure is the information and communication technology "chasm" that exists between research and healthcare. A new focus on "knowledge engineering for health" is needed to facilitate knowledge transmission across the research-healthcare gap. This discipline is required to engineer the bidirectional flow of data: processing research data and knowledge to identify clinically relevant advances and delivering these into healthcare use; conversely, making outcomes from the practice of medicine suitably available for use by the research community. This system will be able to self-optimize in that outcomes for patients treated by decisions that were based on the latest research knowledge will be fed back to the research world. A series of meetings, culminating in the "I-Health 2011" workshop, have brought together interdisciplinary experts to map the challenges and requirements for such a system. Here, we describe the main conclusions from these meetings. An "I4Health" interdisciplinary network of experts now exists to promote the key aims and objectives, namely "integrating and interpreting information for individualized healthcare," by developing the "knowledge engineering for health" domain.
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Medicina de Precisión , Conferencias de Consenso como Asunto , Bases de Datos como Asunto , Humanos , Gestión de la Información , Comunicación Interdisciplinaria , Informática Médica , Sistemas de Registros Médicos ComputarizadosRESUMEN
PURPOSE: For over three decades, the Computer-Assisted Radiology and Surgery (CARS) International Congress and Exhibition has provided a forum for the presentation of innovations in computer applications in radiology, medicine, and surgery. A unique feature of the CARS meetings is the interplay between scientists, engineers, and physicians. Since 2007, a Clinical Day program was introduced to the Congress highlighting the practical applications of new technology within the context of clinical medical and surgical practice. METHODS: The Clinical Day of the CARS Congress allows cross-fertilization of ideas between technologically oriented engineers and clinically oriented physicians; two groups who typically have little interaction. Activities of the Clinical Day include presentations by invited speakers, presentations of Innovative Clinical Investigations, a Panel Discussion and Open Forum, and, most recently, real-time clinical presentations with professionally prepared scholarly videos. Special consideration is given to young researchers and students. There has been an explosion of interest in the Clinical Day with continued and growing interest in Artificial Intelligence, Computer-Assisted Surgery, and new scientific breakthroughs as they become linked to clinical applications. RESULTS: Success of the Clinical Day is emphasized by increased participation and efforts to expand the scope and depth of Clinical Day activities. The Open Forum has proven to be highly effective in identifying important new technologic challenges in medicine and promoting discussion among those whose expertise likely can lead to solutions. CONCLUSIONS: The original goal of the Clinical Day, to provide an effective means to "bridge the gap" between the engineering community and practicing physicians and surgeons, has been realized through the presentation and discussion of real-life, clinical material that utilizes advanced technology. The program has served to inspire young researchers by allowing them to see the end results of their laboratory investigations, thereby gaining a greater appreciation of the importance of their work.
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Radiología , Cirugía Asistida por Computador , Inteligencia Artificial , Humanos , Filosofía , RadiografíaRESUMEN
Plasma concentrations of natriuretic peptides (NP) contribute to risk stratification and management of patients undergoing non-cardiac surgery. However, genetically determined variability in the levels of these biomarkers has been described previously. In the perioperative setting, genetic contribution to NP plasma level variability has not yet been determined. A cohort of 427 patients presenting for non-cardiac surgery was genotyped for single-nucleotide polymorphisms (SNPs) from the NPPA/NPPB locus. Haplotype population frequencies were estimated and adjusted haplotype trait associations for brain natriuretic peptide (BNP) and amino-terminal pro natriuretic peptide (NT-proBNP) were calculated. Five SNPs were included in the analysis. Compared to the reference haplotype TATAT (rs198358, rs5068, rs632793, rs198389, rs6676300), haplotype CACGC, with an estimated frequency of 4%, showed elevated BNP and NT-proBNP plasma concentrations by 44% and 94%, respectively. Haplotype CGCGC, with an estimated frequency of 9%, lowered NT-proBNP concentrations by 28%. ASA classification status III and IV, as well as coronary artery disease, were the strongest predictors of increased NP plasma levels. Inclusion of genetic information might improve perioperative risk stratification of patients based on adjusted thresholds of NP plasma levels.
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Enfermedad de la Arteria Coronaria , Péptido Natriurético Encefálico , Factor Natriurético Atrial/genética , Enfermedad de la Arteria Coronaria/genética , Haplotipos/genética , Humanos , Péptido Natriurético Encefálico/genética , Péptidos Natriuréticos , Nitrobenzoatos , Fragmentos de Péptidos , Procainamida/análogos & derivadosRESUMEN
For a hard parton moving through a dense QCD medium, we compute self-consistently the energy loss and the fraction deposited into the medium due to showering and rescattering of the shower, assuming weak coupling between probe and medium. The same transport coefficients thus determine both the energy loss and its deposition into the medium. This allows a parameter free calculation of the latter once the former are computed or measured. We compute them for a weakly interacting medium. Assuming a short thermalization time for the deposited energy, we determine the medium's hydrodynamical response and obtain a conical pattern that is strongly enhanced by showering.
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Very little medical virtual reality systems which are developed are applied in real surgical scenarios. One reason for this is that the system solutions resulting from research projects often address a single research question and are not embedded in an overall design. This paper presents a DICOM based approach on standardizing data structures, i.e. surface meshes, which are required for supporting surgical workflows by virtual reality applications.
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Simulación por Computador/normas , Procedimientos Quirúrgicos Operativos/educación , Interfaz Usuario-Computador , Alemania , Humanos , Procesamiento de Imagen Asistido por Computador/normas , Intensificación de Imagen RadiográficaAsunto(s)
Radiología , Cirugía Asistida por Computador , Computadores , Toma de Decisiones , Humanos , RadiografíaRESUMEN
PURPOSE: Oncological treatment is being increasingly complex, and therefore, decision making in multidisciplinary teams is becoming the key activity in the clinical pathways. The increased complexity is related to the number and variability of possible treatment decisions that may be relevant to a patient. In this paper, we describe validation of a multidisciplinary cancer treatment decision in the clinical domain of head and neck oncology. METHOD: Probabilistic graphical models and corresponding inference algorithms, in the form of Bayesian networks, can support complex decision-making processes by providing a mathematically reproducible and transparent advice. The quality of BN-based advice depends on the quality of the model. Therefore, it is vital to validate the model before it is applied in practice. RESULTS: For an example BN subnetwork of laryngeal cancer with 303 variables, we evaluated 66 patient records. To validate the model on this dataset, a validation workflow was applied in combination with quantitative and qualitative analyses. In the subsequent analyses, we observed four sources of imprecise predictions: incorrect data, incomplete patient data, outvoting relevant observations, and incorrect model. Finally, the four problems were solved by modifying the data and the model. CONCLUSION: The presented validation effort is related to the model complexity. For simpler models, the validation workflow is the same, although it may require fewer validation methods. The validation success is related to the model's well-founded knowledge base. The remaining laryngeal cancer model may disclose additional sources of imprecise predictions.
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Algoritmos , Toma de Decisiones Clínicas , Neoplasias Laríngeas/terapia , Flujo de Trabajo , Teorema de Bayes , Toma de Decisiones , Humanos , Neoplasias Laríngeas/patología , Modelos Estadísticos , Estadificación de Neoplasias , Reproducibilidad de los ResultadosRESUMEN
In complex cancer cases, Bayesian networks can support clinical experts in finding the best patient-specific therapeutic decisions. However, the development of decision networks requires teamwork of at least one domain expert and one knowledge engineer making the process expensive, time-consuming, and prone to misunderstandings. We present a novel method for guided modeling. This method enables domain experts to model collaboratively without the need of knowledge engineers, increasing both the development speed and model quality.
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Teorema de Bayes , Árboles de Decisión , Neoplasias/terapia , HumanosRESUMEN
For better integration of surgical assist systems into the operating room, a common communication and processing plattform that is based on the users needs is needed. The development of such a system, a Surgical Picture Aquisition and Communication System (S-PACS), according the systems engineering cycle is oulined in this paper. The first two steps (concept and specification) for the engineering of the S-PACS are discussed.A method for the systematic integration of the users needs', the Quality Function Deployment (QFD), is presented. The properties of QFD for the underlying problem and first results are discussed. Finally, this leads to a first definition of an S-PACS system.
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Simulación por Computador , Quirófanos , Sistemas de Información Radiológica , Recolección de Datos , Alemania , Cirugía Asistida por Computador , Integración de SistemasRESUMEN
Clinical decision support systems (CDSS) are developed to facilitate physicians' decision making, particularly for complex, oncological diseases. Access to relevant patient specific information from electronic health records (EHR) is limited to the structure and transmission formats in the respective hospital information system. We propose a system-architecture for a standardized access to patient specific information for a CDSS for laryngeal cancer. Following the idea of a CDSS using Bayesian Networks, we developed an architecture concept applying clinical standards. We recommend the application of Arden Syntax for the definition and processing of needed medical knowledge and clinical information, as well as the use of HL7 FHIR to identify the relevant data elements in an EHR to increase the interoperability the CDSS.
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Sistemas de Apoyo a Decisiones Clínicas/estadística & datos numéricos , Registros Electrónicos de Salud/normas , Teorema de Bayes , Minería de Datos , Sistemas de Apoyo a Decisiones Clínicas/organización & administración , Registros Electrónicos de Salud/organización & administración , Sistemas de Información en Hospital/organización & administración , Sistemas de Información en Hospital/normas , Humanos , Modelos Estadísticos , Integración de SistemasRESUMEN
Two metal ion binding sites are conserved in metallo-beta-lactamase from Aeromonas hydrophila. The ligands of a first zinc ion bound with picomolar dissociation constant were identified by EXAFS spectroscopy as one Cys, two His and one additional N/O donor. Sulfur-to-metal charge transfer bands are observed for all mono- and di-metal species substituted with Cu(II) or Co(II) due to ligation of the single conserved cysteine residue. Binding of a second metal ion results in non-competitive inhibition which might be explained by an alternative kinetic mechanism. A possible partition of metal ions between the two binding sites is discussed.
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Aeromonas hydrophila/enzimología , beta-Lactamasas/química , Aeromonas hydrophila/genética , Sitios de Unión , Cobalto/química , Cobre/química , Imipenem/química , Cinética , Análisis Espectral , Zinc/químicaRESUMEN
The size of the average fluctuations of net baryon number and electric charge in a finite volume of hadronic matter differs widely between the confined and deconfined phases. These differences may be exploited as indicators of the formation of a quark-gluon plasma in relativistic heavy-ion collisions, because fluctuations created in the initial state survive until freeze-out due to the rapid expansion of the hot fireball.