Establishing the longitudinal hemodynamic mapping framework for wearable-driven coronary digital twins
Not provided.
Health Care Sciences & Services↗
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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Deep learning for identifying personal and family history of suicidal thoughts and behaviors from EHRs
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Health Care Sciences & Services↗
Digital twins for noninvasively measuring predictive markers of right heart failure
Not provided.
Health Care Sciences & Services↗
DeScoD-ECG: Deep Score-Based Diffusion Model for ECG Baseline Wander and Noise Removal
Not provided.
Computer Science↗
Assessing the reliability of medical resource demand models in the context of COVID-19
Abstract Background Numerous medical resource demand models have been created as tools for governments or hospitals, aiming to predict the need for crucial resources like ventilators, hospital beds, personal protective equipment (PPE), and diagnostic kits during crises such as the COVID-19 pandemic. However, the reliability of these demand models remains uncertain. Methods Demand models typically consist of two main components: hospital use epidemiological models that predict hospitalizations or daily admissions, and a demand calculator that translates the outputs of the epidemiological model into predictions for resource usage. We conducted separate analyses to evaluate each of these components. In the first analysis, we validated various hospital use epidemiological models using a recent validation framework designed for epidemiological models. This allowed us to quantify the accuracy of the models in predicting critical aspects such as the date and magnitude of local COVID-19 peaks, among other factors. In the second analysis, we evaluated a range of demand calculators for ventilators, medical gowns, and COVID-19 test kits. To achieve this, we decoupled these demand calculators from the underlying epidemiological models and provided ground truth data for their inputs. This approach enabled a direct comparison of the demand calculators, comparing them against each other and actual usage data when available. The code is available athttps://doi.org/10.5281/zenodo.13712387. Results Performance varied greatly across the epidemiological models, with greater variability in COVID-19 hospital use predictions than for COVID-19 deaths as analyzed previously. Some models did not have any peaks. Among those that did, the models under-estimated date of peak approximately as often as they over-estimated, but were more likely to under-estimate magnitude of peak, with typical relative errors around 50%. Regarding demand calculator predictions, there was significant variability, including five-fold differences in predictions for gown models. Validation against actual or surrogate usage data illustrated the potential value of demand models while demonstrating their limitations. Conclusions The emerging field of demand modeling holds promise in averting medical resource shortages during future public health emergencies. However, achieving this potential necessitates focused efforts on standardization, transparency, and rigorous model validation before placing reliance on demand models in critical public health decision-making.
Medical Informatics↗
Exploration Medical System Demonstration
BACKGROUND: Exploration class missions will present significant new challenges and hazards to the health of the astronauts. Regardless of the intended destination, beyond low Earth orbit a greater degree of crew autonomy will be required to diagnose medical conditions, develop treatment plans, and implement procedures due to limited communications with ground-based personnel. SCOPE: The Exploration Medical System Demonstration (EMSD) project will act as a test bed on the International Space Station (ISS) to demonstrate to crew and ground personnel that an end-to-end medical system can assist clinician and non-clinician crew members in optimizing medical care delivery and data management during an exploration mission. Challenges facing exploration mission medical care include limited resources, inability to evacuate to Earth during many mission phases, and potential rendering of medical care by non-clinicians. This system demonstrates the integration of medical devices and informatics tools for managing evidence and decision making and can be designed to assist crewmembers in nominal, non-emergent situations and in emergent situations when they may be suffering from performance decrements due to environmental, physiological or other factors. PROJECT OBJECTIVES: The objectives of the EMSD project are to: a. Reduce or eliminate the time required of an on-orbit crew and ground personnel to access, transfer, and manipulate medical data. b. Demonstrate that the on-orbit crew has the ability to access medical data/information via an intuitive and crew-friendly solution to aid in the treatment of a medical condition. c. Develop a common data management framework that can be ubiquitously used to automate repetitive data collection, management, and communications tasks for all activities pertaining to crew health and life sciences. d. Ensure crew access to medical data during periods of restricted ground communication. e. Develop a common data management framework that allows for scalability, extensibility, and interoperability of data sources and data users. f. Lower total cost of ownership for development and sustainment of peripheral hardware and software that use EMSD for data management. g. Provide a better standard of healthcare for crew members through reductions in the time required by crew and ground personnel to provide medical treatment and the number of crew errors experienced during treatment.
Rubin, D. A.↗
NASA Johnson Space Center Usability Testing and Analysis Facility (UTAF) Overview
The Usability Testing and Analysis Facility (UTAF) is part of the Space Human Factors Laboratory at the NASA Johnson Space Center in Houston, Texas. The facility provides support to the Office of Biological and Physical Research, the Space Shuttle Program, the International Space Station Program, and other NASA organizations. In addition, there are ongoing collaborative research efforts with external businesses and universities. The UTAF provides human factors analysis, evaluation, and usability testing of crew interfaces for space applications. This includes computer displays and controls, workstation systems, and work environments. The UTAF has a unique mix of capabilities, with a staff experienced in both cognitive human factors and ergonomics. The current areas of focus are: human factors applications in emergency medical care and informatics; control and display technologies for electronic procedures and instructions; voice recognition in noisy environments; crew restraint design for unique microgravity workstations; and refinement of human factors processes. This presentation will provide an overview of ongoing activities, and will address how the projects will evolve to meet new space initiatives.
Whitmore, M.↗
NASA Johnson Space Center Usability Testing and Analysis Facility (WAF) Overview
The Usability Testing and Analysis Facility (UTAF) is part of the Space Human Factors Laboratory at the NASA Johnson Space Center in Houston, Texas. The facility provides support to the Office of Biological and Physical Research, the Space Shuttle Program, the International Space Station Program, and other NASA organizations. In addition, there are ongoing collaborative research efforts with external businesses and universities. The UTAF provides human factors analysis, evaluation, and usability testing of crew interfaces for space applications. This includes computer displays and controls, workstation systems, and work environments. The UTAF has a unique mix of capabilities, with a staff experienced in both cognitive human factors and ergonomics. The current areas of focus are: human factors applications in emergency medical care and informatics; control and display technologies for electronic procedures and instructions; voice recognition in noisy environments; crew restraint design for unique microgravity workstations; and refinement of human factors processes. This presentation will provide an overview of ongoing activities, and will address how the projects will evolve to meet new space initiatives.
Whitmore, M.↗
NASA Johnson Space Center Usability Testing and Analysis facility (UTAF) Overview
The Usability Testing and Analysis Facility (UTAF) is part of the Space Human Factors Laboratory at the NASA Johnson Space Center in Houston, Texas. The facility performs research for NASA's HumanSystems Integration Program, under the HumanSystems Research and Technology Division. Specifically, the UTAF provides human factors support for space vehicles, including the International Space Station, the Space Shuttle, and the forthcoming Crew Exploration Vehicle. In addition, there are ongoing collaborative research efforts with external corporations and universities. The UTAF provides human factors analysis, evaluation, and usability testing of crew interfaces for space applications. This includes computer displays and controls, workstation systems, and work environments. The UTAF has a unique mix of capabilities, with a staff experienced in both cognitive human factors and ergonomics. The current areas of focus are: human factors applications in emergency medical care and informatics; control and display technologies for electronic procedures and instructions; voice recognition in noisy environments; crew restraint design for unique microgravity workstations; and refinement of human factors processes and requirements. This presentation will provide an overview of ongoing activities, and will address how the UTAF projects will evolve to meet new space initiatives.
Whitmore, Mihriban↗
Mondo: integrating disease terminology across communities
Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.
biomedical informatics↗
The scope and direction of health informatics
Health Informatics (HI) is a dynamic discipline based on the medical sciences, information sciences, and cognitive sciences. Its domain can broadly be defined as medical information management. The purpose of this paper is to provide an overview of this domain, discuss the current "state of the art," and indicate the likely growth areas for health informatics. The sources of information used in this paper are selected publications from the literature of Health Informatics, HI 5300: Introduction to Health Informatics, which is a course from the Department of Health Informatics at the University of Texas Houston Health Sciences Center, and the author's personal experience in practicing telemedicine and implementing an electronic medical record at the NASA-Johnson Space Center. The conclusion is that the direction of Health Informatics is in the direction of data management, transfer, and representation via electronic medical records and the Internet.
Medical Informatics Applications↗
NASA Biomedical Informatics Capabilities and Needs
To improve on-orbit clinical capabilities by developing and providing operational support for intelligent, robust, reliable, and secure, enterprise-wide and comprehensive health care and biomedical informatics systems with increasing levels of autonomy, for use on Earth, low Earth orbit & exploration class missions. Biomedical Informatics is an emerging discipline that has been defined as the study, invention, and implementation of structures and algorithms to improve communication, understanding and management of medical information. The end objective of biomedical informatics is the coalescing of data, knowledge, and the tools necessary to apply that data and knowledge in the decision-making process, at the time and place that a decision needs to be made.
Johnson-Throop, Kathy A.↗
The Scope and Direction of Health Informatics
Health Informatics (HI) is a dynamic discipline based upon the medical sciences, information sciences, and cognitive sciences. Its domain is can broadly be defined as medical information management. The purpose of this paper is to provide an overview of this domain, discuss the current "state of the art" , and indicate the likely growth areas for health informatics. The sources of information utilized in this paper are selected publications from the literature of Health Informatics, HI 5300: Introduction to Health Informatics, which is a course from the Department of Health Informatics at the University of Texas Houston Health Sciences Center, and the author's personal experience in practicing telemedicine and implementing an electronic medical record at the NASA Johnson Space Center. The conclusion is that the direction of Health Informatics is in the direction of data management, transfer, and representation via electronic medical records and the Internet.
McGinnis, Patrick J.↗
Supporting Information for manuscript: “A latitudinal gradient in S/G lignin monomer ratio driven by laccase in natural poplar variants”
Lignin composition plays a crucial role in plant structural integrity and environmental adaptation. However, the genetic and molecular mechanisms underlying natural variation in lignin composition remain poorly understood. This study investigates the syringyl-to-guaiacyl (S/G) lignin monomer ratio across a natural population of Populus trichocarpa spanning a latitudinal gradient along the Northwest coast of North America. By integrating biochemical, genomic, and geographic analysis, we identify key gene variants associated with S/G ratio differences. These datasets provide valuable insights into the evolutionary and functional genomics of lignin composition and serve as a resource for developing poplar variants optimized for forestry and bioenergy applications.
Poplar, lignin composition, laccases, latitude, ad↗
Crew Health and Performance Integrated Data Architecture (CHP-IDA) Project
BACKGROUND: Future Human Exploration missions introduce a new paradigm as crews move further from the resupply and near real-time ground support typical of Low Earth Orbit missions today. Without immediate support from ground-based personnel, exploration crews will be more reliant on inflight data and technology to respond to emergencies and anomalies. A data architecture to support a new generation of technologies, employing advanced analytical and predictive modeling techniques, is needed to enable crew autonomy. OVERVIEW: The Crew Health and Performance Integrated Data Architecture (CHP-IDA) project funded by NASA’s Exploration Medical Integrated Product Team (XMIPT) is laying a foundation for future in-flight informatics by providing a back-end architecture for collecting, storing, and integrating multiple sources of data generated by and around the crew. CHP-IDA provides a platform for common data models and Application Programming Interfaces to access, integrate, process, and display CHP data (e.g., environmental, exercise, medical, sleep, performance, etc.). This will facilitate the increased situation awareness and decision support required by the crew and remote support of exploration missions. This presentation will describe the currently ongoing effort to develop and evaluate a path-to-flight concept of the CHP-IDA software and its core capabilities. Current integrations will be discussed, including analytics for Extravehicular Activity metabolic rate and data ingestion from a multi-functional integrated medical device. The presentation will also provide examples of scenarios used to demonstrate the CHP-IDA through human-in-the-loop test bed activities as well as examples of appropriate system performance metrics. DISCUSSION: Today, in-flight data is often siloed, unsynchronized, and largely inaccessible in real time. Many data sets require manual entry and/or data transfer between vehicles and the ground. These issues contribute to risks in supporting exploration medical capabilities. The CHP-IDA is a back-end data system providing core capabilities needed for timely and meaningful data insights across CHP domains to crew and remote personnel to enable increased crew autonomy. Future work includes collaboration with additional CHP domains, new technology integrations, and further demonstrations of the IDA within different vehicle and communication latency contexts. LEARNING OBJECTIVES 1. The audience will understand that the CHP-IDA is a back-end system, providing a platform to facilitate access, promote decision tools, and provide meaningful insights to crew and to remote stakeholders during exploration missions. 2. The audience will gain insight into human-centered research and activities used to discover CHP domain data needs and pain points and how this information is used to guide development of the IDA.
Exploration↗
International Space Station Medical Operations
NASA is currently the leader, in conjunction with our Russian counterpart co-leads, of the Multilateral Medical Policy Board (MMPB), the Multilateral Medical Operations Panel (MMOP), which coordinates medical system support for International Space Station (ISS) crews, and the Multilateral Space Medicine Board (MSMB), which medically certifies all crewmembers for space flight on-board the ISS. These three organizations have representatives from NASA, RSA-IMBP (Russian Space Agency- Institute for Biomedical Problems), GCTC (Gagarin Cosmonaut Training Center), ESA (European Space Agency), JAXA (Japanese Space Agency), and CSA (Canadian Space Agency). The policy and strategic coordination of ISS medical operations occurs at this level, and includes interactions with MMOP working groups in Radiation Health, Countermeasures, Extra Vehicular Activity (EVA), Informatics, Environmental Health, Behavioral Health and Performance, Nutrition, Clinical Medicine, Standards, Post-flight Activities and Rehabilitation, and Training. Each ISS Expedition has a lead Crew Surgeon from NASA and a Russian Crew Surgeon from GCTC assigned to the mission. Day-to-day issues are worked real-time by the flight surgeons and biomedical engineers (also called the Integrated Medical Group) on consoles at the MCC (Mission Control Center) in Houston and the TsUP (Center for Flight Control) in Moscow/Korolev. In the future, this may also include mission control centers in Europe and Japan, when their modules are added onto the ISS. Private medical conferences (PMCs) are conducted regularly and upon crew request with the ISS crew via private audio and video communication links from the biomedical MPSR (multipurpose support room) at MCC Houston. When issues arise in the day-to-day medical support of ISS crews, they are discussed and resolved at the SMOT (space medical operations team) meetings, which occur weekly among the International Partners. Any medical or life science issue that is not resolved at the SMOT can be taken to the Mission Management Team meeting, which occurs biweekly from MCC-Houston. This meeting includes the other International Partners and all flight support and console position representatives via teleconference. ISS Crew Surgeons have handled many medical conditions on orbit; including skin rashes, dental abscesses, lacerations, and STT segment EKG changes. Fortunately to date, there have not been any forced medical evacuations from the ISS. This speaks well for the implementation of the primary, secondary and even tertiary prevention strategies invoked by the Integrated Medical Group, as there were several medical evacuations during the previous Russian space stations.
Jones, Jeffrey A.↗
Objective Structured Clinical Evaluation (OSCE) of an Artificial Intelligence (AI) Clinical Decision Support System (CDSS) Tool
BACKGROUND Objective Structured Clinical Evaluations (OSCEs) have long been established as a robust methodology for summative assessment of clinical skills and decision-making during medical education. The recent integration of Artificial Intelligence (AI) into clinical decision-making processes has prompted the need for novel evaluation frameworks to assess the efficacy and reliability of AI clinical decision support system (CDSS) tools. This abstract outlines the process of quantitatively evaluating a novel CDSS (“Doc in a Box” Google 2024) trained on curated medical spaceflight data in the psychomotor domain as it interfaces with a human volunteer acting as the crew medical officer (CMO). PURPOSE The AI CDSS under review was developed as part of the Lunar Command and Control Interoperability (LuCCI) project, which is intended to address a gap in how Lunar Surface Systems (LSS) would interoperate across multiple programs, commercial partners, and international partners. The project objective is to define, prototype, integrate, and evaluate an interoperable lunar command, control, data, and software reference architecture to enable autonomy and informatics capability through common standards across LSS. A multi-modal AI-based CDSS compatible with Federated LSS will assist clinicians in diagnosing and managing complex medical conditions by providing evidence-based recommendations through predictive analytics. Given the critical role of decision-support as NASA continues to evolve its Earth-independent medical operations (EIMO), it is imperative to ensure that such AI tools perform reliably and align with clinical standards during progressive lunar and Martian exploration class missions. METHODS The OSCE framework, traditionally used for evaluating human clinicians, was adapted to assess the AI tool's decision-making capabilities in simulated clinical scenarios. In this adapted OSCE, the AI CDSS was tested across a series of structured clinical scenarios designed to mimic real-life spaceflight patient cases. These scenarios included a range of conditions and complexities, allowing for comprehensive assessment of the tool's performance. Key evaluation metrics included accuracy of diagnosis, timeliness of decision-making, and appropriate recommendations for therapies. The OSCE was scored by human physician evaluators who assessed the AI's recommendations in comparison with expert clinicians' medical decision making to ensure alignment with best practices and the standard of care. RESULTS Preliminary results indicate that the AI CDSS demonstrated high accuracy in diagnostic recommendations and decision support across various scenarios. However, certain limitations were noted, such as occasional discrepancies in handling complex or nuanced cases that required a more contextual understanding. Additionally, the tool scored higher on the diagnostic portion of the rubric, with lower scores in the therapeutic recommendations. These findings highlight the importance of continuous refinement and validation of AI tools through rigorous evaluation frameworks like the OSCE. The adaptation of OSCEs for AI tools presents several advantages, including a structured and reproducible approach to evaluation, the ability to test AI systems in diverse clinical scenarios, and the opportunity to benchmark AI performance against established clinical standards to permit charting of future progress as aerospace medicine evolves as a discipline. Remaining challenges include ensuring that these evaluations capture the full spectrum of clinical decision-making scenarios that will be confronted by CMOs during missions and adequately reflecting real-world variability of the austere spaceflight environment. CONCLUSION Employing OSCEs to evaluate AI clinical decision support tools offers a promising approach to validating their clinical utility and efficacy. This methodology not only provides insights into the tool's performance but also fosters ongoing improvement and alignment with standard of care practices. Future research should focus on refining these evaluation processes and addressing limitations to enhance the integration of AI tools in clinical spaceflight settings. REFERENCES Scott S, Hearns V, Barker MA. Testing Clinical Skills: A Look at the OSCE and USMLE Clinical Skills Exams. S D Med. 2019 Oct;72(10):451-453. Majumder MAA, Kumar A, Krishnamurthy K, Ojeh N, Adams OP, Sa B. An evaluative study of objective structured clinical examination (OSCE): students and examiners perspectives. Adv Med Educ Pract. 2019 Jun 5;10:387-397. Karam VY, Park YS, Tekian A, Youssef N. Evaluating the validity evidence of an OSCE: results from a new medical school. BMC Med Educ. 2018 Dec 20;18(1):313.
Ariana M Nelson↗