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NASA NTRSDate not supplied

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↗

NASA NTRSDate not supplied

Objective Structured Clinical Evaluation (OSCE) of an Artificial Intelligence (AI) Clinical Decision Support System (CDSS) Tool

Explore the source record for details and available documents.

Ariana Nelson↗

NASA NTRS2006

Zero to Integration in Eight Months, the Dawn Ground Data System Engineering Challenge

The Dawn Project has presented the Ground Data System (GDS) with technical challenges driven by cost and schedule constraints commonly associated with National Aeronautics and Space Administration (NASA) Discovery Projects. The Dawn mission consists of a new and exciting Deep Space partnership among: the Jet Propulsion Laboratory (JPL), manages the project and is responsible for flight operation; Orbital Sciences Corporation (OSC), is the spacecraft builder and is responsible for flight system test and integration; and the University of California, at Los Angeles (UCLA), is responsible for science planning and operations. As a cost-capped mission, one of Dawn's implementation strategies is to leverage from both flight and ground heritage. OSC's ground data system is used for flight system test and integration as part of the flight heritage strategy. Mission operations, however, are to be conducted with JPL's ground system. The system engineering challenge of dealing with two heterogeneous ground systems emerged immediately. During the first technical interchange meeting between the JPL's GDS Team and OSC's Flight Software Team, August 2003, the need to integrate the ground system with the flight software was brought to the table. This need was driven by the project's commitment to enable instrument engineering model integration in a spacecraft simulator environment, for both demonstration and risk mitigation purposes, by April 2004. This paper will describe the system engineering approach that was undertaken by JPL's GDS Team in order to meet the technical challenge within a non-negotiable eight-month schedule. Key to the success was adherence to fundamental systems engineering practices: decomposition of the project request into manageable requirements; integration of multiple ground disciplines and experts into a focused team effort; definition of a structured yet flexible development process; definition of an in-process risk reduction plan; and aggregation of the intermediate products to an integrated final product. In addition, this paper will highlight the role of lessons learned from the integration experience. The lessons learned from an early GDS deployment have served as the foundation for the design and implementation of the Dawn Ground Data System.

Ground Data System (GDS)↗

NASA NTRS1993

The Telecommunications and Data Acquisition Report

This quarterly publication provides archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). The TDA Office also performs work funded by another NASA program office through and with the cooperation of OSC. This is the Orbital Debris Radar Program with tile Office of Space Systems Development. The TDA Office is directly involved in several tasks that directly support the Office of Space Science (OSS), with OSC funding DSN operational support. In radio science, The TDA Progress Report describes the spacecraft radio science program conducted using tile DSN. For the High-Resolution Microwave Survey (HRMS), the report covers implementation and operations for searching the microwave spectrum. In solar system radar, it reports on the uses of the Goldstone Solar System Radar for scientific exploration of the planets, their rings and satellites, asteroids, and comets. In radio astronomy, the areas off support include spectroscopy, very long baseline interferometry, and astrometry.

Edward C Posner↗

NASA NTRS2006

Zero to Integration in Eight Months, the Dawn Ground Data System Engineering Challange

The Dawn Project has presented the Ground Data System (GDS) with technical challenges driven by cost and schedule constraints commonly associated with National Aeronautics and Space Administration (NASA) Discovery Projects. The Dawn mission consists of a new and exciting Deep Space partnership among: the Jet Propulsion Laboratory (JPL), responsible for project management and flight operations; Orbital Sciences Corporation (OSC), spacecraft builder and responsible for flight system test and integration; and the University of California, at Los Angeles (UCLA), responsible for science planning and operations. As a cost-capped mission, one of Dawn s implementation strategies is to leverage from both flight and ground heritage. OSC's ground data system is used for flight system test and integration as part of the flight heritage strategy. Mission operations, however, are to be conducted with JPL s ground system. The system engineering challenge of dealing with two heterogeneous ground systems emerged immediately. During the first technical interchange meeting between the JPL s GDS Team and OSC's Flight Software Team, August 2003, the need to integrate the ground system with the flight software was brought to the table. This need was driven by the project s commitment to enable instrument engineering model integration in a spacecraft simulator environment, for both demonstration and risk mitigation purposes, by April 2004. This paper will describe the system engineering approach that was undertaken by JPL's GDS Team in order to meet the technical challenge within a non-negotiable eight-month schedule. Key to the success was adherence to an overall systems engineering process and fundamental systems engineering practices: decomposition of the project request into manageable requirements; definition of a structured yet flexible development process; integration of multiple ground disciplines and experts into a focused team effort; in-process risk management; and aggregation of the intermediate products to an integrated final product. In addition, this paper will highlight the role of lessons learned from the integration experience. The lessons learned from an early GDS deployment have served as the foundation for the design and implementation of the Dawn Ground Data System.

systems engineering↗

NASA NTRS2008

The NASA Orbiting Carbon Observatory (OCO) Mission: Objectives, Approach, and Status

The Orbiting Carbon Observatory (OCO) is a NASA Earth System Science Pathfinder (ESSP) mission that is currently under development at the Jet Propulsion Laboratory (JPL). OCO will make global, space-based measurements of atmospheric carbon dioxide (CO2) with the precision, resolution, and coverage needed to characterize regional-scale sources and sinks of this important greenhouse gas. The observatory consists of a dedicated spacecraft bus that carries a single instrument. The bus employs single-string version of Orbital Sciences Corporation (OSC) LEOStar-2 architecture. This 3-axis stabilized bus includes a propulsion system for orbit insertion and maintenance, provides power, points the instrument, receives and processes commands from the ground, and records, stores, and downlinks science and engineering data. The OCO instrument incorporates 3 oboresighted, high resolution grating spectrometers that will make coincident measurements of reflected sunlight in near-infrared CO2 and molecular oxygen (O2) bands. The instrument was designed and manufactured by Hamilton Sundstrand (Pomona, CA), and then integrated, flight qualified, and calibrated by JPL. It is scheduled for delivery to OSC (Dulles, VA) for integration with the spacecraft bus in the spring of 2008. OCO will be launched from the Vandenberg Air Force Base on a dedicated OSC Taurus XL launch vehicle in December 2008. It will fly in formation with the Earth Observing System Afternoon Constellation, a group of satellites that files in a 98.8 minute, 705 km altitude, sun-synchronous orbit. This orbit provides coverage of the sunlit hemisphere with a 16-day ground track repeat cycle. OCO will fly approx.4 minutes ahead of the EOS Aqua platform, with an ascending nodal crossing time of approx.1:26 PM. The OCO science data will be transmitted to the NASA Ground Network Stations in Alaska and Virginia, and then transferred to the OCO Ground Data System at JPL. There, the CO2 and O2 spectra will be analyzed by the OCO Science Team to provide spatially resolved estimates of the column-averaged CO2 dry air mole fraction, XCO2. These measurements are expected to improve our understanding of the nature and processes that regulate atmospheric CO2 enabling more reliable forecasts of CO2 buildup and its impact on climate change.

global measurements↗

NASA NTRS2010

Reactive Sequencing for Autonomous Navigation Evolving from Phoenix Entry, Descent, and Landing

Virtual Machine Language (VML) is an award-winning advanced procedural sequencing language in use on NASA deep-space missions since 1997, and was used for the successful entry, descent, and landing (EDL) of the Phoenix spacecraft onto the surface of Mars. Phoenix EDL utilized a state-oriented operations architecture which executed within the constraints of the existing VML 2.0 flight capability, compatible with the linear "land or die" nature of the mission. The intricacies of Phoenix EDL included the planned discarding of portions of the vehicle, the complex communications management for relay through on-orbit assets, the presence of temporally indeterminate physical events, and the need to rapidly catch up four days of sequencing should a reboot of the spacecraft flight computer occur shortly before atmospheric entry. These formidable operational challenges led to new techniques for packaging and coordinating reusable sequences called blocks using one-way synchronization via VML sequencing global variable events. The coordinated blocks acted as an ensemble to land the spacecraft, while individually managing various elements in as simple a fashion as possible. This paper outlines prototype VML 2.1 flight capabilities that have evolved from the one-way synchronization techniques in order to implement even more ambitious autonomous mission capabilities. Target missions for these new capabilities include autonomous touch-and-go sampling of cometary and asteroidal bodies, lunar landing of robotic missions, and ultimately landing of crewed lunar vehicles. Close proximity guidance, navigation, and control operations, on-orbit rendezvous, and descent and landing events featured in these missions require elaborate abort capability, manifesting highly non-linear scenarios that are so complex as to overtax traditional sequencing, or even the sort of one-way coordinated sequencing used during EDL. Foreseeing advanced command and control needs for small body and lunar landing guidance, navigation and control scenarios, work began three years ago on substantial upgrades to VML that are now being exercised in scenarios for lunar landing and comet/asteroid rendezvous. The advanced state-based approach includes coordinated state transition machines with distributed decision-making logic. These state machines are not merely sequences - they are reactive logic constructs capable of autonomous decision making within a well-defined domain. Combined with the JPL's AutoNav software used on Deep Space 1 and Deep Impact, the system allows spacecraft to autonomously navigate to an unmapped surface, soft-contact, and either land or ascend. The state machine architecture enabled by VML 2.1 has successfully performed sampling missions and lunar descent missions in a simulated environment, and is progressing toward flight capability. The authors are also investigating using the VML 2.1 flight director architecture to perform autonomous activities like rendezvous with a passive hypothetical Mars sample return capsule. The approach being pursued is similar to the touch-and-go sampling state machines, with the added complications associated with the search for, physical capture of, and securing of a separate spacecraft. Complications include optically finding and tracking the Orbiting Sample Capsule (OSC), keeping the OSC illuminated, making orbital adjustments, and physically capturing the OSC. Other applications could include autonomous science collection and fault compensation.

asteroid↗

NASA NTRS1980

Offshore Space Center (offshore launch site)

Any activity requiring the development of the HLLV can benefit by operations from an offshore space center (OSC) since operating near the equator provides a twenty percent increase in payload in an ecliptic plan orbit. Some OSC concepts considered include a moored floating (semisubmersible) design, a stationary design supported by fixed piles, and a combination of these two. The facility supports: a 15,000 foot long, 300 foot wide runway, designed to accommodate a two staged winged launch vehicle, with a one million pound payload capacity to low earth orbit; an industrial area for HLLV maintenance; an airport terminal, control and operation center, and observation tower; liquid hydrogen and liquid oxygen production and storage, and fuel storage platforms; a power generation station, docks with an unloading area; two separate launch sites; and living accommodations for 10,000 people. Potential sites include the Paramount Seamount in the Pacific Ocean off the north coast of South America. Cost estimates are considered.

Harvey, D. G.↗

NASA NTRS1991

Introduction to Orbital Sciences Corporation

A general overview of the Orbital Sciences Corporation (OSC) is presented. The following topics are covered: (1) manpower, facilities, and financial growth; (2) organization and management team; (3) the Space Data Division organization; (4) the Chandler facility; (5) Space Data-Products and Services; (6) space transportation systems; (7) spacecraft and space support systems; (8) turn-key suborbital launch services and support systems; and (9) OSC suborbital booster performance.

Source record↗

NASA NTRS1991

A nonradial pulsation model for the rapidly rotating Delta Scuti star Kappa(2) Bootis

A sectorial nonradial pulsation model is used to construct theoretical line profiles which mimic the variations for Kappa(2) Boo. Synthetic spectra generated with the appropriate Teff and log g are used as input. It is found that the data can be reproduced by the combination of a high-degree l is approximately equal to 12 mode with P(osc) aproximately equal to 0.071 d, and a low-degree mode, l is approximately equal to 0-2 with P(osc) approximately equal to 0.071-0.079 d. The projected rotational velocity (v sin i - 115 +/-5 km/s) was determined by fitting synthetic line profiles to the observed spectra. The velocity amplitude of the high-degree oscillations is estimated to be about 3.5 km/s. It is found that the ratio of the horizontal and radial pulsation amplitudes is small (about 0.02) and consistent with p-mode oscillations. Comparisons are made with models invoking starspots, and it is impossible to fit the observations of Kappa(2) Boo by a starspot model without assuming unrealistic values of radius or equatorial velocity.

Kennelly, E. J.↗

NASA NTRS1993

The Telecommunications and Data Acquisition Report

This quarterly publication provides archival reports on developments in programs managed by JPL's Office of Telecommunications and Data Acquisition (TDA) in the following areas: space communications, radio navigation, radio science, and ground-based radio and radar astronomy. This document also reports on the activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). The TDA Office also performs work funded by another NASA program office through and with the cooperation of OSC. This is the Orbital Debris Radar Program with the Office of Space Systems Development.

Posner, Edward C.↗

NASA NTRS1993

An onboard star identification algorithm

The paper presents the autonomous Initial Stellar Acquisition (ISA) algorithm developed for the X-Ray Timing Explorer for prividing the attitude quaternion within the desired accuracy, based on the one-axis attitude knowledge (through the use of the Digital Sun Sensor, CCD Star Trackers, and the onboard star catalog, OSC). Mathematical analysis leads to an accurate measure of the performance of the algorithm as a function of various parameters, such as the probability of a tracked star being in the OSC, the sensor noise level, and the number of stars matched. It is shown that the simplicity, tractability, and robustness of the ISA algorithm, compared to a general three-axis attiude determination algorithm, make it a viable on-board solution.

Ha, Kong↗

NASA NTRS1994

The Telecommunications and Data Acquisition Report

Yuen, Joseph H.↗

NASA NTRS1996

The Telecommunications and Data Acquisition Report

This quarterly publication provides archival reports on developments in programs managed by JPL's Telecommunications and Mission Operations Directorate (TMOD), which now includes the former Telecommunications and Data Acquisition (TDA) Office. In space communications, radio navigation, radio science, and ground-based radio and radar astronomy, it reports on activities of the Deep Space Network (DSN) in planning, supporting research and technology, implementation, and operations. Also included are standards activity at JPL for space data and information systems and reimbursable DSN work performed for other space agencies through NASA. The preceding work is all performed for NASA's Office of Space Communications (OSC). TMOD also performs work funded by other NASA program offices through and with the cooperation of OSC. The first of these is the Orbital Debris Radar Program funded by the Office of Space Systems Development. It exists at Goldstone only and makes use of the planetary radar capability when the antennas are configured as science instruments making direct observations of the planets, their satellites, and asteroids of our solar system. The Office of Space Sciences funds the data reduction and science analyses of data obtained by the Goldstone Solar System Radar. The antennas at all three complexes are also configured for radio astronomy research and, as such, conduct experiments funded by the National Science Foundation in the U.S. and other agencies at the overseas complexes. These experiments are either in microwave spectroscopy or very long baseline interferometry. Finally, tasks funded under the JPL Director's Discretionary Fund and the Caltech President's Fund that involve TMOD are included. This and each succeeding issue of 'The Telecommunications and Data Acquisition Progress Report' will present material in some, but not necessarily all, of the aforementioned programs.

Yuen, Joseph H.↗

NASA NTRS1996

Technology Directions for the 21st Century

The Office of Space Communications (OSC) is tasked by NASA to conduct a planning process to meet NASA's science mission and other communications and data processing requirements. A set of technology trend studies was undertaken by Science Applications International Corporation (SAIC) for OSC to identify quantitative data that can be used to predict performance of electronic equipment in the future to assist in the planning process. Only commercially available, off-the-shelf technology was included. For each technology area considered, the current state of the technology is discussed, future applications that could benefit from use of the technology are identified, and likely future developments of the technology are described. The impact of each technology area on NASA operations is presented together with a discussion of the feasibility and risk associated with its development. An approximate timeline is given for the next 15 to 25 years to indicate the anticipated evolution of capabilities within each of the technology areas considered. This volume contains four chapters: one each on technology trends for database systems, computer software, neural and fuzzy systems, and artificial intelligence. The principal study results are summarized at the beginning of each chapter.

Crimi, Giles F.↗

NASA NTRS1997

Feedback Implementation of Zermelo's Optimal Control by Sugeno Approximation

This paper proposes an approach to implement optimal control laws of nonlinear systems in real time. Our methodology does not require solving two-point boundary value problems online and may not require it off-line either. The optimal control law is learned using the original Sugeno controller (OSC) from a family of optimal trajectories. We compare the trajectories generated by the OSC and the trajectories yielded by the optimal feedback control law when applied to Zermelo's ship steering problem.

Clifton, C.↗

NASA NTRS2004

OrbView-3 Initial On-Orbit Characterization

NASA at Stennis Space Center (SSC) established a Space Act Agreement with Orbital Sciences Corporation (OSC) and ORBIMAGE Inc. to collaborate on the characterization of the OrbView-3 system and its imagery products and to develop characterization techniques further. In accordance with the agreement, NASA performed an independent radiometric, spatial, and geopositional accuracy assessment of OrbView-3 imagery acquired before completion of the system's initial on-orbit checkout. OSC acquired OrbView-3 imagery over SSC from July 2003 through January 2004, and NASA collected ground reference information coincident with many of these acquisitions. After evaluating all acquisitions, NASA deemed two multispectral images and five panchromatic images useful for characterization. NASA then performed radiometric, spatial, and geopositional characterizations.

Ross, Kent↗

NASA NTRS2003

Convection in a Very Compressible Fluid: Comparison of Simulations With Experiments

The time profile (Delta)T(t) of the temperature difference, measured across a very compressible fluid layer of supercritical He-3 after the start of a heat flow, shows a damped oscillatory behavior before steady state convection is reached. The results for (Delta)T(t) obtained from numerical simulations and from laboratory experiments are compared over a temperature range where the compressibility varies by a factor of approx. = 40. First the steady-state convective heat current j(sup conv) as a function of the Rayleigh number R(alpha) is presented, and the agreement is found to be good. Second, the shape of the time profile and two characteristic times in the transient part of (Delta)T(t) from simulations and experiments are compared, namely: 1) t(sub osc), the oscillatory period and 2) t(sub p), the time of the first peak after starting the heat flow. These times, scaled by the diffusive time tau(sub D) versus R(alpha), are presented. The agreement is good for t(sup osc)/tau(sub D), where the results collapse on a single curve showing a powerlaw behavior. The simulation hence confirms the universal scaling behavior found experimentally. However for t(sub p)/tau(sub D), where the experimental data also collapse on a single curve, the simulation results show systematic departures from such a behavior. A possible reason for some of the disagreements, both in the time profile and in t(sub p) is discussed. In the Appendix a third characteristic time, t(sub m), between the first peak and the first oscillation minimum is plotted and a comparison between the results of experiments and simulations is made.

Meyer, H.↗