Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health

• URL: http://arxiv.org/abs/2112.12554v1
• Date: Wed, 22 Dec 2021 05:33:15 GMT
• Title: Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health
• Authors: Ryan T. Scott (1), Erik L. Antonsen (2), Lauren M. Sanders (3), Jaden J.A. Hastings (4), Seung-min Park (5), Graham Mackintosh (6), Robert J. Reynolds (7), Adrienne L. Hoarfrost (8), Aenor Sawyer (9), Casey S. Greene (10), Benjamin S. Glicksberg (11), Corey A. Theriot (12 and 13), Daniel C. Berrios (1), Jack Miller (1), Joel Babdor (14), Richard Barker (15), Sergio E. Baranzini (16), Afshin Beheshti (1), Stuart Chalk (17), Guillermo M. Delgado-Aparicio (18), Melissa Haendel (19), Arif A. Hamid (20), Philip Heller (21), Daniel Jamieson (22), Katelyn J. Jarvis (9), John Kalantari (23), Kia Khezeli (23), Svetlana V. Komarova (24), Matthieu Komorowski (25), Prachi Kothiyal (26), Ashish Mahabal (27), Uri Manor (28), Hector Garcia Martin (29 and 30 and 31), Christopher E. Mason (4), Mona Matar (32), George I. Mias (33), Jerry G. Myers, Jr. (32), Charlotte Nelson (16), Jonathan Oribello (3), Patricia Parsons-Wingerter (34), R. K. Prabhu (35), Amina Ann Qutub (36), Jon Rask (37), Amanda Saravia-Butler (38), Suchi Saria (39 and 40), Nitin Kumar Singh (41), Frank Soboczenski (42), Michael Snyder (43), Karthik Soman (16), David Van Valen (44), Kasthuri Venkateswaran (41), Liz Warren (45), Liz Worthey (46), Jason H. Yang (47), Marinka Zitnik (48), Sylvain V. Costes (49) ((1) KBR, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA., (2) Department of Emergency Medicine, Center for Space Medicine, Baylor College of Medicine, Houston, TX, USA., (3) Blue Marble Space Institute of Science, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA., (4) Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA., (5) Department of Urology, Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA., (6) Bay Area Environmental Research Institute, NASA Ames Research Center, Moffett Field, CA, USA., (7) Mortality Research & Consulting, Inc., Houston, TX, USA., (8) Universities Space Research Association (USRA), Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA., (9) UC Space Health, Department of Orthopaedic Surgery, University of California, San Francisco, San Francisco, CA, USA., (10) Center for Health AI, Department of Biochemistry and Molecular Genetics, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, USA., (11) Hasso Plattner Institute for Digital Health at Mount Sinai, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA., (12) Department of Preventive Medicine and Community Health, UTMB, Galveston, TX, USA., (13) Human Health and Performance Directorate, NASA Johnson Space Center, Houston, TX, USA., (14) Department of Microbiology and Immunology, Department of Otolaryngology, Head and Neck Surgery, University of California San Francisco, San Francisco, CA, USA., (15) The Gilroy AstroBiology Research Group, The University of Wisconsin, Madison, Madison, WI, USA., (16) Weill Institute for Neurosciences, Department of Neurology, University of California San Francisco, San Francisco, CA, USA., (17) Department of Chemistry, University of North Florida, Jacksonville, FL, USA., (18) Data Science Analytics, Georgia Institute of Technology, Lima, Peru., (19) Center for Health AI, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, USA., (20) Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA., (21) Department of Computer Science, College of Science, San Jos\'e State University, San Jose, CA, USA., (22) Biorelate, Manchester, United Kingdom., (23) Center for Individualized Medicine, Department of Surgery, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA., (24) Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada., (25) Faculty of Medicine, Department of Surgery and Cancer, Imperial College London, London, United Kingdom., (26) SymbioSeq LLC, NASA Johnson Space Center, Ashburn, VA, USA., (27) Center for Data Driven Discovery, California Institute of Technology, Pasadena, CA, USA., (28) Waitt Advanced Biophotonics Center, Chan-Zuckerberg Imaging Scientist Fellow, Salk Institute for Biological Studies, La Jolla, CA, USA., (29) Biological Systems and Engineering Division, Lawrence Berkeley National Lab, Berkeley, CA, USA., (30) DOE Agile BioFoundry, Emeryville, CA, USA., (31) Joint BioEnergy Institute, Emeryville, CA, USA., (32) Human Research Program Cross-cutting Computational Modeling Project, NASA John H. Glenn Research Center, Cleveland, OH, USA., (33) Institute for Quantitative Health Science and Engineering, Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA., (34) Low Exploration Gravity Technology, NASA John H. Glenn Research Center, Cleveland, OH, USA., (35) Universities Space Research Association (USRA), Human Research Program Cross-cutting Computational Modeling Project, NASA John H. Glenn Research Center, Cleveland, OH, USA., (36) AI MATRIX Consortium, Department of Biomedical Engineering, University of Texas, San Antonio and UT Health Sciences, San Antonio, TX, USA., (37) Office of the Center Director, NASA Ames Research Center, Moffett Field, CA, USA., (38) Logyx, Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA., (39) Computer Science, Statistics, and Health Policy, Johns Hopkins University, Baltimore, MD, USA., (40) ML, AI and Healthcare Lab, Bayesian Health, New York, NY, USA., (41) Biotechnology and Planetary Protection Group, Jet Propulsion Laboratory, Pasadena, CA, USA., (42) SPHES, Medical Faculty, King's College London, London, United Kingdom., (43) Department of Genetics, Stanford School of Medicine, Stanford, CA, USA., (44) Department of Biology, California Institute of Technology, Pasadena, CA, USA., (45) ISS National Laboratory, Center for the Advancement of Science in Space, Melbourne, FL, USA., (46) UAB Center for Computational Biology and Data Science, University of Alabama, Birmingham, Birmingham, AL, USA., (47) Center for Emerging and Re-Emerging Pathogens, Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Newark, NJ, USA., (48) Department of Biomedical Informatics, Harvard Medical School, Harvard Data Science, Broad Institute of MIT and Harvard, Harvard University, Boston, MA, USA., (49) Space Biosciences Division, NASA Ames Research Center, Moffett Field, CA, USA.)
• Abstract summary: We propose an appropriately autonomous and intelligent Precision Space Health system. It will monitor, aggregate, and assess biomedical statuses. It will analyze and predict personalized adverse health outcomes.
• Score: 0.8838373492847601
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Human space exploration beyond low Earth orbit will involve missions of significant distance and duration. To effectively mitigate myriad space health hazards, paradigm shifts in data and space health systems are necessary to enable Earth-independence, rather than Earth-reliance. Promising developments in the fields of artificial intelligence and machine learning for biology and health can address these needs. We propose an appropriately autonomous and intelligent Precision Space Health system that will monitor, aggregate, and assess biomedical statuses; analyze and predict personalized adverse health outcomes; adapt and respond to newly accumulated data; and provide preventive, actionable, and timely insights to individual deep space crew members and iterative decision support to their crew medical officer. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration, on future applications of artificial intelligence in space biology and health. In the next decade, biomonitoring technology, biomarker science, spacecraft hardware, intelligent software, and streamlined data management must mature and be woven together into a Precision Space Health system to enable humanity to thrive in deep space.

Related papers

• SatHealth: A Multimodal Public Health Dataset with Satellite-based Environmental Factors [8.107949747896107]
  SatHealth is a dataset combining environmental data, satellite images, all-disease prevalences estimated from medical claims, and social determinants of health indicators.<n>We conducted experiments under two use cases with SatHealth: regional public health modeling and personal disease risk prediction.<n>Results show that living environmental information can significantly improve AI models' performance and temporal-spatial generalizability.
  arXiv  Detail & Related papers  (2025-06-16T16:34:41Z)
• A Survey of Large Language Model-Powered Spatial Intelligence Across Scales: Advances in Embodied Agents, Smart Cities, and Earth Science [27.66472429481388]
  We review human spatial cognition and its implications for spatial intelligence in large language models (LLMs) We then examine spatial memory, knowledge representations, and abstract reasoning in LLMs, highlighting their roles and connections. We analyze spatial intelligence across scales -- from embodied to urban and global levels -- following a framework that progresses from spatial memory and understanding to spatial reasoning and intelligence.
  arXiv  Detail & Related papers  (2025-04-14T03:38:31Z)
• Scaling Laws in Scientific Discovery with AI and Robot Scientists [72.3420699173245]
  An autonomous generalist scientist (AGS) concept combines agentic AI and embodied robotics to automate the entire research lifecycle. AGS aims to significantly reduce the time and resources needed for scientific discovery. As these autonomous systems become increasingly integrated into the research process, we hypothesize that scientific discovery might adhere to new scaling laws.
  arXiv  Detail & Related papers  (2025-03-28T14:00:27Z)
• Towards a Reliable Offline Personal AI Assistant for Long Duration Spaceflight [4.382282101149638]
  This paper proposes enhancing systems like METIS by integrating GPTs, Retrieval-Augmented Generation (RAG), Knowledge Graphs (KGs), and Augmented Reality (AR) The idea is to allow astronauts to interact with their data more intuitively, using natural language queries and visualizing real-time information through AR.
  arXiv  Detail & Related papers  (2024-10-21T18:08:42Z)
• Care3D: An Active 3D Object Detection Dataset of Real Robotic-Care Environments [52.425280825457385]
  This paper introduces an annotated dataset of real environments. The captured environments represent areas which are already in use in the field of robotic health care research. We also provide ground truth data within one room, for assessing SLAM algorithms running directly on a health care robot.
  arXiv  Detail & Related papers  (2023-10-09T10:35:37Z)
• Enabling Astronaut Self-Scheduling using a Robust Advanced Modelling and Scheduling system: an assessment during a Mars analogue mission [44.621922701019336]
  We study the usage of a computer decision-support tool by a crew of analog astronauts. The proposed tool, called Romie, belongs to the new category of Robust Advanced Modelling and Scheduling (RAMS) systems.
  arXiv  Detail & Related papers  (2023-01-14T21:10:05Z)
• Neuromorphic Computing and Sensing in Space [69.34740063574921]
  Neuromorphic computer chips are designed to mimic the architecture of a biological brain. The emphasis on low power and energy efficiency of neuromorphic devices is a perfect match for space applications.
  arXiv  Detail & Related papers  (2022-12-10T07:46:29Z)
• Artificial Intelligence and Natural Language Processing and Understanding in Space: Four ESA Case Studies [48.53582660901672]
  We present a methodological framework based on artificial intelligence and natural language processing and understanding to automatically extract information from Space documents. Case studies are implemented across different functional areas of ESA, including Mission Design, Quality Assurance, Long-Term Data Preservation, and the Open Space Innovation Platform.
  arXiv  Detail & Related papers  (2022-10-07T15:50:17Z)
• Coordinated Science Laboratory 70th Anniversary Symposium: The Future of Computing [80.72844751804166]
  In 2021, the Coordinated Science Laboratory CSL hosted the Future of Computing Symposium to celebrate its 70th anniversary. We summarize the major technological points, insights, and directions that speakers brought forward during the symposium. Participants discussed topics related to new computing paradigms, technologies, algorithms, behaviors, and research challenges to be expected in the future.
  arXiv  Detail & Related papers  (2022-10-04T17:32:27Z)
• Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs [0.8855198354664937]
  Space biology research aims to understand fundamental effects of spaceflight on organisms. Bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life.
  arXiv  Detail & Related papers  (2021-12-22T05:18:26Z)
• Autonomous Aerial Robot for High-Speed Search and Intercept Applications [86.72321289033562]
  A fully-autonomous aerial robot for high-speed object grasping has been proposed. As an additional sub-task, our system is able to autonomously pierce balloons located in poles close to the surface. Our approach has been validated in a challenging international competition and has shown outstanding results.
  arXiv  Detail & Related papers  (2021-12-10T11:49:51Z)
• Towards a Collective Agenda on AI for Earth Science Data Analysis [39.78763440312085]
  We aim to inspire researchers, especially the younger generations, to tackle these challenges for a real advance of remote sensing and the geosciences. In our declared agenda for AI on Earth sciences, we aim to inspire researchers, especially the younger generations, to tackle these challenges for a real advance of remote sensing and the geosciences.
  arXiv  Detail & Related papers  (2021-04-11T20:54:44Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.