2025
Insights of Key Technologies for Manned-Unmanned Teaming
Yuan M, Wang C, Wu L, Yin D. Insights of Key Technologies for Manned-Unmanned Teaming. Lecture Notes In Electrical Engineering 2025, 1326: 646-658. DOI: 10.1007/978-981-96-2468-3_54.Peer-Reviewed Original ResearchManned-unmanned teamingHuman-swarm interactionMUM-THuman-machine interactionArtificial intelligenceAugmented RealityHuman-machine interaction interfaceHuman-in-the-loop mannerNatural user interfaceHuman-in-the-loopDevelopment of artificial intelligenceReal-world tasksHuman commandsDialogue systemsIntelligent interfaceUser interfaceSpeech recognitionUnmanned systemsOODA loopReal-time feedbackLevel of autonomyKey technologiesEye trackingTaskDesign elements
2024
Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system
Luo Y, Mao C, Sanchez‐Pinto L, Ahmad F, Naidech A, Rasmussen L, Pacheco J, Schneider D, Mithal L, Dresden S, Holmes K, Carson M, Shah S, Khan S, Clare S, Wunderink R, Liu H, Walunas T, Cooper L, Yue F, Wehbe F, Fang D, Liebovitz D, Markl M, Michelson K, McColley S, Green M, Starren J, Ackermann R, D'Aquila R, Adams J, Lloyd‐Jones D, Chisholm R, Kho A. Northwestern University resource and education development initiatives to advance collaborative artificial intelligence across the learning health system. Learning Health Systems 2024, 8: e10417. PMID: 39036530, PMCID: PMC11257059, DOI: 10.1002/lrh2.10417.Peer-Reviewed Original ResearchLearning health systemCollaborative AIMultidisciplinary workforceHealth systemArtificial intelligenceCollaborative artificial intelligenceDevelopment of artificial intelligenceLanguage processing pipelinePeer-reviewed publicationsHealth workforceHealthcare initiativesExtract structural informationAI/machine learningHealth informationHospital administratorsClinical specialtiesHealthcare dataEducational resourcesAI methodsAI scientistsUnmet needsPractical resourcesData modelHealthcareProcessing pipelineThe artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma
Pan X, AbdulJabbar K, Coelho-Lima J, Grapa A, Zhang H, Cheung A, Baena J, Karasaki T, Wilson C, Sereno M, Veeriah S, Aitken S, Hackshaw A, Nicholson A, Jamal-Hanjani M, Swanton C, Yuan Y, Le Quesne J, Moore D. The artificial intelligence-based model ANORAK improves histopathological grading of lung adenocarcinoma. Nature Cancer 2024, 5: 347-363. PMID: 38200244, PMCID: PMC10899116, DOI: 10.1038/s43018-023-00694-w.Peer-Reviewed Original Research
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply