BEGIN:VCALENDAR VERSION:2.0 PRODID:-//swoogo.com//NONSGML kigkonsult.se iCalcreator 2.41.90// CALSCALE:GREGORIAN UID:38313865-6261-4038-a366-643864623033 BEGIN:VEVENT UID:1362315a2f6ff3d7c834850e750a2eb45b51ba1e@swoogo.com DTSTAMP:20261008T001528Z DESCRIPTION:Artificial Intelligence (AI) is poised to revolutionize healthc are deliver by becoming valuable tools to augment clinical decision making \, optimize clinical workflows\, facilitate patient interactions\, and imp rove patient outcomes. Clinical decision-making involves considering vario us factors beyond the immediate data\, such as the patient preferences\, m edical history\, ethical considerations\, and the healthcare setting/opera tional environment. AI algorithms need to be designed to incorporate this contextual information to ensure their recommendations align with real-wor ld clinical practice. Translating AI enhanced healthcare technologies from the lab to the clinic\, especially for military applications in expeditio nary settings where resources may be limited\, requires a unique synergy b etween engineers\, clinicians\, and military advisors. This presentation w ill explore the critical importance of interdisciplinary collaboration\, h ighlighting the challenges and potential solutions in developing clinical AI applications for the military. Developing robust AI algorithms relies h eavily on access to large\, high-quality datasets. For example\, in dental applications the datasets used to develop AI systems comprise of diverse data types including clinical records\, radiographs\, and intraoral images for diagnostics and fabrication of dental appliances. Processing this het erogeneous data presents significant challenges due to data variability\, data scarcity\, data privacy and the potential of incomplete datasets. An associated challenge includes data sharing between DHA and collaborators i n academia or industry. Leveraging opportunities to facilitate collaborati ons where data sharing is restricted will be critical to develop novel AI systems. The U.S. Army Artificial Intelligence Institute (A2I2) has a deve lopment environment that enables collaborations with leading AI experts in the U.S. to solve Army problems related to Expeditionary Maneuver and Air /Ground Reconnaissance. Recently\, the A2I2 development environment was ut ilized by researchers at the U.S Army Institute of Surgical Research to de velop Synthetic Dental Radiographs. The dental research officers at USAISR can leverage their clinical knowledge and experience to integrate with te chnology development teams to advance development of AI systems to optimiz e dentistry in garrison and augment expeditionary dentistry. Military dent al research is an opportunity to advance Military Dentistry\, but the tech nology\, techniques and knowledge gained by developing these AI systems ca n translate to other clinical applications throughout the military healthc are system. The algorithms and techniques developed for Dental AI systems can serve as a platform to advance AI development to augment clinical deci sion making\, interpret medical imaging\, advance medical robotics\, and i ntegrate AI systems with virtual health capabilities. The co-presenters ha ve collaborated to develop AI enhanced portable medical devices for expedi tionary use and dental AI systems. A point of discussion among the present ers is how can differences in clinical judgement among healthcare provider s (end-user) impact the development\, testing and validation of clinical A I systems. While AI excels at pattern recognition and data analysis\, curr ent technology cannot fully replicate or replace the clinical judgment of experienced healthcare providers. The impact of clinical judgement on deve lopment of AI systems is not well studied but is an important component to consider when implementing AI systems into expeditionary and clinical wor kflows. DTSTART:20250304T213000Z DTEND:20250304T223000Z LAST-MODIFIED:20261008T001528Z LOCATION: SEQUENCE:0 STATUS:CONFIRMED SUMMARY:CANCELLED Bridging the Gap: Engineers and Clinicians Working Toget her to Advance Expeditionary Medical and Dental Applications of Artificial Intelligent Systems TRANSP:OPAQUE X-ALT-DESC;FMTTYPE=text/html:

Artificial Intelligence (AI) is poised to r evolutionize healthcare deliver by becoming valuable tools to augment clin ical decision making\, optimize clinical workflows\, facilitate patient in teractions\, and improve patient outcomes. Clinical decision-making involv es considering various factors beyond the immediate data\, such as the pat ient preferences\, medical history\, ethical considerations\, and the heal thcare setting/operational environment. AI algorithms need to be designed to incorporate this contextual information to ensure their recommendations align with real-world clinical practice. Translating AI enhanced healthca re technologies from the lab to the clinic\, especially for military appli cations in expeditionary settings where resources may be limited\, require s a unique synergy between engineers\, clinicians\, and military advisors. This presentation will explore the critical importance of interdisciplina ry collaboration\, highlighting the challenges and potential solutions in developing clinical AI applications for the military. Developing robust AI algorithms relies heavily on access to large\, high-quality datasets. For example\, in dental applications the datasets used to develop AI systems comprise of diverse data types including clinical records\, radiographs\, and intraoral images for diagnostics and fabrication of dental appliances. Processing this heterogeneous data presents significant challenges due to data variability\, data scarcity\, data privacy and the potential of inco mplete datasets. An associated challenge includes data sharing between DHA and collaborators in academia or industry. Leveraging opportunities to fa cilitate collaborations where data sharing is restricted will be critical to develop novel AI systems. The U.S. Army Artificial Intelligence Institu te (A2I2) has a development environment that enables collaborations with l eading AI experts in the U.S. to solve Army problems related to Expedition ary Maneuver and Air/Ground Reconnaissance. Recently\, the A2I2 developmen t environment was utilized by researchers at the U.S Army Institute of Sur gical Research to develop Synthetic Dental Radiographs. The dental researc h officers at USAISR can leverage their clinical knowledge and experience to integrate with technology development teams to advance development of A I systems to optimize dentistry in garrison and augment expeditionary dent istry. Military dental research is an opportunity to advance Military Dent istry\, but the technology\, techniques and knowledge gained by developing these AI systems can translate to other clinical applications throughout the military healthcare system. The algorithms and techniques developed fo r Dental AI systems can serve as a platform to advance AI development to a ugment clinical decision making\, interpret medical imaging\, advance medi cal robotics\, and integrate AI systems with virtual health capabilities. The co-presenters have collaborated to develop AI enhanced portable medica l devices for expeditionary use and dental AI systems. A point of discussi on among the presenters is how can differences in clinical judgement among healthcare providers (end-user) impact the development\, testing and vali dation of clinical AI systems. While AI excels at pattern recognition and data analysis\, current technology cannot fully replicate or replace the c linical judgment of experienced healthcare providers. The impact of clinic al judgement on development of AI systems is not well studied but is an im portant component to consider when implementing AI systems into expedition ary and clinical workflows.

BEGIN:VALARM UID:39353037-6666-4439-b062-393635346266 ACTION:DISPLAY DESCRIPTION:Artificial Intelligence (AI) is poised to revolutionize healthc are deliver by becoming valuable tools to augment clinical decision making \, optimize clinical workflows\, facilitate patient interactions\, and imp rove patient outcomes. Clinical decision-making involves considering vario us factors beyond the immediate data\, such as the patient preferences\, m edical history\, ethical considerations\, and the healthcare setting/opera tional environment. AI algorithms need to be designed to incorporate this contextual information to ensure their recommendations align with real-wor ld clinical practice. Translating AI enhanced healthcare technologies from the lab to the clinic\, especially for military applications in expeditio nary settings where resources may be limited\, requires a unique synergy b etween engineers\, clinicians\, and military advisors. This presentation w ill explore the critical importance of interdisciplinary collaboration\, h ighlighting the challenges and potential solutions in developing clinical AI applications for the military. Developing robust AI algorithms relies h eavily on access to large\, high-quality datasets. For example\, in dental applications the datasets used to develop AI systems comprise of diverse data types including clinical records\, radiographs\, and intraoral images for diagnostics and fabrication of dental appliances. Processing this het erogeneous data presents significant challenges due to data variability\, data scarcity\, data privacy and the potential of incomplete datasets. An associated challenge includes data sharing between DHA and collaborators i n academia or industry. Leveraging opportunities to facilitate collaborati ons where data sharing is restricted will be critical to develop novel AI systems. The U.S. Army Artificial Intelligence Institute (A2I2) has a deve lopment environment that enables collaborations with leading AI experts in the U.S. to solve Army problems related to Expeditionary Maneuver and Air /Ground Reconnaissance. Recently\, the A2I2 development environment was ut ilized by researchers at the U.S Army Institute of Surgical Research to de velop Synthetic Dental Radiographs. The dental research officers at USAISR can leverage their clinical knowledge and experience to integrate with te chnology development teams to advance development of AI systems to optimiz e dentistry in garrison and augment expeditionary dentistry. Military dent al research is an opportunity to advance Military Dentistry\, but the tech nology\, techniques and knowledge gained by developing these AI systems ca n translate to other clinical applications throughout the military healthc are system. The algorithms and techniques developed for Dental AI systems can serve as a platform to advance AI development to augment clinical deci sion making\, interpret medical imaging\, advance medical robotics\, and i ntegrate AI systems with virtual health capabilities. The co-presenters ha ve collaborated to develop AI enhanced portable medical devices for expedi tionary use and dental AI systems. A point of discussion among the present ers is how can differences in clinical judgement among healthcare provider s (end-user) impact the development\, testing and validation of clinical A I systems. While AI excels at pattern recognition and data analysis\, curr ent technology cannot fully replicate or replace the clinical judgment of experienced healthcare providers. The impact of clinical judgement on deve lopment of AI systems is not well studied but is an important component to consider when implementing AI systems into expeditionary and clinical wor kflows. TRIGGER:-PT15M END:VALARM END:VEVENT END:VCALENDAR