EDBT 2026 Demo / reviewers in the wild / expert
Richard M. Satava
dblp:81/512
· DBLP profile ↗
6ranked-venue papers
2as first author
2since 2021 · last 2022
0000-0002-3431-1881ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 4 · 1 first-author · 2 since 2021Artificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1Human-computer interaction and ubiquitous computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
3 papers |
Medical and health informatics · 100% | |
| Computer graphics and multimedia
2 papers |
Virtual and augmented reality · 100% |
Topics — the 5 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Medical and health informatics › surgical robotics
minimally invasive robotic surgery |
0.6 | 1 | 2022 | Robot-Assisted Minimally Invasive Surgery - Surgical Robotics in the Data Age · Proc. IEEE 2022 |
Medical and health informatics
surgical robotics |
0.6 | 1 | 2022 | Robot-Assisted Minimally Invasive Surgery - Surgical Robotics in the Data Age · Proc. IEEE 2022 |
Virtual and augmented reality › virtual reality
virtual reality applications |
0.1 | 1 | 2007 | VR Support of Clinical Applications: Collaboration, Politics, and Ethics · VR 2007 |
Virtual and augmented reality
medical virtual reality |
0.0 | 1 | 1998 | Current and future applications of virtual reality for medicine · Proc. IEEE 1998 |
Virtual and augmented reality
surgical simulation |
0.0 | 1 | 1998 | Current and future applications of virtual reality for medicine · Proc. IEEE 1998 |
Methods — techniques the papers use, named apart from their topics
machine learning · 0.6artificial intelligence · 0.6tissue property measurement · 0.1photorealistic anatomical rendering · 0.1patient-specific modeling · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Robot-Assisted Minimally Invasive Surgery - Surgical Robotics in the Data AgeabstractTelesurgical robotics, as a technical solution for robot-assisted minimally invasive surgery (RAMIS), has become the first domain within medicosurgical robotics that achieved a true global clinical adoption. Its relative success (still at a low single-digit percentile total market penetration) roots in the particular human-in-the-loop control, in which the trained surgeon is always kept responsible for the clinical outcome achieved by the robot-actuated invasive tools. Nowadays, this paradigm is challenged by the need for improved surgical performance, traceability, and safety reaching beyond the human capabilities. Partially due to the technical complexity and the financial burden, the adoption of telesurgical robotics has not reached its full potential, by far. Apart from the absolutely market-dominating da Vinci surgical system, there are already 60+ emerging RAMIS robot types, out of which 15 have already achieved some form of regulatory clearance. This article aims to connect the technological advancement with the principles of commercialization, particularly looking at engineering components that are under development and have the potential to bring significant advantages to the clinical practice. Current RAMIS robots often do not exceed the functionalities deriving from their mechatronics, due to the lack of data-driven assistance and smart human–machine collaboration. Computer assistance is gradually gaining more significance within emerging RAMIS systems. Enhanced manipulation capabilities, refined sensors, advanced vision, task-level automation, smart safety features, and data integration mark together the inception of a new era in telesurgical robotics, infiltrated by machine learning (ML) and artificial intelligence (AI) solutions. Observing other domains, it is definite that a key requirement of a robust AI is the good quality data, derived from proper data acquisition and sharing to allow building solutions in real time based on ML. Emerging RAMIS technologies are reviewed both in a historical and a future perspective. Tamás Haidegger, Stefanie Speidel, Danail Stoyanov, Richard M. Satava |
Proc. IEEE | 4 |
| 2022 | 5G in Healthcare: From COVID-19 to Future ChallengesabstractWorldwide up to May 2022 there have been 515 million cases of COVID-19 infection and over 6 million deaths. The World Health Organization estimated that 115,000 healthcare workers died from COVID-19 from January 2020 to May 2021. This toll on human lives prompted this review on 5G based networking primarily on major components of healthcare delivery: diagnosis, patient monitoring, contact tracing, diagnostic imaging tests, vaccines distribution, emergency medical services, telesurgery and robot-assisted tele-ultrasound. The positive impact of 5G as core technology for COVID-19 applications enabled exchange of huge data sets in fangcang (cabin) hospitals and real-time contact tracing, while the low latency enhanced robot-assisted tele-ultrasound, and telementoring during ophthalmic surgery. In other instances, 5G provided a supportive technology for applications related to COVID-19, e.g., patient monitoring. The feasibility of 5G telesurgery was proven, albeit by a few studies on real patients, in very low samples size in most instances. The important future applications of 5G in healthcare include surveillance of elderly people, the immunosuppressed, and nano- oncology for Internet of Nano Things (IoNT). Issues remain and these require resolution before routine clinical adoption. These include infrastructure and coverage; health risks; security and privacy protection of patients' data; 5G implementation with artificial intelligence, blockchain, and IoT; validation, patient acceptance and training of end-users on these technologies. Andrea Moglia, Konstantinos Georgiou, Blagoi Marinov, Evangelos Georgiou, Raffaella Nice Berchiolli, Richard M. Satava, Alfred Cuschieri |
IEEE J. Biomed. Health Informatics | 6 |
| 2007 | VR Support of Clinical Applications: Collaboration, Politics, and Ethics
Grigore C. Burdea, Zohara A. Cohen, Henry Fuchs, Richard M. Satava |
VR | 4 |
| 2002 | White Paper: Military Research Needs in Biomedical InformaticsabstractThe 2001 U.S. Army Medical Research and Materiel Command (USAMRMC) Biomedical Informatics Roadmap Meeting was devoted to developing a strategic plan in four focus areas: Hospital and Clinical Informatics, E-Health, Combat Health Informatics, and Bioinformatics and Biomedical Computation. The driving force of this Roadmap Meeting was the recent accelerated pace of change in biomedical informatics in which emerging technologies have the potential to affect significantly the Army research portfolio and investment strategy in these focus areas. The meeting was structured so that the first two days were devoted to presentations from experts in the field, including representatives from the three services, other government agencies, academia, and the private sector, and the morning of the last day was devoted to capturing specific biomedical informatics research needs in the four focus areas. This white paper summarizes the key findings and recommendations and should be a powerful tool for the crafting of future requests for proposals to help align USAMRMC new strategic research investments with new developments and emerging technologies. Jaques Reifman, Gary R. Gilbert, Lawrence M. Fagan, Richard M. Satava |
J. Am. Medical Informatics Assoc. | 4 |
| 1998 | Current and future applications of virtual reality for medicineabstractVirtual reality is just emerging as an accepted scientific discipline for medicine. The majority of near-term applications are in the area of surgical planning, interoperative navigation, and surgical simulations. Its use in rehabilitative medicine and psychiatry has made significant progress. The immediate future holds promise for virtual endoscopy, which may replace standard endoscopic procedures for diagnostic screening. Viewing of these virtual images may be with head-mounted displays or true suspended holograms. The most highly developed area is in surgical simulations. Current generations are approaching photorealistic representation of the anatomy, while measurement science is providing physical tissue properties and physiologic parameters. The types of simulations range from "needle-based" procedures, such as standard intravenous insertion, central venous placement catheter, and chest-tube insertion to more sophisticated simulations of full surgical procedures like laparoscopic cholecystectomy or hysteroscopic resection of interuterine myoma. In addition, haptic input devices are providing the sense of touch to the procedures. Soon there will be patient-specific models derived from computed tomography or magnetic resonance imaging scans that will permit a surgeon to practice a delicate surgical procedure on the patient's specific virtual anatomy before actually performing the procedure on the patient. Richard M. Satava, Shaun B. Jones |
Proc. IEEE | 1 |
| 1994 | Emerging medical applications of virtual reality: a surgeon's perspective
Richard M. Satava |
Artif. Intell. Medicine | 1 |