Journal of Psycholinguistic Research, Journal Year: 2023, Volume and Issue: 52(6), P. 2937 - 2954
Published: Nov. 7, 2023
Language: Английский
Anesthesia & Analgesia, Journal Year: 2024, Volume and Issue: 138(2), P. 350 - 357
Published: Jan. 12, 2024
Remote monitoring and artificial intelligence will become common intertwined in anesthesiology by 2050. In the intraoperative period, technology lead to development of integrated systems that integrate multiple data streams allow anesthesiologists track patients more effectively. This free up focus on complex tasks, such as managing risk making value-based decisions. also enable continued integration remote control towers having profound effects coverage practice models. PACU ICU, early warning can identify who are at complications, enabling interventions proactive care. The augmented reality for better diverse types decision-making. Postoperatively, proliferation wearable devices monitor patient vital signs their progress be discharged from hospital sooner receive care home. require increased use telemedicine, which consult with doctors remotely. All these advances changes legal regulatory frameworks new workflows different those familiar today's providers.
Language: Английский
Citations
19
Advanced Intelligent Systems, Journal Year: 2024, Volume and Issue: 6(5)
Published: April 21, 2024
Surgical robot systems (SRS) represent an innovative cross‐disciplinary research field using robotic technology to assist surgeons in operations. Current bottlenecks SRS, such as the limited ability process complex information and make surgical decisions, have not been effectively solved. Artificial intelligence (AI) is a valuable technique for simulating extending human intelligence. AI offers new direction impetus SRS by enhancing performance areas perception, navigation, planning, control strategies. This review introduces developmental history of AI‐aided summarizes basic architecture, analyzes how can improve performance. Classical cases impact evidence clinical settings, associated ethical legal considerations are explored. Finally, challenges discussed, including algorithm development, data science, human–robot coordination, trust building between humans robots.
Language: Английский
Citations
19
Langenbeck s Archives of Surgery, Journal Year: 2025, Volume and Issue: 410(1)
Published: Jan. 28, 2025
Language: Английский
Citations
2
Nature Reviews Gastroenterology & Hepatology, Journal Year: 2022, Volume and Issue: 20(3), P. 171 - 182
Published: Nov. 9, 2022
Language: Английский
Citations
65
npj Digital Medicine, Journal Year: 2022, Volume and Issue: 5(1)
Published: July 19, 2022
Abstract The use of digital technology is increasing rapidly across surgical specialities, yet there no consensus for the term ‘digital surgery’. This critical as health technologies present technical, governance, and legal challenges which are unique to surgeon patient. We aim define surgery ethical issues surrounding its clinical application, identify barriers research goals future practice. 38 international experts, fields surgery, AI, industry, law, ethics policy, participated in a four-round Delphi exercise. Issues were generated by an expert panel public through scoping questionnaire around key themes identified from literature voted upon two subsequent rounds. Consensus was defined if >70% deemed statement important <30% unimportant. A final online meeting held discuss statements. definition enhancement preoperative planning, performance, therapeutic support, or training, improve outcomes reduce harm achieved 100% agreement. highlight concerning data, privacy, confidentiality trust, consent, litigation liability, commercial partnerships within Developers users must not only have awareness applications healthcare, but also considerations surgery. Future into these involve all stakeholders including patients.
Language: Английский
Citations
62
Medical Image Analysis, Journal Year: 2022, Volume and Issue: 80, P. 102488 - 102488
Published: May 27, 2022
Semantic image segmentation is an important prerequisite for context-awareness and autonomous robotics in surgery. The state of the art has focused on conventional RGB video data acquired during minimally invasive surgery, but full-scene semantic based spectral imaging obtained open surgery received almost no attention to date. To address this gap literature, we are investigating following research questions hyperspectral (HSI) pigs setting: (1) What adequate representation HSI neural network-based fully automated organ segmentation, especially with respect spatial granularity (pixels vs. superpixels patches full images)? (2) Is there a benefit using compared other modalities, namely processed (e.g. tissue parameters like oxygenation), when performing segmentation? According comprehensive validation study 506 images from 20 pigs, annotated total 19 classes, deep learning-based performance increases, consistently across context input data. Unprocessed offers advantage over or camera provider, increasing decreasing size network. Maximum (HSI applied whole images) yielded mean DSC 0.90 ((standard deviation (SD)) 0.04), which range inter-rater variability (DSC 0.89 0.07)). We conclude that could become powerful modality fully-automatic surgical scene understanding many advantages traditional imaging, including ability recover additional functional information. Code pre-trained models: https://github.com/IMSY-DKFZ/htc.
Language: Английский
Citations
53
Frontiers in Medical Technology, Journal Year: 2022, Volume and Issue: 4
Published: Dec. 14, 2022
Artificial Intelligence (AI) plays an integral role in enhancing the quality of surgical simulation, which is increasingly becoming a popular tool for enriching training experience surgeon. This spans spectrum from facilitating preoperative planning, to intraoperative visualisation and guidance, ultimately with aim improving patient safety. Although arguably still its early stages widespread clinical application, AI technology enables personal evaluation provides personalised feedback simulations. Several forms technologies currently use anatomical education presurgical assessment rely on different algorithms. However, while it promising see examples technological reports attesting efficacy AI-supported simulators, barriers wide-spread commercialisation such devices software remain complex multifactorial. High implementation production costs, scarcity evidencing superiority technology, intrinsic limitations at forefront. As key driving future this paper will review literature delineating current state, challenges, prospects. In addition, consolidated list FDA/CE approved AI-powered medical simulation presented, order shed light existing gap between academic achievements universal AI-enabled simulators. We call further simulators support novel regulatory body usher surgery into new era education.
Language: Английский
Citations
51
Proceedings of the IEEE, Journal Year: 2022, Volume and Issue: 110(7), P. 932 - 950
Published: May 18, 2022
Interventional robotic systems have been deployed with all existing imaging modalities in an expansive portfolio of therapies and surgeries. Over the years, literature reviews painted a comprehensive portrait translation underlying technology from research to practice. While many these robots performed promisingly preclinical settings, only handful them managed evolve further, break through commercialization boundary, even fewer reached wide-scale adoption. Despite undeniable success service robotics general particularly some sophisticated medical applications, image-guided robotics’ impact remained modest compared other surgical areas, especially laparoscopic minimally invasive surgery. This article aims embrace state art on one hand, provide narrative situation described, support future system developers, facilitate scientific applied clinical development.
Language: Английский
Citations
47
IEEE Transactions on Medical Imaging, Journal Year: 2022, Volume and Issue: 41(7), P. 1677 - 1687
Published: Feb. 2, 2022
Automatically recognising surgical gestures from data is an important building block of automated activity recognition and analytics, technical skill assessment, intra-operative assistance eventually robotic automation. The complexity articulated instrument trajectories the inherent variability due to style patient anatomy make analysis fine-grained segmentation motion patterns robot kinematics alone very difficult. Surgical video provides crucial information site with context for kinematic interaction between instruments tissue. Yet sensor fusion stream non-trivial because have different frequency, dimensions discriminative capability. In this paper, we integrate multimodal attention mechanisms in a two-stream temporal convolutional network compute relevance scores weight visual feature representations dynamically time, aiming aid training achieve effective fusion. We report results our system on JIGSAWS benchmark dataset new vivo suturing segments prostatectomy procedures. Our are promising obtain prediction sequences higher accuracy better structure than corresponding unimodal solutions. Visualization also gives physically interpretable insights understanding strengths weaknesses each sensor.
Language: Английский
Citations
45
Artificial Intelligence Surgery, Journal Year: 2022, Volume and Issue: 2(3), P. 144 - 58
Published: Jan. 1, 2022
Aim: Artificial intelligence (AI) is rapidly evolving in healthcare worldwide, especially surgery. This article reviews important terms used machine learning and the challenges of deep Methods: A review English literature was carried out focused on “challenges learning” “surgery” using Medline PubMed between 2018 2022. Results: In total, 54 articles discussed general. We include 25 from various surgical specialties discussing corresponding to their respective specialties. Conclusion: The increased utilization AI surgery faced with a wide variety technical, ethical, clinical, business-related challenges. best way expedite its expansion safest most cost-efficient manner by ensuring that as many surgeons possible have clear understanding basic concepts how they can be applied preoperative, intraoperative, postoperative, long-term follow-up phases patient care.
Language: Английский
Citations
43