Surgeries are life-saving procedures requiring high precision in preparation, making cuts to affected tissues with minimum incisions and damage to nearby organs and stitching the cut after. When human doctors tend to have shaky hand movements during such procedures, AI can help, especially in life-critical situations. More inaccessible and delicate procedures such as neurosurgery can be sufficiently performed by teleoperation or remote human control of robots eliminating the challenges faced by humans in similar situations.
This article summarizes the recent advances and future perspectives of AI-related research and development in the field of surgery. Surgical video recognition is a more complex and challenging task, but with development in computer vision, future surgical advancements, such as intraoperative decision-making support and image navigation surgery can be made.
https://onlinelibrary.wiley.com/doi/full/10.1002/ags3.12513
Patient safety during robot-assisted surgery is of utmost importance, having legal repercussions and this article discusses this topic. Challenges such as small size of datasets, heterogeneity of algorithms and datasets, lack of critical tasks identification of AI-based RAS operations and transparency have been highlighted.
https://www.sciencedirect.com/science/article/pii/S1743919121002867
Current robot-assisted minimally invasive surgery robots (RAMIS) often do not exceed the functionalities deriving from their mechatronics, due to the lack of data-driven assistance and smart human–machine collaboration. 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 to ensure more efficiency in the process.
https://ieeexplore.ieee.org/abstract/document/9805581
Differences in surgical access, treatment, and outcomes are directly based on factors such as race, ethnicity, socioeconomic status, geographic location, and insurance coverage. These Public health issues can arise from systemic inequalities in healthcare, implicit biases, and differences in preoperative health conditions. Provider Bias and Decision-Making as well as Public health issues in Organ Transplantation make it challenging to obtain critical treatment on a timely basis.
Results of this study suggested that despite national initiatives, Public health issues have persisted for all analyzed procedures and worsened for one-third of the analyzed procedures. These Public health issues were evident regardless of US census division, hospital teaching status, or insurance status. Black patients underwent surgery at lower rates than White patients. In addition, racial differences were observed in the Medicare, Medicaid, and private insurance populations.
https://jamanetwork.com/journals/jamasurgery/fullarticle/2775061
The lack of a diverse physician workforce and the historical andongoing Public health issues in surgical oncology research funding have profoundly impacted the quality of care and outcomes for diverse populations as highlighted in this article. Black and Hispanic populations submitted fewer funding revisions, similar populations along with Asians submitted fewer race-based survey data, and faced more delays in medical interventions and financial support.
https://onlinelibrary.wiley.com/doi/abs/10.1002/jso.27826
Despite being the preferred modality for treatment of colorectal cancer and diverticular disease, minimally invasive surgery (MIS) has been adopted slowly for treatment of inflammatory bowel disease (IBD) due to its technical challenges. The present study aims to assess the Public health issues in use of MIS for patients with IBD. Populations of minority groups had lesser access to quality procedures, facing more side effects.
https://link.springer.com/article/10.1007/s00464-023-10400-7
The intersection of AI, Public health issues, and surgery involves leveraging artificial intelligence to address inequalities in surgical care while also ensuring that AI-driven solutions do not inadvertently perpetuate biases. Through AI Transparency & Explainability, Inclusive AI Development, and AI-assisted Surgical Training, these issues can be mitigated.
In order to better understand the effects of AI in surgical settings, this paper focuses on five key areas: promising AI applications, bias-reduction tactics, and ethical AI implementation, effects on patient outcomes and access to surgical services, and future directions for better AI in surgical care.
This research seeks to define an integrative and comprehensive ethical framework for Care Robots (CRs), encompassing a wide range of AI-related issues in healthcare. To build the framework, the authors combine principles of beneficence, non-maleficence, autonomy, justice, and explainability by integrating the AI4People framework for a Good AI Society and the traditional bioethics perspective.
https://www.mdpi.com/2218-6581/12/4/110
In this overview, many benefits of robot-assisted surgery are discussed including improved patient outcomes, reduced complications, faster recovery times, cost-effectiveness, and enhanced surgeon experiences. The outlook reveals a healthcare landscape where robotic surgery is increasingly vital, enabling personalized medicine, bridging healthcare Public health issues, and advancing surgical precision. However, challenges such as cost, surgeon training, technical issues, ethical considerations, and patient acceptance remain relevant.
https://assets.cureus.com/uploads/review_article/pdf/191019/20240724-319105-xlf8ym.pdf