Revolutionizing Remote Surgery: The Impact of Artificial Intelligence on Peripheral Practice

Abstract

Revolutionizing Remote Surgery: The Impact of Artificial Intelligence on Peripheral Practice

Dr. Sunil Kumar

Ex-HOD and Senior consultant, TATA main Hospital, Jamshedpur

Dr. Saurabh Bokade

(MBBS, DNB, FIAGES, PDF GI-HPB Oncosurgery)

Asst. Professor, NKPSIMS & RC and LMH, Nagpur

AI involves computers mimicking intelligent behaviour with minimal human involvement, often linked to robots, from the Czech term "robota" meaning forced labour machines. In medicine, AI is divided into virtual and physical realms. Virtual AI employs informatics like deep learning for managing data and aiding decisions in electronic health records. Physical AI encompasses robots aiding patients or surgeons and nano-robots for drug delivery.¹

AI is a vast interdisciplinary field encompassing logic, statistics, psychology, neuroscience, and more. Strategic foresight in AI applications can shift workplace practices from reactive to proactive, aiding in addressing and mitigating negative impacts on worker safety and well-being. ²

AI empowers computers to learn from data and mimic human thinking, revolutionizing healthcare with enhanced learning and decision support systems. This transformation affects clinical practice, research, and public health, underlining the crucial significance of privacy, data sharing, and genetic information.³

Professionals in the life sciences working with Artificial Intelligence (AI) and Machine Learning (ML) face growing pressure to accelerate algorithm development. These technologies focus on how computers can learn from data and emulate human cognitive processes. AI and ML enhance learning capabilities and provide decision support systems at a scale that is reshaping the future of healthcare. ⁴

The fusion of artificial intelligence (AI) with geographic information systems (GIS) has given rise to GeoAI. This emerging field is becoming increasingly significant in health and healthcare, as geographic location plays a crucial role in both population and individual health. ⁵

Despite the extensive literature highlighting the significant potential of artificial intelligence (AI), there are no reports demonstrating its effectiveness in enhancing patient safety in robot-assisted surgery (RAS). ⁶

The growing need for AI-driven clinical decision support systems (CDSS) underscores the importance of AI-based clinical outcome prediction models. "Dr. Answer," an AI software for predicting outcomes in prostate cancer treated with radical prostatectomy, serves as an effective CDSS. It aids physicians in decision-making and helps patients understand and feel more confident about their treatment outcomes. ⁷

The Dr. Answer AI project, developed using a biochemical recurrence (BCR) prediction model, serves as a clinical decision support system that assists physicians and patients in making informed treatment decisions during clinical follow-ups. ⁸

Artificial intelligence also plays a significant role in thoracic surgery, aiding in diagnosis, pulmonary disease management, preoperative risk assessment, surgical planning, and outcomes prediction. ⁹

While AI in colorectal surgery is currently in its early stages of development, the rapid progression of technologies suggests that it will likely become more integrated into everyday practice in the near future.¹⁰

For aspiring surgeons engaged in remote practice, artificial intelligence stands as a valuable asset. The advancement of robotic and microrobotic surgical platforms is enriching surgical training and refining technical performance. ¹¹

AI plays a crucial role in decision-making, especially in scenarios with complex treatment options. Accurate predictions from AI models can significantly impact patient and provider behavior by offering objectivity amid uncertainty. Wijnberge et al. used AI to forecast intraoperative hypotension, resulting in fewer episodes and reduced time-weighted hypotension. Similarly, Shimabukuro et al. implemented a machine-learning tool for sepsis prediction, leading to shorter ICU stays and lower in-hospital mortality rates. Successful integration of AI decision support requires alignment with digital workflows and redefining their role in surgical care beyond clinical trials.¹²  AI can be implemented in the Enhanced Recovery after Surgery (ERAS) pathway post operatively. ¹⁰

Artificial intelligence (AI) is increasingly utilized in clinical medicine, particularly in surgery where machine learning algorithms serve as decision aids for risk prediction and intraoperative tasks like image recognition and video analysis. Despite its promise, the implementation of AI in surgery warrants careful consideration due to potential pitfalls for hospital systems and surgeons. ¹³

Artificial intelligence (AI), particularly natural language processing (NLP), has surged in popularity. ChatGPT, a chatbot utilizing NLP, excels in generating natural conversations. Its medicine integration holds immense potential for healthcare delivery. While studies have assessed ChatGPT's accuracy in self-diagnosis, there's still a gap in research concerning its precision and recommendation of medical consultations. ¹⁴