Artificial intelligence in surgical education and training: opportunities, challenges, and ethical considerations – correspondence

Satapathy, Prakasini; Hermis, Alaa Hamza; Rustagi, Sarvesh; Pradhan, Keerti Bhusan; Padhi, Bijaya Kumar; Sah, Ranjit

doi:10.1097/js9.0000000000000387

Cited by 15 publications

(7 citation statements)

References 7 publications

(6 reference statements)

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“…This technology can aid in the early detection of colorectal cancer as well as in the assessment of disease progression and response to treatment, ultimately improving patient outcomes. Machine learning algorithms are also being used to integrate and analyze vast data sets, including genetic, molecular, clinical, and radiological information. , By identifying complex patterns within this data, machine learning can help clinicians predict patient prognosis, identify potential treatment targets, and tailor therapies to individual patients. These algorithms have the capacity to consider a wide range of variables and discover hidden correlations that may not be apparent through traditional methods, offering a more comprehensive and personalized approach to colorectal cancer treatment. , …”

Section: Future Directions and Emerging Technologiesmentioning

confidence: 99%

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Kiran,

Yashaswini,

Maheshwari

et al. 2024

ACS Pharmacol. Transl. Sci.

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Precision medicine is transforming colorectal cancer treatment through the integration of advanced technologies and biomarkers, enhancing personalized and effective disease management. Identification of key driver mutations and molecular profiling have deepened our comprehension of the genetic alterations in colorectal cancer, facilitating targeted therapy and immunotherapy selection. Biomarkers such as microsatellite instability (MSI) and DNA mismatch repair deficiency (dMMR) guide treatment decisions, opening avenues for immunotherapy. Emerging technologies such as liquid biopsies, artificial intelligence, and machine learning promise to revolutionize early detection, monitoring, and treatment selection in precision medicine. Despite these advancements, ethical and regulatory challenges, including equitable access and data privacy, emphasize the importance of responsible implementation. The dynamic nature of colorectal cancer, with its tumor heterogeneity and clonal evolution, underscores the necessity for adaptive and personalized treatment strategies. The future of precision medicine in colorectal cancer lies in its potential to enhance patient care, clinical outcomes, and our understanding of this intricate disease, marked by ongoing evolution in the field. The current reviews focus on providing in-depth knowledge on the various and diverse approaches utilized for precision medicine against colorectal cancer, at both molecular and biochemical levels.

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Section: Future Directions and Emerging Technologiesmentioning

confidence: 99%

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Kiran,

Yashaswini,

Maheshwari

et al. 2024

ACS Pharmacol. Transl. Sci.

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“…Equally crucial is addressing potential biases in AI, given its dependency on training data, to prevent the perpetuation of healthcare disparities, particularly in lung cancer treatment where demographic differences are significant ( 53 , 54 ). Furthermore, the opacity of AI systems necessitates a robust approach to transparency and accountability, ensuring that AI supplements rather than supplants the expert clinical judgment of healthcare professionals ( 54 , 55 ). The ethical integration of AI in thoracic surgery demands continuous monitoring and evaluation to assess its accuracy, effectiveness, safety, and overall impact on patient outcomes, ensuring that AI’s deployment remains aligned with ethical standards and patient-centric values.…”

Section: Challenges and Limitationsmentioning

confidence: 99%

The future of artificial intelligence in thoracic surgery for non-small cell lung cancer treatment a narrative review

Abbaker,

Minervini,

Guttadauro

et al. 2024

Front. Oncol.

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ObjectivesTo present a comprehensive review of the current state of artificial intelligence (AI) applications in lung cancer management, spanning the preoperative, intraoperative, and postoperative phases.MethodsA review of the literature was conducted using PubMed, EMBASE and Cochrane, including relevant studies between 2002 and 2023 to identify the latest research on artificial intelligence and lung cancer.ConclusionWhile AI holds promise in managing lung cancer, challenges exist. In the preoperative phase, AI can improve diagnostics and predict biomarkers, particularly in cases with limited biopsy materials. During surgery, AI provides real-time guidance. Postoperatively, AI assists in pathology assessment and predictive modeling. Challenges include interpretability issues, training limitations affecting model use and AI’s ineffectiveness beyond classification. Overfitting and global generalization, along with high computational costs and ethical frameworks, pose hurdles. Addressing these challenges requires a careful approach, considering ethical, technical, and regulatory factors. Rigorous analysis, external validation, and a robust regulatory framework are crucial for responsible AI implementation in lung surgery, reflecting the evolving synergy between human expertise and technology.

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“…AI exhibits the potential to revolutionize surgical education and practice, promising a future where procedures are optimized for delivering the highest quality patient care. This synergy between surgeons and AI technology marks a paradigm shift in surgical techniques, promising more efficient and effective procedures [ 7 , 9 ].…”

Section: Reviewmentioning

confidence: 99%

Advancements and Challenges in the Application of Artificial Intelligence in Surgical Arena: A Literature Review

Mithany,

Aslam,

Abdallah

et al. 2023

Cureus

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This literature review delves into the transformative potential of artificial intelligence (AI) in the field of surgery, exploring its evolution, applications, and technological advancements. AI, with its ability to mimic human intelligence, presents a paradigm shift in surgical practices. The review critically analyzes a broad range of research, encompassing machine learning, deep learning, natural language processing, and their diverse applications in preoperative planning, surgical simulation, intraoperative guidance, and postoperative analysis. Ethical, legal, and regulatory considerations, as well as challenges and future directions, are also explored. The study underscores AI's ability to revolutionize surgical visualization and its role in shaping the future of healthcare.

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Artificial intelligence in surgical education and training: opportunities, challenges, and ethical considerations – correspondence

Cited by 15 publications

References 7 publications

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

Advances in Precision Medicine Approaches for Colorectal Cancer: From Molecular Profiling to Targeted Therapies

The future of artificial intelligence in thoracic surgery for non-small cell lung cancer treatment a narrative review

Advancements and Challenges in the Application of Artificial Intelligence in Surgical Arena: A Literature Review

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