The future of Cardiothoracic surgery in Artificial intelligence

Mumtaz, Hassan; Saqib, Muhammad; Ansar, Farrukh; Zargar, Durafshan; Hameed, Madiha; Hasan, Mohammad; Muskan, Pakiza

doi:10.1016/j.amsu.2022.104251

Cited by 12 publications

(6 citation statements)

References 35 publications

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“…If the health-care providers are not sure of how the machine came up with the result, they are less likely to be integrated into clinical practice. [ 28 ]…”

Section: Discussionmentioning

confidence: 99%

“…If the health-care providers are not sure of how the machine came up with the result, they are less likely to be integrated into clinical practice. [28] One of the concerns in the use of AI in any field is that it might replace humans. While in of neurosurgery, the outcomes should be patient centric and the use of AI should be weighed on the benefits versus the risk, it can provide to the patients.…”

Section: Role Of Ai In Intraoperative Performance and Safety In Neuro...mentioning

confidence: 99%

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The future of artificial intelligence in neurosurgery: A narrative review

Iqbal

Jahangir

Mashkoor

et al. 2022

Surgical Neurology International

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Background: Artificial intelligence (AI) and machine learning (ML) algorithms are on the tremendous rise for being incorporated into the field of neurosurgery. AI and ML algorithms are different from other technological advances as giving the capability for the computer to learn, reason, and problem-solving skills that a human inherits. This review summarizes the current use of AI in neurosurgery, the challenges that need to be addressed, and what the future holds. Methods: A literature review was carried out with a focus on the use of AI in the field of neurosurgery and its future implication in neurosurgical research. Results: The online literature on the use of AI in the field of neurosurgery shows the diversity of topics in terms of its current and future implications. The main areas that are being studied are diagnostic, outcomes, and treatment models. Conclusion: Wonders of AI in the field of medicine and neurosurgery hold true, yet there are a lot of challenges that need to be addressed before its implications can be seen in the field of neurosurgery from patient privacy, to access to high-quality data and overreliance on surgeons on AI. The future of AI in neurosurgery is pointed toward a patient-centric approach, managing clinical tasks, and helping in diagnosing and preoperative assessment of the patients.

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“…If the health-care providers are not sure of how the machine came up with the result, they are less likely to be integrated into clinical practice. [ 28 ]…”

Section: Discussionmentioning

confidence: 99%

Section: Role Of Ai In Intraoperative Performance and Safety In Neuro...mentioning

confidence: 99%

The future of artificial intelligence in neurosurgery: A narrative review

Iqbal

Jahangir

Mashkoor

et al. 2022

Surgical Neurology International

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“…Central to this ethical framework is ensuring patient autonomy through informed consent, as AI’s involvement in diagnostic and surgical decision-making introduces complexities requiring patient comprehension of AI’s influence on treatment options and conscious choice-making ( 52 ). This aligns with the imperative need to safeguard patient data privacy and security, addressing the ethical challenges posed by AI’s reliance on extensive health data for operation, thereby keeping patient trust and confidentiality ( 53 ). 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 ).…”

Section: Challenges and Limitationsmentioning

confidence: 91%

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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“…Data derived from the AI is very useful for the cardiac anaesthesiologist for diagnostic augmentation, preoperative counselling, optimisation, event prediction (hypoxia and hypotension), resource allocation, developing an anaesthesia plan and personalised perioperative interventions. [ 11 ]…”

Section: Artificial Intelligence In Cardiac Anaesthesiologymentioning

confidence: 99%

Recent advances in cardiac anaesthesia

et al. 2023

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The speciality of cardiac anaesthesia has rapidly evolved over the past few decades with advances in technology, including artificial intelligence (AI), newer devices, techniques, imaging, pain relief and a better understanding of the pathophysiology of disease states. Incorporation of the same has led to improved patient outcomes in terms of morbidity and mortality benefits. With the advent of minimally invasive surgical methods, minimising the dose of opioids and ultrasound-guided regional anaesthesia for pain relief, enhanced recovery after cardiac surgery has been made possible. Perioperative imaging including 3D transoesophageal echocardiography, newer devices and drugs and AI algorithms will play a significant role in cardiac anaesthesia. This review briefly addresses some of the recent advances that the authors believe can impact the practice of cardiac anaesthesia.

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The future of Cardiothoracic surgery in Artificial intelligence

Cited by 12 publications

References 35 publications

The future of artificial intelligence in neurosurgery: A narrative review

The future of artificial intelligence in neurosurgery: A narrative review

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

Recent advances in cardiac anaesthesia

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