Artificial Intelligence Technologies in Neurosurgery: a Systematic Literature Review Using Topic Modeling. Part II: Research Objectives and Perspectives

Danilov, Gleb; Shifrin, Michael; Kotik, Konstantin; Ishankulov, Timur; Orlov, Yu. N.; Kulikov, A S; Потапов, А. А.

doi:10.17691/stm2020.12.6.12

Cited by 13 publications

(6 citation statements)

References 76 publications

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“…AI systems are created to recognise patterns in data, learn from that data, and then make decisions based on that learning. [6][7][8] Machine learning (ML) is a subset of AI that focuses primarily on the development of algorithms that can learn from data and get better over time without explicit programming. 6,7,9 AI in Neurosurgery: Potential Benefits The use of AI in neurosurgery has got the potential for improving patient outcomes, reducing the risk of complications, and increasing the efficiency of surgical procedures.…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence and neurosurgery: a revolution in the field

Khizar

2024

PJNS

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Artificial Intelligence (AI) is being used in the field of neurosurgery for improving patient outcomes, reducing the risk of complications, and increasing the efficiency of surgical procedures. AI algorithms can analyze patient data, plan surgical procedures, guide surgical instruments, monitor brain activity, and improve post-operative care. The benefits of incorporating AI into neurosurgical practice include pre-operative planning, intraoperative navigation, real-time monitoring, and post-operative care. AI is already being used in neurosurgery for image segmentation, surgical planning, intraoperative navigation, real-time monitoring, and predictive analytics. The potential applications of AI in neurosurgery include personalized medicine, virtual reality, robotic surgery, predictive analytics, and medical imaging. However, the challenges of incorporating AI into neurosurgical practice are data quality, data privacy and security, regulatory frameworks, and training and education. In short, AI has the potential to completely transform the discipline of neurosurgery, but there is a need to address the challenges associated with its incorporation into neurosurgical practice.

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Section: Discussionmentioning

confidence: 99%

Artificial intelligence and neurosurgery: a revolution in the field

Khizar

2024

PJNS

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“…[ 50 ] Another thing to consider is no matter how advanced AI gets, it does not possess human consciousness to take responsible and informed decisions. [ 13 ]…”

Section: Discussionmentioning

confidence: 99%

“…[50] Another thing to consider is no matter how advanced AI gets, it does not possess human consciousness to take responsible and informed decisions. [13] It is recommended to verify and certify AI-based systems for the safety of the patient, and also, AI system failures on patients must be minimized. Another future challenge is to annotate targets, such as sometimes, it is difficult for even the neurosurgeons to recognize the anatomical structures.…”

Section: Limitations and Future Recommendationsmentioning

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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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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“…The dataset for experiments was initially obtained from the PubMed search engine while performing a systematic review of artificial intelligence (AI) applications in neurosurgery in July 2019 [5,6]. The exact search query to PubMed implied a broad definition of artificial intelligence: ("neurosurgical procedures" OR "neurosurgery") AND ("artificial intelligence" OR "machine learning" OR "natural language processing" OR "NLP" OR "text mining" OR "fuzzy logic" OR "data mining" OR "big data" OR "topic model").…”

Section: Methodsmentioning

confidence: 99%

The Classification of Short Scientific Texts Using Pretrained BERT Model

Szostek

Ishankulov

Kotik

et al. 2021

Studies in Health Technology and Informatics

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Automated text classification is a natural language processing (NLP) technology that could significantly facilitate scientific literature selection. A specific topical dataset of 630 article abstracts was obtained from the PubMed database. We proposed 27 parametrized options of PubMedBERT model and 4 ensemble models to solve a binary classification task on that dataset. Three hundred tests with resamples were performed in each classification approach. The best PubMedBERT model demonstrated F1-score = 0.857 while the best ensemble model reached F1-score = 0.853. We concluded that the short scientific texts classification quality might be improved using the latest state-of-art approaches.

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Artificial Intelligence Technologies in Neurosurgery: a Systematic Literature Review Using Topic Modeling. Part II: Research Objectives and Perspectives

Cited by 13 publications

References 76 publications

Artificial intelligence and neurosurgery: a revolution in the field

Artificial intelligence and neurosurgery: a revolution in the field

The future of artificial intelligence in neurosurgery: A narrative review

The Classification of Short Scientific Texts Using Pretrained BERT Model

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