Artificial Intelligence in Perioperative Planning and Management of Liver Resection.

Artificial intelligence Liver resections Perioperative management

Journal

Indian journal of surgical oncology
ISSN: 0975-7651
Titre abrégé: Indian J Surg Oncol
Pays: India
ID NLM: 101532448

Informations de publication

Date de publication:
May 2024
Historique:
received: 18 09 2023
accepted: 16 01 2024
pmc-release: 01 05 2025
medline: 31 5 2024
pubmed: 31 5 2024
entrez: 31 5 2024
Statut: ppublish

Résumé

Artificial intelligence (AI) is a speciality within computer science that deals with creating systems that can replicate the intelligence of a human mind and has problem-solving abilities. AI includes a diverse array of techniques and approaches such as machine learning, neural networks, natural language processing, robotics, and expert systems. An electronic literature search was conducted using the databases of "PubMed" and "Google Scholar". The period for the search was from 2000 to June 2023. The search terms included "artificial intelligence", "machine learning", "liver cancers", "liver tumors", "hepatectomy", "perioperative" and their synonyms in various combinations. The search also included all MeSH terms. The extracted articles were further reviewed in a step-wise manner for identification of relevant studies. A total of 148 articles were identified after the initial literature search. Initial review included screening of article titles for relevance and identifying duplicates. Finally, 65 articles were reviewed for this review article. The future of AI in liver cancer planning and management holds immense promise. AI-driven advancements will increasingly enable precise tumour detection, location, and characterisation through enhanced image analysis. ML algorithms will predict patient-specific treatment responses and complications, allowing for tailored therapies. Surgical robots and AI-guided procedures will enhance the precision of liver resections, reducing risks and improving outcomes. AI will also streamline patient monitoring, better hemodynamic management, enabling early detection of recurrence or complications. Moreover, AI will facilitate data-driven research, accelerating the development of novel treatments and therapies. Ultimately, AI's integration will revolutionise liver cancer care, offering personalised, efficient and effective solutions, improving patients' quality of life and survival rates.

Identifiants

pubmed: 38818006
doi: 10.1007/s13193-024-01883-4
pii: 1883
pmc: PMC11133260
doi:

Types de publication

Journal Article Review

Langues

eng

Pagination

186-195

Informations de copyright

© The Author(s), under exclusive licence to Indian Association of Surgical Oncology 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Déclaration de conflit d'intérêts

Competing interestsThe authors declare no competing interests.

Auteurs

Shruti Gairola (S)

Department of Anaesthesiology, Critical Care and Pain, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra India.

Sohan Lal Solanki (SL)

Department of Anaesthesiology, Critical Care and Pain, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra India.

Shraddha Patkar (S)

Division of Hepatobiliary Surgical Oncology, Department of Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra India.

Mahesh Goel (M)

Division of Hepatobiliary Surgical Oncology, Department of Surgical Oncology, Tata Memorial Hospital, Homi Bhabha National Institute, Mumbai, Maharashtra India.

Classifications MeSH