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      Artificial intelligence in the diagnosis and treatment of acute appendicitis: a narrative review

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          Abstract

          Artificial intelligence is transforming healthcare. Artificial intelligence can improve patient care by analyzing large amounts of data to help make more informed decisions regarding treatments and enhance medical research through analyzing and interpreting data from clinical trials and research projects to identify subtle but meaningful trends beyond ordinary perception. Artificial intelligence refers to the simulation of human intelligence in computers, where systems of artificial intelligence can perform tasks that require human-like intelligence like speech recognition, visual perception, pattern-recognition, decision-making, and language processing. Artificial intelligence has several subdivisions, including machine learning, natural language processing, computer vision, and robotics. By automating specific routine tasks, artificial intelligence can improve healthcare efficiency. By leveraging machine learning algorithms, the systems of artificial intelligence can offer new opportunities for enhancing both the efficiency and effectiveness of surgical procedures, particularly regarding training of minimally invasive surgery. As artificial intelligence continues to advance, it is likely to play an increasingly significant role in the field of surgical learning. Physicians have assisted to a spreading role of artificial intelligence in the last decade. This involved different medical specialties such as ophthalmology, cardiology, urology, but also abdominal surgery. In addition to improvements in diagnosis, ascertainment of efficacy of treatment and autonomous actions, artificial intelligence has the potential to improve surgeons’ ability to better decide if acute surgery is indicated or not. The role of artificial intelligence in the emergency departments has also been investigated. We considered one of the most common condition the emergency surgeons have to face, acute appendicitis, to assess the state of the art of artificial intelligence in this frequent acute disease. The role of artificial intelligence in diagnosis and treatment of acute appendicitis will be discussed in this narrative review.

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          Support-vector networks

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            I.—COMPUTING MACHINERY AND INTELLIGENCE

            A Turing (1950)
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              Acute appendicitis: modern understanding of pathogenesis, diagnosis, and management.

              Acute appendicitis is one of the most common abdominal emergencies worldwide. The cause remains poorly understood, with few advances in the past few decades. To obtain a confident preoperative diagnosis is still a challenge, since the possibility of appendicitis must be entertained in any patient presenting with an acute abdomen. Although biomarkers and imaging are valuable adjuncts to history and examination, their limitations mean that clinical assessment is still the mainstay of diagnosis. A clinical classification is used to stratify management based on simple (non-perforated) and complex (gangrenous or perforated) inflammation, although many patients remain with an equivocal diagnosis, which is one of the most challenging dilemmas. An observed divide in disease course suggests that some cases of simple appendicitis might be self-limiting or respond to antibiotics alone, whereas another type often seems to perforate before the patient reaches hospital. Although the mortality rate is low, postoperative complications are common in complex disease. We discuss existing knowledge in pathogenesis, modern diagnosis, and evolving strategies in management that are leading to stratified care for patients.
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                Author and article information

                Contributors
                gbrisin@tin.it
                Journal
                Updates Surg
                Updates Surg
                Updates in Surgery
                Springer International Publishing (Cham )
                2038-131X
                2038-3312
                12 March 2024
                12 March 2024
                2024
                : 76
                : 3
                : 783-792
                Affiliations
                [1 ]Emergency Surgery and Trauma Center, Department of Abdominal and Endocrine Metabolic Medical and Surgical Sciences, IRCCS, Fondazione Policlinico Universitario A Gemelli, ( https://ror.org/00rg70c39) Largo Agostino Gemelli 8, 00168 Rome, Italy
                [2 ]General Surgery Operative Unit, Vittorio Emanuele Hospital, 93012 Gela, Italy
                [3 ]Department of Surgery, General Surgery Operative Unit, Azienda Sanitaria Provinciale Cosenza, 87100 Cosenza, Italy
                [4 ]Catholic School of Medicine, University Department of Translational Medicine and Surgery, 00168 Rome, Italy
                Author information
                http://orcid.org/0000-0002-8817-3760
                http://orcid.org/0000-0003-1656-6861
                https://orcid.org/0009-0001-0316-1999
                http://orcid.org/0000-0003-3455-0062
                http://orcid.org/0000-0001-8820-9471
                Article
                1801
                10.1007/s13304-024-01801-x
                11129994
                38472633
                b7210c8c-2e01-4828-86bc-ccb326ac606c
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 6 February 2024
                : 24 February 2024
                Funding
                Funded by: Università Cattolica del Sacro Cuore
                Categories
                Review Article
                Custom metadata
                © Italian Society of Surgery (SIC) 2024

                Surgery
                acute appendicitis,artificial intelligence,diagnosis,laparoscopy,surgery
                Surgery
                acute appendicitis, artificial intelligence, diagnosis, laparoscopy, surgery

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