Evidence map›Paper›PMID 38315197›Full record

ArticleSurgical endoscopy2024

Explainable artificial intelligence prediction-based model in laparoscopic liver surgery for segments 7 and 8: an international multicenter study.

Victor Lopez-Lopez, Zeniche Morise, Mariano Albaladejo-González, Concepción Gomez Gavara, Brian K P Goh, Ye Xin Koh, Sijberden Jasper Paul, Mohammed Abu Hilal, Kohei Mishima, Jaime Arthur Pirola Krürger and 28 more

Erratum issuedOpen access · hybridAbstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Surgical endoscopy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.8field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

38 authors at 20 institutions in 7 countries.

Victor Lopez-LopezDepartment of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de La Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain.ORCID 0000-0003-1718-3352
Zeniche MoriseDepartment of Surgery, Fujita Health University School of Medicine Okazaki Medical Center, Okazaki, Aichi, Japan.
Mariano Albaladejo-GonzálezDepartment of Information and Communication Engineering, Murcia University, Murcia, Spain.
Concepción Gomez GavaraDepartment of HPB Surgery and Transplants, Vall d'Hebron University Hospital, Barcelona Autonomic University, Barcelona, Spain.
Brian K P GohDepartment of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital and National Cancer Centre Singapore, Singapore, Singapore.
Ye Xin KohDepartment of Hepatopancreatobiliary and Transplant Surgery, Singapore General Hospital and National Cancer Centre Singapore, Singapore, Singapore.
Sijberden Jasper PaulDepartment of Surgery, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy.
Mohammed Abu HilalDepartment of Surgery, Fondazione Poliambulanza Istituto Ospedaliero, Brescia, Italy.
Kohei MishimaDepartment of Surgery, Ageo Central General Hospital, Ageo, Japan.
Jaime Arthur Pirola KrürgerServiço de Cirurgia do Fígado, Divisão de Cirurgia do Aparelho Digestivo, Departamento de Gastroenterologia, Faculdade de Medicina, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, Brazil.
Paulo HermanServiço de Cirurgia do Fígado, Divisão de Cirurgia do Aparelho Digestivo, Departamento de Gastroenterologia, Faculdade de Medicina, Hospital das Clínicas HCFMUSP, Universidade de São Paulo, São Paulo, Brazil.
Alvaro CerezuelaDepartment of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de La Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain.
Roberto BrusadinDepartment of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de La Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain.
Takashi KaizuDepartment of General, Pediatric and Hepatobiliary-Pancreatic Surgery, Kitasato University School of Medicine, Sagamihara, Japan.
Juan LujanDepartment of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de La Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain.
Fernando RotellarDepartment of General Surgery, School of Medicine, Clínica Universidad de Navarra, University of Navarra, Pamplona, Spain.
Kazuteru MondenDepartment of Surgery, Fukuyama City Hospital, Hiroshima, Japan.
Mar DalmauDepartment of HPB Surgery and Transplants, Vall d'Hebron University Hospital, Barcelona Autonomic University, Barcelona, Spain.
Naoto GotohdaDepartment of Surgery, National Cancer Center Hospital East, Kashiwa, Japan.
Masashi KudoDepartment of Surgery, National Cancer Center Hospital East, Kashiwa, Japan.
Akishige KanazawaDepartment of Hepato-Biliary-Pancreatic Surgery, Osaka City General Hospital, Osaka, Japan.
Yutaro KatoDepartment of Surgery, Fujita Health University, Toyoake, Japan.
Hiroyuki NittaDepartment of Surgery, Iwate Medical University, Iwate, Japan.
Satoshi AmanoDepartment of Surgery, Iwate Medical University, Iwate, Japan.
Raffaele Dalla ValleGeneral Surgery Unit, Parma University Hospital, Parma, Italy.
Mario GiuffridaGeneral Surgery Unit, Parma University Hospital, Parma, Italy.
Masaki UenoSecond Department of Surgery, Wakayama Medical University, 811-1 Kimiidera, Wakayama City, Wakayama, Japan.
Yuichiro OtsukaDepartment of Surgery, Toho University, Tokyo, Japan.
Daisuke AsanoDepartment of Hepatobiliary and Pancreatic Surgery, Graduate School of Medicine, Tokyo Medical and Dental University, Tokyo, Japan.
Minoru TanabeDepartment of Hepatobiliary and Pancreatic Surgery, Graduate School of Medicine, Tokyo Medical and Dental University, Tokyo, Japan.
Osamu ItanoDepartment of Hepato-Biliary-Pancreatic and Gastrointestinal Surgery, School of Medicine, International University of Health and Welfare, Chiba, Japan.
Takuya MinagawaDepartment of Hepato-Biliary-Pancreatic and Gastrointestinal Surgery, School of Medicine, International University of Health and Welfare, Chiba, Japan.
Dilmurodjon EshmuminovDepartment of Surgery and Transplantation, University Hospital Zurich and University of Zurich, Zurich, Switzerland.
Irene HerreroDepartment of Surgery, Getafe University Hospital, Madrid, Spain.
Pablo RamírezDepartment of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de La Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain.
José A Ruipérez-ValienteDepartment of Information and Communication Engineering, Murcia University, Murcia, Spain. jruiperez@um.es.
Ricardo Robles-Campos *Department of General, Visceral and Transplantation Surgery, Clinic and University Hospital Virgen de La Arrixaca, IMIB-ARRIXACA, El Palmar, Murcia, Spain.
Go Wakabayashi *Department of Surgery, Ageo Central General Hospital, Ageo, Japan.
Hospital Universitario Virgen de la Arrixaca · ESClinica Universidad de Navarra · ESFujita Health University · JPHakodate Central General Hospital · JPHospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo · BRInternational University of Health and Welfare · JPIwate Medical University · JPNational Cancer Center Hospital East · JPNational University of Singapore · SGTokyo Medical and Dental University · JPUniversidad de Murcia · ESUniversitat Autònoma de Barcelona · ESUniversity of Parma · ITFondazione Poliambulanza Istituto Ospedaliero · ITFukuyama City Hospital · JPHospital Universitario de Getafe · ESKitasato University · JPOsaka City General Hospital · JPToho University · JPUniversity Hospital Southampton NHS Foundation Trust · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is becoming more useful as a decision-making and outcomes predictor tool. We have developed AI models to predict surgical complexity and the postoperative course in laparoscopic liver surgery for segments 7 and 8.

methodsWe included patients with lesions located in segments 7 and 8 operated by minimally invasive liver surgery from an international multi-institutional database. We have employed AI models to predict surgical complexity and postoperative outcomes. Furthermore, we have applied SHapley Additive exPlanations (SHAP) to make the AI models interpretable. Finally, we analyzed the surgeries not converted to open versus those converted to open.

resultsOverall, 585 patients and 22 variables were included. Multi-layer Perceptron (MLP) showed the highest performance for predicting surgery complexity and Random Forest (RF) for predicting postoperative outcomes. SHAP detected that MLP and RF gave the highest relevance to the variables "resection type" and "largest tumor size" for predicting surgery complexity and postoperative outcomes. In addition, we explored between surgeries converted to open and non-converted, finding statistically significant differences in the variables "tumor location," "blood loss," "complications," and "operation time."

conclusionWe have observed how the application of SHAP allows us to understand the predictions of AI models in surgical complexity and the postoperative outcomes of laparoscopic liver surgery in segments 7 and 8.

Indexed as

Artificial IntelligenceHepatectomyLaparoscopyLiver NeoplasmsAdultAgedFemaleHumansMaleMiddle AgedOperative TimePostoperative ComplicationsArtificial intelligenceLiver resectionMaking decisionMinimally invasive surgery

Identifiers

PMID38315197
PMCPMC11078826
OpenAlexW4391530303

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.