Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.

BACKGROUND: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study evaluates the feasibility of predicting AL using machine learning (ML) algorithms based on preoperative data. METHODS: We retrospectively analyzed data including 21 predictors from patients undergoing colorectal surgery with bowel anastomosis at four Swiss hospitals. Several ML algorithms were applied for binary classification into AL or non-AL groups, utilizing a five-fold cross-validation strategy with a 90% training and 10% validation split. Additionally, a holdout test set from an external hospital was employed to assess the models' robustness in external validation. RESULTS: Among 1244 patients, 112 (9.0%) suffered from AL. The Random Forest model showed an AUC-ROC of 0.78 (SD: ± 0.01) on the internal test set, which significantly decreased to 0.60 (SD: ± 0.05) on the external holdout test set comprising 198 patients, including 7 (3.5%) with AL. Conversely, the Logistic Regression model demonstrated more consistent AUC-ROC values of 0.69 (SD: ± 0.01) on the internal set and 0.61 (SD: ± 0.05) on the external set. Accuracy measures for Random Forest were 0.82 (SD: ± 0.04) internally and 0.87 (SD: ± 0.08) externally, while Logistic Regression achieved accuracies of 0.81 (SD: ± 0.10) and 0.88 (SD: ± 0.15). F1 Scores for Random Forest moved from 0.58 (SD: ± 0.03) internally to 0.51 (SD: ± 0.03) externally, with Logistic Regression maintaining more stable scores of 0.53 (SD: ± 0.04) and 0.51 (SD: ± 0.02). CONCLUSION: In this pilot study, we evaluated ML-based prediction models for AL post-colorectal surgery and identified ten patient-related risk factors associated with AL. Highlighting the need for multicenter data, external validation, and larger sample sizes, our findings emphasize the potential of ML in enhancing surgical outcomes and inform future development of a web-based application for broader clinical use.

Safety and efficacy of LA-ERCP procedure following Roux-en-Y gastric bypass: a systematic review and meta-analysis.

INTRODUCTION: Rapid weight loss following Roux-en-Y gastric bypass surgery (RYGB) translates to an increased need for endoscopic retrograde cholangiopancreatography (ERCP) intervention. Laparoscopically Assisted Transgastric ERCP (LA-ERCP) has emerged to address the issue of accessing the excluded stomach. This study aims to evaluate the safety and efficacy of LA-ERCP procedure following RYGB. METHODS: The Cochrane, EMBASE, SCOPUS, MEDLINE, Daily and Epub databases were searched from inception to May 2022 using the PRISMA guidelines. Eligible studies reported participants older than 18 years who underwent the LA-ERCP procedure, following RYGB, and outcomes of patients. RESULTS: 27 unique studies met the inclusion criteria with 1283 patients undergoing 1303 LA-ERCP procedures. 81.9% of the patients were female and the mean age was 52.18 ± 13.38 years. The rate of concurrent cholecystectomy was 33.6%. 90.9% of procedures were undertaken for a biliary indication. The mean time between RYGB and LA-ERCP was 89.19 months. The most common intervention performed during the LA-ERCP was a sphincterotomy (94.3%). Mean total operative time was 130.48 min. Mean hospital length of stay was 2.697 days. Technical success was 95.3%, while clinical success was 93.8%. 294 complications were recorded with a 20.6% complication rate. The most frequent complications encountered were pancreatitis (6.8%), infection (6.1%), bleeding (3.4%), and perforation (2.5%). Rate of conversion to open laparotomy was 7%. CONCLUSION: This meta-analysis presents preliminary evidence to suggest the safety and efficacy of LA-ERCP procedure following RYGB. Further investigations are warranted to evaluate the long-term efficacy of this procedure using studies with long-term patient follow-up.

Is pain control for chronic neuropathic pain after inguinal hernia repair using endoscopic retroperitoneal neurectomy effective? A meta-analysis of 142 patients from 1995 to 2022.

PURPOSE: Neuropathic pain is a complication after groin hernia surgery. Triple neurectomy of the iliohypogastric nerve, ilioinguinal nerve and genitofemoral nerve is an efficient treatment modality, with several surgical approaches. The minimally invasive endoscopic method to neurectomy was specifically investigated in this meta-analysis. Our aim is to determine the efficacy of this method in the treatment of chronic neuropathic pain posthernia repair surgery. METHODS: A systematic review was conducted using four databases to search for the keywords ("endoscopic retroperitoneal neurectomy" and "laparoscopic retroperitoneal neurectomy"). The NCBI National Library of Medicine, Cochrane Library, MEDLINE Complete and BioMed Central were last searched on 26 May 2022. Randomised control trials and retrospective or prospective papers involving endoscopic retroperitoneal neurectomy operations after inguinal hernia repair were included. All other surgeries, procedures and study designs were excluded. The internal quality of included studies was assessed using the Newcastle-Ottawa Scale. The percentage of patients who had reduction in pain ("positive treatment outcome") was used to assess the procedure's effectiveness in each analysis. RESULTS: Five comparable endoscopic retroperitoneal neurectomy studies with a total of 142 patients were analysed. Both the Wald test (Q (6) = 1.79, = .775) and the probability ratio test (Q (6) = 4.24, = .374) provide similar findings (0.000, 0.0% [0.0%; 78%]). The meta-analysis' key finding is that the intervention was up to 78% effective (95% confidence interval, 71%; 84%). CONCLUSION: Endoscopic retroperitoneal neurectomy can be an effective treatment option for postoperative neuropathic pain relief following surgical hernia repair. Although there is limited reported experience with this technique, it may provide a clinical benefit to the patient. We recommend further prospective data and long-term follow-up studies be conducted to confirm and expand on these outcomes.

Relationship between training supervision and evolution of the density of GPs: a 3-year cohort study on French cities between 2018 and 2021.

CONTEXT: There is an uneven distribution of general practitioners (GPs) across territories of developed countries leading to inequalities in access to health care. Countries are implementing incentive or coercive policies depending on the characteristics of their health system. Several studies suggest that the location of practical training may influence the location of GPs' practices. The objective of this study is to investigate the existence of a relationship between training supervision and evolution of the density of GPs in French municipalities between 2018 and 2021. METHODS: The evolution of the density of GPs in almost all French municipalities between 2018 and 2021 was followed up. A bivariate statistical analysis was carried out to look for a relationship between the evolution of the density of GPs and the number of training supervisors. Other bivariate analyses were carried out with other factors likely to influence the density of GPs, such as the existence of financial aid in the territory or the age of GPs. A multivariate analysis with all the significant variables in bivariate analysis was then carried out using the stepwise descending method. RESULTS: A total of 34 990 (99.9%) French municipalities were included in the follow-up. Among these, 9427 (26.9%) had a GP and 3866 (11%) had a GP involved in the training supervision. The density of GPs in French cities decreased on average by 2.17% between 2018 and 2021. Territories without training supervisors decreased by 4.63% while those with at least one increased by 1.36% (p < 0.01). This significant relationship was also found in multivariate analysis. CONCLUSION: The training supervision is associated with a better evolution of density of GPs in French municipalities. This association persisted when other factors were considered. The results of this 3-year follow-up may lead us to consider the training supervision as a factor to regulate the distribution of GPs.

Prognostic Value of Immunohistochemical Markers for Locally Advanced Rectal Cancer.

The aim of this study is to reveal the potential roles of apoptosis markers (Bcl2 and p53), proliferation markers (Ki-67 and CyclD1), and the neuroendocrine marker Chromogranin A as markers for the radioresistance of rectal cancer. Statistically significant differences were found in the expression of p53, Ki-67, and Chromogranin A in groups of patients with and without a favorable prognosis after radiotherapy. The survival analysis revealed that the marker of neuroendocrine differentiation, Chromogranin A, also demonstrated a high prognostic significance, indicating a poor prognosis. Markers of proliferation and apoptosis had no prognostic value for patients who received preoperative radiotherapy. Higher Chromogranin A values were predictors of poor prognosis. The results obtained from studying the Chromogranin A expression suggest that the secretion of biologically active substances by neuroendocrine cells causes an increase in tumor aggressiveness.

Advancements of Artificial Intelligence in Liver-Associated Diseases and Surgery.

Background and Objectives: The advancement of artificial intelligence (AI) based technologies in medicine is progressing rapidly, but the majority of its real-world applications has not been implemented. The establishment of an accurate diagnosis with treatment has now transitioned into an artificial intelligence era, which has continued to provide an amplified understanding of liver cancer as a disease and helped to proceed better with the method of procurement. This article focuses on reviewing the AI in liver-associated diseases and surgical procedures, highlighting its development, use, and related counterparts. Materials and Methods: We searched for articles regarding AI in liver-related ailments and surgery, using the keywords (mentioned below) on PubMed, Google Scholar, Scopus, MEDLINE, and Cochrane Library. Choosing only the common studies suggested by these libraries, we segregated the matter based on disease. Finally, we compiled the essence of these articles under the various sub-headings. Results: After thorough review of articles, it was observed that there was a surge in the occurrence of liver-related surgeries, diagnoses, and treatments. Parallelly, advanced computer technologies governed by AI continue to prove their efficacy in the accurate screening, analysis, prediction, treatment, and recuperation of liver-related cases. Conclusions: The continual developments and high-order precision of AI is expanding its roots in all directions of applications. Despite being novel and lacking research, AI has shown its intrinsic worth for procedures in liver surgery while providing enhanced healing opportunities and personalized treatment for liver surgery patients.

Association of a prehabilitation program with anxiety and depression before colorectal surgery: a post hoc analysis of the pERACS randomized controlled trial.

PURPOSE: Hospital-associated anxiety and depression are major preoperative stressors and common in colorectal cancer surgery and major abdominal surgery. The prehabilitation Enhanced Recovery After Colorectal Surgery (pERACS) study is a single-center, single-blinded randomized controlled trial (RCT) evaluating the effect of a structured prehabilitation program. We evaluate within this RCT the association of a prehabilitation program with anxiety and depression before colorectal surgery. METHODS: Treatment allocation randomized and single-blinded. Regardless of group allocation, patients were treated according to our institutional Enhanced Recovery After Surgery (ERAS) protocol. Inclusion criteria consisted of adult patients suffering from colorectal disease requiring surgical treatment and who were treated according to the ERAS protocol. Anxiety and depression scores were assessed at baseline and at admission according to the Hospital Anxiety and Depression Scale (HADS), with its subcomponents for depression (HADS-D) and for anxiety (HADS-A). RESULTS: A total of 23 patients randomized to prehabilitation (mean age: 64.8±11.5 years) and 25 patients randomized to the control group (64.0±11.9 years) were included. There was no statistically significant difference in HADS-Anxiety improvement (Prehabilitation: -1.7±2.8 points vs. control: -0.4±3.4 points, p=0.132). Similarly, the difference in HADS-Depression improvement among the prehabilitation (1.0±2.4 points) and control (-0.3 ± 4.0 points) groups (p = 0.543) was non-significant. Clinically meaningful improvement in anxiety (60.9%/40.0%, p=0.149) and depression (34.8%/20.0%, p=0.250) was similar among the groups. CONCLUSION: In a post hoc analysis of a randomized trial, prehabilitation had no effect on preoperative reduction of anxiety and depression measures. TRIAL REGISTRATION NUMBER: Clinicaltrials.gov NCT02746731. Date of registration: April 21, 2016.

Risk indicators of aggressive periodontitis in a Jordanian population.

BACKGROUND: Knowledge of the risk indicators of aggressive periodontitis (AgP) will help clinicians to better diagnose the disease, put a treatment plan that involves modification of modifiable risk indicators, understand non-modifiable risk indicators, and may potentially serve as an aid in developing preventive programs. The objective of the present study was to assess risk indicators of aggressive periodontitis (AgP) in Jordan including socio-demographic factors, oral hygiene habits, smoking, family history and parents' consanguinity. METHODS: A total of 162 patients (81 AgP and 81 controls), attending the Periodontology clinic at Jordan University of Science and Technology, Dental Teaching Centre, were interviewed and examined. All AgP subjects had full periodontal and radiographic examination. The data recorded included socio-demographic and economic variables, oral hygiene and smoking habits, family history and parents' consanguinity. RESULTS: Most AgP patients were young females, had ≤12 years of education, lived in urban areas and brushed their teeth ≥ once daily. Risk indicators of AgP included: age > 35 years, female gender and positive family history. CONCLUSIONS: Risk indicators associated with AgP in this study population were: age > 35 years, female gender and positive family history of periodontal disease.

Is clipping the preferable technique to perform sympathicotomy? A retrospective study and review of the literature.

PURPOSE: Thoracoscopic sympathetic surgery is nowadays a broadly accepted technique in the treatment of primary hyperhidrosis as well as facial blushing. The objective of this study was to compare the two currently most commonly used methods for thoracic sympathicotomy: transection (ETS) and clipping (ETC.). METHODS: This is a retrospective study on a total of 63 patients, who underwent rib-oriented sympathicotomy, either by transection (n = 36, 57 %) or by clipping (n = 27, 43 %). Moreover, the up-to-date international literature is reviewed concerning which level(s) of the sympathetic trunk should be addressed, depending on the patients underlying condition. Furthermore, the highly controversial topic of reversibility of sympathetic clipping is debated. RESULTS: Our results confirm that clipping is at least as effective as transection of the sympathetic chain in the treatment of hyperhidrosis and facial blushing. Furthermore, the analysis of all larger studies on unclipping in humans shows a surprisingly high reported reversal rate between 48 and 77 %. CONCLUSIONS: Depending on the symptoms of the patient, different levels of the sympathetic chain should be addressed. When a higher rib level such as R2 is approached, which more likely will result in moderate to severe compensatory sweating, clipping should be preferred as it seems that this technique has indeed a potential for reversibility. As demonstrated, this method is at least as effective as an irreversible transection of the sympathetic chain.

Analysis of artificial intelligence in thyroid diagnostics and surgery: A scoping review.

BACKGROUND: Artificial Intelligence provides numerous applications in the healthcare sector. The main aim of this study is to evaluate the extent of the current application of artificial intelligence in thyroid diagnostics. METHODS: Our protocol was based on the Scoping Reviews extension of the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA-ScR). Information was gathered from PubMed, Cochrane, and EMBASE databases and Google Scholar. Eligible studies were published between 2017 and 2022. RESULTS: The search identified 133 records, after which 18 articles were included in the scoping review. All the publications were journal articles and discussed various ways that specialists in thyroid diagnostics and surgery have utilized artificial intelligence in their practice. CONCLUSIONS: The development and incorporation of Artificial Intelligence applications in thyroid diagnostics and surgery has been moderate yet promising. However, applications are currently inconsistent and further research is needed to delineate the true benefit and limitations in this field.

An analysis of virtual reality in abdominal surgery-A scoping review.

BACKGROUND: The integration of virtual reality (VR) in surgery has gained prominence as VR applications have increased in popularity. METHODS: A scoping review was undertaken, gathering the most relevant sources, utilising a detailed literature search of medical and academic databases including EMBASE, PubMed, Cochrane, IEEE, Google Scholar, and the Google search engine. RESULTS: Of the 18 articles included, 7 focused on VR in colon surgery, 5 addressed VR in pancreas surgery, and the remaining 6 concentrated on VR in liver surgery. All the articles concluded that VR has a promising future in abdominal surgery by facilitating precision, visualisation, and surgeon training. CONCLUSIONS: Adopting VR technology in abdominal surgery has the potential to improve preoperative planning, decrease perioperative anxiety among patients, and facilitate the training of surgeons, residents, and medical students. Additional supporting studies are necessary before VR can be widely implemented in surgical care delivery.

Association of vitamin D receptor gene polymorphisms with chronic and aggressive periodontitis in Jordanian patients.

Vitamin D acts through binding with vitamin D receptor (VDR) and is responsible for regulating bone metabolism and mineralization; it also suppresses the immune system. The aim of this study was to investigate if VDR gene polymorphisms are associated with chronic periodontitis (CP) and aggressive periodontitis (AgP) in a Jordanian population. A total of 99 patients with CP, 63 patients with AgP, and 126 controls were genotyped using PCR-restriction fragment length polymorphism (RFLP) for BsmI, ApaI, and TaqI single nucleotide polymorphisms (SNPs). The association was determined after correcting for confounding factors using multivariate logistic regression analysis. Estimation of haplotype frequencies was carried out using the EH program, and haplotypes were constructed using the phase 2.1 program. After correcting for confounding factors, multivariate logistic regression analysis revealed that inheritance of the BsmI bb genotype or the ApaI aa genotype was associated with increased risk of developing CP (OR = 2.4 and OR = 3.4, respectively) but with reduced risk of developing AgP (OR = 0.4 and OR = 0.3, respectively). This was further supported by association of the ba haplotype with CP but not with AgP. This study supports an association of VDR gene polymorphisms with CP and AgP in a Jordanian population; however, the pattern of association was different between the two diseases.

The development of machine learning in bariatric surgery.

Background: Machine learning (ML), is an approach to data analysis that makes the process of analytical model building automatic. The significance of ML stems from its potential to evaluate big data and achieve quicker and more accurate outcomes. ML has recently witnessed increased adoption in the medical domain. Bariatric surgery, otherwise referred to as weight loss surgery, reflects the series of procedures performed on people demonstrating obesity. This systematic scoping review aims to explore the development of ML in bariatric surgery. Methods: The study used the Preferred Reporting Items for Systematic and Meta-analyses for Scoping Review (PRISMA-ScR). A comprehensive literature search was performed of several databases including PubMed, Cochrane, and IEEE, and search engines namely Google Scholar. Eligible studies included journals published from 2016 to the current date. The PRESS checklist was used to evaluate the consistency demonstrated during the process. Results: A total of seventeen articles qualified for inclusion in the study. Out of the included studies, sixteen concentrated on the role of ML algorithms in prediction, while one addressed ML's diagnostic capacity. Most articles (n = 15) were journal publications, whereas the rest (n = 2) were papers from conference proceedings. Most included reports were from the United States (n = 6). Most studies addressed neural networks, with convolutional neural networks as the most prevalent. Also, the data type used in most articles (n = 13) was derived from hospital databases, with very few articles (n = 4) collecting original data via observation. Conclusions: This study indicates that ML has numerous benefits in bariatric surgery, however its current application is limited. The evidence suggests that bariatric surgeons can benefit from ML algorithms since they will facilitate the prediction and evaluation of patient outcomes. Also, ML approaches to enhance work processes by making data categorization and analysis easier. However, further large multicenter studies are required to validate results internally and externally as well as explore and address limitations of ML application in bariatric surgery.

Gastrointestinal Stromal Tumor (GIST): A Remarkable Case Report and Literature Review.

Gastrointestinal stromal tumor (GIST) makes up less than 1% of all gastrointestinal tumors, but it is the most common mesenchymal tumor of the digestive system. It is commonly found in the stomach and the small intestine and rarely seen in the colon and the esophagus. Additionally, sigmoid GIST is quite rare since colorectal GIST often occurs in the rectum. A total of 21 patients (including the study case) were looked at for this study, of which 14 (66.6%) were males and seven (33.3%) were females. We focused on GIST and conducted an online search and systematic analysis of all case presentations.

Corrigendum: The development of machine learning in bariatric surgery.

[This corrects the article DOI: 10.3389/fsurg.2023.1102711.].

Machine learning in pancreas surgery, what is new? literature review.

Background: Machine learning (ML) is an inquiry domain that aims to establish methodologies that leverage information to enhance performance of various applications. In the healthcare domain, the ML concept has gained prominence over the years. As a result, the adoption of ML algorithms has become expansive. The aim of this scoping review is to evaluate the application of ML in pancreatic surgery. Methods: We integrated the preferred reporting items for systematic reviews and meta-analyses for scoping reviews. Articles that contained relevant data specializing in ML in pancreas surgery were included. Results: A search of the following four databases PubMed, Cochrane, EMBASE, and IEEE and files adopted from Google and Google Scholar was 21. The main features of included studies revolved around the year of publication, the country, and the type of article. Additionally, all the included articles were published within January 2019 to May 2022. Conclusion: The integration of ML in pancreas surgery has gained much attention in previous years. The outcomes derived from this study indicate an extensive literature gap on the topic despite efforts by various researchers. Hence, future studies exploring how pancreas surgeons can apply different learning algorithms to perform essential practices may ultimately improve patient outcomes.

Robotic colorectal surgery: quality assessment of patient information available on the internet using webscraping.

The primary goal of this study is to assess current patient information available on the internet concerning robotic colorectal surgery. Acquiring this information will aid in patients understanding of robotic colorectal surgery. Data was acquired through a web-scraping algorithm. The algorithm used two Python packages: Beautiful Soup and Selenium. The long-chain keywords incorporated into Google, Bing and Yahoo search engines were 'Da Vinci Colon-Rectal Surgery', 'Colorectal Robotic Surgery' and 'Robotic Bowel Surgery'. 207 websites resulted, were sorted and evaluated according to the ensuring quality information for patients (EQIP) score. Of the 207 websites visited, 49 belonged to the subgroup of hospital websites (23.6%), 46 to medical centers (22.2%), 45 to practitioners (21.7%), 42 to health care systems (20,2%), 11 to news services (5.3%), 7 to web portals (3.3%), 5 to industry (2.4%), and 2 to patient groups (0.9%). Only 52 of the 207 websites received a high rating. The quality of available information on the internet concerning robotic colorectal surgery is low. The majority of information was inaccurate. Medical facilities involved in robotic colorectal surgery, robotic bowel surgery and related robotic procedures should develop websites with credible information to guide patient decisions.

Second Primary Cancer Among Patients With Papillary Thyroid Carcinoma Following the Chernobyl Disaster.

Importance: To our knowledge, there are no complete population-based studies of the risks of developing second malignant tumors after papillary thyroid carcinoma (PTC) in patients following the Chernobyl nuclear accident. Objective: To study the risk of second primary cancers in patients with PTC after the Chernobyl disaster. Design, Setting, and Participants: This was a retrospective cohort study conducted in the Republic of Belarus over a 31-year time frame evaluating patients with primary PTC and second malignant tumors. Personal data from the Belarussian Cancer Registry were used in the investigation, and only second primary cancers were included in the analysis. Patients were observed from January 1, 1990, to December 31, 2021, for the establishment of second primary malignant tumors. Main Outcomes and Measures: For analysis, synchronous and metachronous tumors were grouped into 1 group (second primary cancer group). If the patient had more than 2 cancers, they were observed until development of a second tumor and, subsequently, the development of a third tumor. The starting point for calculating the number of person-years was the date of thyroid cancer diagnosis. The end point for calculating the number of person-years was the date of diagnosis of the second primary malignant tumor, the date of death, the date of the last visit of the patient, or December 31, 2021 (the end the of study period). The incidence of a second primary malignant tumor with PTC was calculated for the study groups using standardized incidence ratios. Results: Of the 30 568 patients with a primary PTC included in this study, 2820 (9.2%) developed a second malignant tumor (2204 women and 616 men); the mean (SD) age of all patients at time of the primary cancer was 53.9 (12.6) years and at time of the secondary cancer was 61.5 (11.8) years. Overall, the standardized incidence ratio was statistically significant for all types of cancer (1.25; 95% CI, 1.21-1.30), including solid malignant tumors (1.20; 95% CI, 1.15-1.25) and all leukemias (1.61; 95% CI, 2.17-2.13). Cancers of the digestive system (466 cases [21.1%]), genital organs (376 cases [17.1%]), and breasts (603 cases [27.4%]) were the most prevalent second primary tumors in women following PTC. Second primary tumors of the gastrointestinal tract (146 cases [27.7%]), genitourinary system (139 cases [22.6%]), and urinary tract (139 cases [22.6%]) were the most prevalent in men. Urinary tract cancers (307 cases [10.9%]) and gastrointestinal tumors (612 cases [21.4%]) were the most prevalent second primary tumors overall. Conclusions and Relevance: This cohort study reports the increased incidence of solid secondary tumors in men and women over a 31-year time frame after the Chernobyl disaster. Moreover, there was a statistically significant increased risk of second tumors of the breast, colon, rectum, mesothelium, eye, adnexa, meninges, and adrenal glands as well as Kaposi sarcoma. These data might have an effect on the follow-up of this cohort of patients to detect secondary malignant tumors at an early stage.

Development and validation of a predictive model of the hospital cost associated with bariatric surgery.

Hospitals are facing difficulties in predicting, evaluating, and managing cost-affecting parameters in patient treatments. Inaccurate cost prediction leads to a deficit in operational revenue. This study aims to determine the ability of Machine Learning (ML) algorithms to predict the cost of care in bariatric and metabolic surgery and develop a predictive tool for improved cost analysis. 602 patients who underwent bariatric and metabolic surgery at Wetzikon hospital from 2013 to 2019 were included in the study. Multiple variables including patient factors, surgical factors, and post-operative complications were tested using a number of predictive modeling strategies. The study was registered under Req 2022-00659 and approved by an institutional review board. The cost was defined as the sum of all costs incurred during the hospital stay, expressed in CHF (Swiss Francs). The data was preprocessed and split into a training set (80%) and a test set (20%) to build and validate models. The final model was selected based on the mean absolute percentage error (MAPE). The Random Forest model was found to be the most accurate in predicting the overall cost of bariatric surgery with a mean absolute percentage error of 12.7. The study provides evidence that the Random Forest model could be used by hospitals to help with financial calculations and cost-efficient operation. However, further research is needed to improve its accuracy. This study serves as a proof of principle for an efficient ML-based prediction tool to be tested on multi-center data in future phases of the study.

The Development of Artificial Intelligence in Hernia Surgery: A Scoping Review.

Background: Artificial intelligence simulates human intelligence in machines that have undergone programming to make them think like human beings and imitate their activities. Artificial intelligence has dominated the medical sector to perform various patient diagnosis activities and improve communication between professionals and patients. The main goal of this study is to perform a scoping review to evaluate the development of artificial intelligence in all forms of hernia surgery except the diaphragm and upside-down hernia. Methods: The study used the Preferred Reporting Items for Systematic and Meta-analyses for Scoping Review (PRISMA-ScR) to guide the structuring of the manuscript and fulfill all the requirements of every subheading. The sources used to gather data are the PubMed, Cochrane, and EMBASE databases, IEEE and Google and Google Scholar search engines. AMSTAR tool is the most appropriate for assessing the methodological quality of the included studies. Results: The study exclusively included twenty articles, whereby seven focused on artificial intelligence in inguinal hernia surgery, six focused on abdominal hernia surgery, five on incisional hernia surgery, and two on AI in medical imaging and robotics in hernia surgery. Conclusion: The outcomes of this study reveal a significant literature gap on artificial intelligence in hernia surgery. The results also indicate that studies focus on inguinal hernia surgery more than any other types of hernia surgery since the articles addressing the topic are more. The study implies that more research is necessary for the field to develop and enjoy the benefits associated with AI. Thus, this situation will allow the integration of AI in activities like medical imaging and surgeon training.