A Comparative Analysis of Deep Learning Convolutional Neural Network Architectures for Fault Diagnosis of Broken Rotor Bars in Induction Motors.

Induction machines (IMs) play a critical role in various industrial processes but are susceptible to degenerative failures, such as broken rotor bars. Effective diagnostic techniques are essential in addressing these issues. In this study, we propose the utilization of convolutional neural networks (CNNs) for detection of broken rotor bars. To accomplish this, we generated a dataset comprising current samples versus angular position using finite element method magnetics (FEMM) software for a squirrel-cage rotor with 28 bars, including scenarios with 0 to 6 broken bars at every possible relative position. The dataset consists of a total of 16,050 samples per motor. We evaluated the performance of six different CNN architectures, namely Inception V4, NasNETMobile, ResNET152, SeNET154, VGG16, and VGG19. Our automatic classification system demonstrated an impressive 99% accuracy in detecting broken rotor bars, with VGG19 performing exceptionally well. Specifically, VGG19 exhibited high accuracy, precision, recall, and F1-Score, with values approaching 0.994 and 0.998. Notably, VGG19 exhibited crucial activations in its feature maps, particularly after domain-specific training, highlighting its effectiveness in fault detection. Comparing CNN architectures assists in selecting the most suitable one for this application based on processing time, effectiveness, and training losses. This research suggests that deep learning can detect broken bars in induction machines with accuracy comparable to that of traditional methods by analyzing current signals using CNNs.

Small Cell Carcinoma of the Vagina: First Systematic Review of Case Reports and Proposal of a Management Algorithm.

OBJECTIVES: Small cell carcinoma of the vagina (SmCCV) is an extremely rare disease. Evidence-based data and specific guidelines are lacking. We conducted the first systematic review of case reports to provide the most overall picture of SmCCV. MATERIALS AND METHODS: Literature search in PubMed and Scopus was performed using the terms "small cell carcinoma" and "vagina." English-language case reports of primary SmCCV up to January 2022 were included. RESULTS: Twenty-nine articles describing 44 cases met our inclusion criteria. We report a new case of our hospital. The global median overall survival (mOS) was 12.00 months (95% CI = 9.31-14.69). The mOS was not reached for stage I, and it was 12.00, 12.00, 9.00, and 8.00 months for stages II, III, IVA, and IVB, respectively (statistically significant differences between stage I and stages II, III, or IVA [log rank p = .003-.017]). Thirty-five cases received local treatments (77.8%). The mOS of patients treated with surgery ± complementary chemotherapy, radiotherapy ± complementary chemotherapy, chemoradiation ± complementary chemotherapy, and surgery + radiotherapy ± complementary chemotherapy were 11.00, 12.00, 17.00, and 29.00 months, respectively. The use of adjuvant or neoadjuvant chemotherapy (64.5%, mostly platinum + etoposide) showed longer mOS (77.00 vs 15.00 months). Four of 5 tested cases presented human papillomavirus infection, 3 of them presenting type 18. CONCLUSIONS: Small cell carcinoma of the vagina shows dismal prognosis. Multimodal local management plus complementary chemotherapy seems to achieve better outcomes. Human papillomavirus could be related to the development of SmCCV. A diagnostic-therapeutic algorithm is proposed.

Prognostic Role of Neutrophil, Monocyte and Platelet to Lymphocyte Ratios in Advanced Ovarian Cancer According to the Time of Debulking Surgery.

Despite a multimodal radical treatment, mortality of advanced epithelial ovarian cancer (AEOC) remains high. Host-related factors, such as systemic inflammatory response and its interplay with the immune system, remain underexplored. We hypothesized that the prognostic impact of this response could vary between patients undergoing primary debulking surgery (PDS) and those undergoing interval debulking surgery (IDS). Therefore, we evaluated the outcomes of two surgical groups of newly diagnosed AEOC patients according to the neutrophil, monocyte and platelet to lymphocyte ratios (NLR, MLR, PLR), taking median ratio values as cutoffs. In the PDS group (n = 61), low NLR and PLR subgroups showed significantly better overall survival (not reached (NR) vs. 72.7 months, 95% confidence interval [CI]: 40.9-95.2, p = 0.019; and NR vs. 56.1 months, 95% CI: 40.9-95.2, p = 0.004, respectively) than those with high values. Similar results were observed in progression free survival. NLR and PLR-high values resulted in negative prognostic factors, adjusting for residual disease, BRCA1/2 status and stage (HR 2.48, 95% CI: 1.03-5.99, p = 0.043, and HR 2.91, 95% CI: 1.11-7.64, p = 0.03, respectively). In the IDS group (n = 85), ratios were not significant prognostic factors. We conclude that NLR and PLR may have prognostic value in the PDS setting, but none in IDS, suggesting that time of surgery can modulate the prognostic impact of baseline complete blood count (CBC).

Analytical Model of Eccentric Induction Machines Using the Conformal Winding Tensor Approach.

Induction machines (IMs) are a critical component of many industrial processes, and their failure can cause large economic losses. Condition-based maintenance systems (CBMs) that are capable of detecting their failures at an incipient stage can reduce these risks by continuously monitoring the IMs' condition. The development and reliable operations of CBMs systems require rapid modeling of the faulty IM. Due to the fault-induced IM asymmetries, these models are much more complex than those used for a healthy IM. In particular, a mixed eccentricity fault (static and dynamic), which can degenerate into rubbing and destruction of the rotor, produces a non-uniform IM air gap that is different for each rotor position, which makes its very difficult to calculate the IM's inductance matrix. In this work, a new analytical model of an eccentric IM is presented. It is based on the winding tensor approach, which allows a clear separation between the air gap and winding-related faults. Contrary to previous approaches, where complex expressions have been developed for obtaining mutual inductances between conductors and windings of an eccentric IM, a conformal transformation is proposed in this work, which allows using the simple inductance expressions of a healthy IM. This novel conformal winding tensor approach (CWFA) is theoretically explained and validated with the diagnosis of two commercial IMs with a mixed eccentricity fault.

A Review of Techniques Used for Induction Machine Fault Modelling.

Over the years, induction machines (IMs) have become key components in industry applications as mechanical power sources (working as motors) as well as electrical power sources (working as generators). Unexpected breakdowns in these components can lead to unscheduled down time and consequently to large economic losses. As breakdown of IMs for failure study is not economically feasible, several IM computer models under faulty conditions have been developed to investigate the characteristics of faulty machines and have allowed reducing the number of destructive tests. This paper provides a review of the available techniques for faulty IMs modelling. These models can be categorised as models based on electrical circuits, on magnetic circuits, models based on numerical methods and the recently proposed in the technical literature hybrid models or models based on finite element method (FEM) analytical techniques. A general description of each type of model is given with its main benefits and drawbacks in terms of accuracy, running times and ability to reproduce a given fault.

Low-Computational-Cost Hybrid FEM-Analytical Induction Machine Model for the Diagnosis of Rotor Eccentricity, Based on Sparse Identification Techniques and Trigonometric Interpolation.

Since it is not efficient to physically study many machine failures, models of faulty induction machines (IMs) have attracted a rising interest. These models must be accurate enough to include fault effects and must be computed with relatively low resources to reproduce different fault scenarios. Moreover, they should run in real time to develop online condition-monitoring (CM) systems. Hybrid finite element method (FEM)-analytical models have been recently proposed for fault diagnosis purposes since they keep good accuracy, which is widely accepted, and they can run in real-time simulators. However, these models still require the full simulation of the FEM model to compute the parameters of the analytical model for each faulty scenario with its corresponding computing needs. To address these drawbacks (large computing power and memory resources requirements) this paper proposes sparse identification techniques in combination with the trigonometric interpolation polynomial for the computation of IM model parameters. The proposed model keeps accuracy similar to a FEM model at a much lower computational effort, which could contribute to the development and to the testing of condition-monitoring systems. This approach has been applied to develop an IM model under static eccentricity conditions, but this may extend to other fault types.

Analytical Model of Induction Machines with Multiple Cage Faults Using the Winding Tensor Approach.

Induction machines (IMs) are one of the main sources of mechanical power in many industrial processes, especially squirrel cage IMs (SCIMs), due to their robustness and reliability. Their sudden stoppage due to undetected faults may cause costly production breakdowns. One of the most frequent types of faults are cage faults (bar and end ring segment breakages), especially in motors that directly drive high-inertia loads (such as fans), in motors with frequent starts and stops, and in case of poorly manufactured cage windings. A continuous monitoring of IMs is needed to reduce this risk, integrated in plant-wide condition based maintenance (CBM) systems. Diverse diagnostic techniques have been proposed in the technical literature, either data-based, detecting fault-characteristic perturbations in the data collected from the IM, and model-based, observing the differences between the data collected from the actual IM and from its digital twin model. In both cases, fast and accurate IM models are needed to develop and optimize the fault diagnosis techniques. On the one hand, the finite elements approach can provide highly accurate models, but its computational cost and processing requirements are very high to be used in on-line fault diagnostic systems. On the other hand, analytical models can be much faster, but they can be very complex in case of highly asymmetrical machines, such as IMs with multiple cage faults. In this work, a new method is proposed for the analytical modelling of IMs with asymmetrical cage windings using a tensor based approach, which greatly reduces this complexity by applying routine tensor algebra to obtain the parameters of the faulty IM model from the healthy one. This winding tensor approach is explained theoretically and validated with the diagnosis of a commercial IM with multiple cage faults.

Fault Diagnosis in the Slip-Frequency Plane of Induction Machines Working in Time-Varying Conditions.

Motor current signature analysis (MCSA) is a fault diagnosis method for induction machines (IMs) that has attracted wide industrial interest in recent years. It is based on the detection of the characteristic fault signatures that arise in the current spectrum of a faulty induction machine. Unfortunately, the MCSA method in its basic formulation can only be applied in steady state functioning. Nevertheless, every day increases the importance of inductions machines in applications such as wind generation, electric vehicles, or automated processes in which the machine works most of time under transient conditions. For these cases, new diagnostic methodologies have been proposed, based on the use of advanced time-frequency transforms-as, for example, the continuous wavelet transform, the Wigner Ville distribution, or the analytic function based on the Hilbert transform-which enables to track the fault components evolution along time. All these transforms have high computational costs and, furthermore, generate as results complex spectrograms, which require to be interpreted for qualified technical staff. This paper introduces a new methodology for the diagnosis of faults of IM working in transient conditions, which, unlike the methods developed up to today, analyzes the current signal in the slip-instantaneous frequency plane (s-IF), instead of the time-frequency (t-f) plane. It is shown that, in the s-IF plane, the fault components follow patterns that that are simple and unique for each type of fault, and thus does not depend on the way in which load and speed vary during the transient functioning; this characteristic makes the diagnostic task easier and more reliable. This work introduces a general scheme for the IMs diagnostic under transient conditions, through the analysis of the stator current in the s-IF plane. Another contribution of this paper is the introduction of the specific s-IF patterns associated with three different types of faults (rotor asymmetry fault, mixed eccentricity fault, and single-point bearing defects) that are theoretically justified and experimentally tested. As the calculation of the IF of the fault component is a key issue of the proposed diagnostic method, this paper also includes a comparative analysis of three different mathematical tools for calculating the IF, which are compared not only theoretically but also experimentally, comparing their performance when are applied to the tested diagnostic signals.

Winding Tensor Approach for the Analytical Computation of the Inductance Matrix in Eccentric Induction Machines.

Induction machines (IMs) are critical components of many industrial processes, what justifies the use of condition-based maintenance (CBM) systems for detecting their faults at an early stage, in order to avoid costly breakdowns of production lines. The development of CBM systems for IMs relies on the use of fast models that can accurately simulate the machine in faulty conditions. In particular, IM models must be able to reproduce the characteristic harmonics that the IM faults impress in the spatial waves of the air gap magneto-motive force (MMF), due to the complex interactions between spatial and time harmonics. A common type of fault is the eccentricity of the rotor core, which provokes an unbalanced magnetic pull, and can lead to destructive rotor-stator rub. Models developed using the finite element method (FEM) can achieve the required accuracy, but their high computational costs hinder their use in online CBM systems. Analytical models are much faster, but they need an inductance matrix that takes into account the asymmetries generated by the eccentricity fault. Building the inductance matrix for eccentric IMs using traditional techniques, such as the winding function approach (WFA), is a highly complex task, because these functions depend on the combined effect of the winding layout and of the air gap asymmetry. In this paper, a novel method for the fast and simple computation of the inductance matrix for eccentric IMs is presented, which decouples the influence of the air gap asymmetry and of the winding configuration using two independent tensors. It is based on the construction of a primitive inductance tensor, which formulates the eccentricity fault using single conductors as the simplest reference frame; and a winding tensor that converts it into the inductance matrix of a particular machine, taking into account the configuration of the windings. The proposed approach applies routine procedures from tensor algebra for performing such transformation in a simple way. It is theoretically explained and experimentally validated with a commercial induction motor with a mixed eccentricity fault.

Chemotherapy and PARP inhibitors in heavily pretreated BRCA1/2 mutation ovarian cancer (BMOC) patients.

OBJECTIVES: The hallmarks of germline(g) and/or somatic(s) BRCA1/2 mutation ovarian cancer (BMOC) patients are increased sensitivity to platinum-based chemotherapy (PCT) and PARP inhibitors (PARPi). There is little information on the effectiveness of chemotherapy in heavily pretreated (≥3 CT lines) g/sBMOC patients. METHODS: g/sBMOC patients who received CT from 2006 to 2016 at 4 cancer centers in Spain were selected. Overall survival (OS) and time to progression (TTP) were calculated with Kaplan Meier and Cox models. RESULTS: 135 g/sBMOC patients were identified (6% sBRCA1/2 mutations). The median number of chemotherapy lines was 2 (1-7). The 6-years OS rate was 69.4% and 71% in BRCA1 or BRCA2 mutation carriers (p = 0.98). A total of 57 (42%) patients had ≥3 CT lines (3-7), which encompassed a total of 155 treatments. The median overall TTP across all treatment lines beyond 2nd line was 10.2 months (CI 95% 8.4-11.9 months). In the platinum-sensitive setting, TTP was improved with PCT plus PARPi (17.1 m), PCT (12.6 m) or PARPi (12.4 m) versus non-PCT (4.9 m; p < 0.001 all comparisons). In the platinum-resistant setting, these differences in TTP were not statistically significant. A multivariate model confirmed that primary platinum-free interval (PFI) > 12 months and exposure to PCT and PARPi associated with improved outcomes. PARPi exposure did not compromise benefit of subsequent CT beyond 2nd relapse. CONCLUSIONS: Heavily pretreated g/sBMOC demonstrated CT sensitivity, including for non-PCT choices. Primary platinum-free interval (PFI) >12 months and exposure to both platinum-based chemotherapy and PARPi associate with improved prognosis in heavily pretreated g/sBMOC patients.

A new species of Stethelmis Hinton (Coleoptera: Elmidae) from Argentina and description of its larva.

A new species of Stethelmis, S. shepardi sp. nov., is described for Patagonia, Argentina from adults of both sexes. A full description and illustrations of both the adult and the larva of the new species are provided with comments on its habitat and distribution. Adults of the new species are compared with those of S. kaszabi (Hinton 1970) and S. chilensis (Hinton 1945). The larva of S. shepardi is compared with that of S. kaszabi, the other Stethelmis larva described. We also describe and illustrate for the first time the male genitalia of S. kaszabi. A key to the known species of Stethelmis is also included.

Cost-Effective Reduced Envelope of the Stator Current via Synchronous Sampling for the Diagnosis of Rotor Asymmetries in Induction Machines Working at Very Low Slip.

Fault diagnosis of rotor asymmetries of IM using the stator current relies on the detection of the characteristic signatures of the fault harmonics in the current spectrum. In some scenarios, such as large induction machines running at a very low slip, or unloaded machines tested offline, this technique may fail. In these scenarios, the fault harmonics are very close to the frequency of the fundamental component, and have a low amplitude, so that they may remain undetected, buried under the fundamental's leakage, until the damage is severe. To avoid false positives, a proven approach is to search for the fault harmonics in the current envelope, instead of the current itself, because in this case the spectrum is free from the leakage of the fundamental. Besides, the fault harmonics appear at a very low frequency. Nevertheless, building the current spectrum is costly in terms of computing complexity, as in the case of the Hilbert transform, or hardware resources, as in the need for simultaneously sampling three stator currents in the case of the EPVA. In this work, a novel method is proposed to avoid this problem. It is based on sampling a phase current just twice per current cycle, with a fixed delay with respect to its zero crossings. It is shown that the spectrum of this reduced set of current samples contains the same fault harmonics as the spectrum of the full-length current envelope, despite using a minimal amount of computing resources. The proposed approach is cost-effective, because the computational requirements for building the current envelope are reduced to less than 1 % of those required by other conventional methods, in terms of storage and computing time. In this way, it can be implemented with low-cost embedded devices for on-line fault diagnosis. The proposed approach is introduced theoretically and validated experimentally, using a commercial induction motor with a broken bar under different load and supply conditions. Besides, the proposed approach has been implemented on a low-cost embedded device, which can be accessed on-line for remote fault diagnosis.

Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window.

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current's spectrogram with a significant reduction of the required computational resources.

Partial Inductance Model of Induction Machines for Fault Diagnosis.

The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models used for healthy machines, because one of the effect of the faults is to change the winding configurations (broken bar faults, rotor asymmetries, and inter-turn short circuits) or the magnetic circuit (eccentricity and bearing faults). This produces a change of the self and mutual phase inductances, which induces in the stator currents the characteristic fault harmonics used to detect and to quantify the fault. The development of a machine model that can reflect these changes is a challenging task, which is addressed in this work with a novel approach, based on the concept of partial inductances. Instead of developing the machine model based on the phases' coils, it is developed using the partial inductance of a single conductor, obtained through the magnetic vector potential, and combining the partial inductances of all the conductors with a fast Fourier transform for obtaining the phases' inductances. The proposed method is validated using a commercial induction motor with forced broken bars.

Translational Research Opportunities Regarding Homologous Recombination in Ovarian Cancer.

Homologous recombination (HR) is a DNA repair pathway that is deficient in 50% of high-grade serous ovarian carcinomas (HGSOC). Deficient HR (DHR) constitutes a therapeutic opportunity for these patients, thanks to poly (ADP-ribose) polymerases (PARP) inhibitors (PARPi; olaparib, niraparib, and rucaparib are already commercialized). Although initially, PARPi were developed for patients with BRCA1/2 mutations, robust clinical data have shown their benefit in a broader population without DHR. This breakthrough in daily practice has raised several questions that necessitate further research: How can populations that will most benefit from PARPi be selected? At which stage of ovarian cancer should PARPi be used? Which strategies are reasonable to overcome PARPi resistance? In this paper, we present a summary of the literature and discuss the present clinical research involving PARPi (after reviewing ClinicalTrials.gov) from a translational perspective. Research into the functional biomarkers of DHR and clinical trials testing PARPi benefits as first-line setting or rechallenge are currently ongoing. Additionally, in the clinical setting, only secondary restoring mutations of BRCA1/2 have been identified as events inducing resistance to PARPi. The clinical frequency of this and other mechanisms that have been described in preclinics is unknown. It is of great importance to study mechanisms of resistance to PARPi to guide the clinical development of drug combinations.

Neoliberalism and Austerity in Spain, Portugal and South Africa: The Revolution of Older Persons.

In Portugal, Spain, and South Africa, there has been a noted anti-neoliberal resistance, marked by the significant participation of the older generation in protest movements. Changing demographics, the global financial crisis, unemployment, poverty, and the reliance of the family nucleus on the pensioner, coupled with neoliberal and austerity-based reductions to welfare programs, pensions, health, and social care, has caused the "silver revolution." As a population group that is often considered to be less politically active and robust members of society, such resistance is a noteworthy moment in society that needs to be considered and responded to.

Preoperative Assessment of Myometrial Invasion in Endometrial Cancer by 3D Ultrasound and Diffusion-Weighted Magnetic Resonance Imaging: A Comparative Study.

OBJECTIVE: The prognosis of endometrial cancer depends on the correct surgical staging. In early stages, 18% to 30% rate of positive lymph nodes is reported with a myometrial invasion of 50% or more. According to this, patients with International Federation of Gynecology and Obstetrics stage Ib would benefit from staging lymphadenectomy. Therefore, it is important to classify these patients preoperatively to plan the surgery. In the recent years, 3-dimensional (3D) ultrasound and diffusion-weighted magnetic resonance imaging (DW-MRI) have been incorporated in the preoperative management of these patients. The aim of this study was to assess the usefulness of 3D ultrasound and DW-MRI as predictor of myometrial invasion in endometrial cancer. MATERIAL AND METHODS: We retrospectively compared the assessment of myometrial invasion by 3D ultrasound and DW-MRI with final pathologic evaluation on hysterectomy specimens, in 98 patients diagnosed of early-stage endometrial cancer, who underwent surgery at the Hospital Clinic of Barcelona between 2012 and 2015. RESULTS: Evaluation of the depth of myometrial invasion with 3D ultrasound had a sensitivity, specificity, and accuracy of 77%, 83% and 81%, respectively. Evaluation of the depth of myometrial invasion with DW-MRI had a sensitivity, specificity, and accuracy of 69%, 86%, and 81%, respectively. Association of both techniques improved all the values, showing a sensitivity, specificity, and accuracy of 87%, 93%, and 91%, respectively. In both 3D ultrasound and DW-MRI, the presence of leiomyomas was the first detectable cause of false negative (3% and 4%, respectively) and false-positive (3% and 1%, respectively). CONCLUSIONS: We conclude that the implementation of the 2 studies in early-stage endometrial cancer provides low false-negatives and false-positives rates. In cases of patients with leiomyomas, adenomiosis, or intrauterine fluid collection, definitive evaluation of myometrial invasion could be better deferred to intraoperative biopsy in an attempt to reduce false-negatives and false-positives rates.

Is sphere assay useful for the identification of cancer initiating cells of the ovary?

OBJECTIVE: Current evidence suggests that the presence of tumor-initiating cells (TICs) in epithelial ovarian cancer (EOC) has a role in chemoresistance and relapse. Surface markers such as CD44(+)/CD24(-), CD117(+), and CD133(+) expression have been reported as potential markers for TICs related to ovarian cancer and tumorigenic cell lines. In this study, we have investigated if spheroid forms are TIC specific or whether they can also be produced by somatic stem cells from healthy tissue in vitro. In addition, we also investigated the specificity of surface markers to identify TICs from papillary serous EOC patients. METHODS: Cells were obtained from fresh tumors from 10 chemotherapy-naive patients with EOC, and cells from ovarian and tubal epithelium were obtained from 5 healthy menopausal women undergoing surgery for benign pathology and cultured in standard and in selective medium. Cells forming nonadherent spheroids were considered TICs, and the adherent cells were considered as non-TIC-like. Percentages of CD24(+), CD44(+), CD117(+), CD133(+), and vascular endothelial growth factor receptor (VEGF-R)(+) cell surface markers were analyzed by flow cytometry. RESULTS: Four of 10 EOC cell tissues were excluded from the study. Tumor cells cultured in selective medium developed spheroid forms after 1 to 7 weeks in 5 of 6 EOC patients. No spheroid forms were observed in cultures of cells from healthy women. Unlike previously published data, low levels of CD24(+), CD44(+), CD117(+), and VEGF-R(+) expression were observed in spheroid cells, whereas expression of CD133(+) was moderate but higher in adherent cells from papillary serous EOC cells in comparison with adherent cells from controls. CONCLUSIONS: Papillary serous EOC contains TICs that form spheroids with low expression of CD44(+), CD24(+), CD117(+) and VEGF-R(+). Further research is required to find specific surface markers to identify papillary serous TICs.

Intestinal surgery performed by gynecologists.

INTRODUCTION: Our objective was to compare the feasibility and safety of surgical procedures to treat gynecological pathologies with intestinal involvement performed by skilled gynecological surgeons and by a multidisciplinary team of gynecologists plus colorectal surgeons. MATERIAL AND METHODS: We performed a comparative, observational, prospective study at a tertiary referral center. The population included all women undergoing bowel surgery for gynecological pathologies over a 3-year period. Cases were analyzed by the specialty of the main surgeon performing the intestinal procedure. The main outcome measures were surgical procedure characteristics and postoperative outcomes and complications. RESULTS: A total of 65 women were included. Surgery was exclusively performed by a subspecialized gynecologist in 30.8% of the women, and undertaken by a multidisciplinary team (colorectal surgeons and gynecologists) in 69.2%. The main demographic and clinical characteristics were comparable in both groups. Main indications for bowel resection in gynecological surgery were advanced ovarian cancer and deep infiltrating endometriosis. In addition to the standard gynecological surgical procedures, a total of 135 intestinal segments were resected, with sigmoid colon the most frequent intestinal segment resected in both groups (53% in the gynecologist group and in 60% in the multidisciplinary group). No significant differences were observed between the two groups in the distribution and frequency of surgical techniques used, rate of complications, mean hospitalization time or frequency of re-intervention. CONCLUSION: Skilled gynecological surgeons appear to be equally good at handling common intestinal problems as a team of gynecologist and colorectal surgeons.