Descriptive Anatomy of the Porcine Ventral Abdominal Wall as a Basis for Training Ventral Hernia Repair Techniques.

Background: In recent times there has been a surge in innovative techniques concerning complex abdominal wall surgery. The availability of simulation models for comprehensive training and skill set development remains limited. Methods: Cadaveric dissections of the porcine abdominal wall were conducted to assess the suitability of anesthetized porcine models for training in both minimally invasive and open surgical procedures. Results: The panniculus carnosus, a typical muscular layer in mammals, is the outermost layer covering the anterolateral abdominal wall. Beneath it, there are four main pairs of abdominal wall muscles, mirroring the human anatomy. The rectus abdominis muscle runs straight along the linea alba and is surrounded by the rectus sheath, which is formed by the fusion of the lateral abdominal wall muscles and differs along the different regions of abdominal wall. The orientation of the muscle fibers in the lateral abdominal wall muscles, i.e., musculus obliquus externus, internus and transversus, is comparable to human anatomy. Although the transition lines between their muscular and aponeurotic part differ to some extent. Relevant for the adoption of surgical techniques, the transversus abdominis muscle is well-developed and resembles a bell curve shape as it transitions from its muscular to aponeurotic part. Conclusion: Despite minor differences in abdominal wall anatomy between pigs and humans, the porcine model provides a high level of fidelity in terms of both anatomical features and the development of skill sets relevant to hernia surgery.

Development and validation of metrics for a new RAPN training model.

Robot-assisted partial nephrectomy (RAPN) is a complex and index procedure that urologists need to learn how to perform safely. No validated performance metrics specifically developed for a RAPN training model (TM) exist. A Core Metrics Group specifically adapted human RAPN metrics to be used in a newly developed RAPN TM, explicitly defining phases, steps, errors, and critical errors. A modified Delphi meeting concurred on the face and content validation of the new metrics. One hundred percent consensus was achieved by the Delphi panel on 8 Phases, 32 Steps, 136 Errors and 64 Critical Errors. Two trained assessors evaluated recorded video performances of novice and expert RAPN surgeons executing an emulated RAPN in the newly developed TM. There were no differences in procedure Steps completed by the two groups. Experienced RAPN surgeons made 34% fewer Total Errors than the Novice group. Performance score for both groups was divided at the median score using Total Error scores, into HiError and LoError subgroups. The LowErrs Expert RAPN surgeons group made 118% fewer Total Errors than the Novice HiErrs group. Furthermore, the LowErrs Expert RAPN surgeons made 77% fewer Total Errors than the HiErrs Expert RAPN surgeons. These results established construct and discriminative validity of the metrics. The authors described a novel RAPN TM and its associated performance metrics with evidence supporting their face, content, construct, and discriminative validation. This report and evidence support the implementation of a simulation-based proficiency-based progression (PBP) training program for RAPN.

Enhancing the Microneurosurgical Training: Development of the Folded Placenta Model for Simulation of the Deep Operative Field Challenges of Cranial Procedures.

BACKGROUND AND OBJECTIVE: Neurosurgery relies heavily on advanced manual skills, necessitating effective training models for skill development. While various models have been utilized, the human placenta has emerged as a promising candidate for microneurosurgical training due to its anatomical similarities with cerebral vasculature. However, existing placenta models have primarily focused on simulating superficial procedures, often neglecting the complexities encountered in deep operative fields during cranial surgeries. METHODS: This study obtained ethical approval and implemented a modified placenta model to address the limitations of existing training models. The key modification involved folding the placenta and placing it within a rigid container, closely mimicking the structural challenges of cranial procedures. The placenta preparation followed a standardized protocol, including the use of specialized equipment for documentation. RESULTS: The primary feature of the modified model is the folded placenta within the rigid container, which replicates cranial anatomy. This innovative approach enables trainees to engage in a comprehensive range of microsurgical exercises, encompassing vessel dissection, aneurysm clipping, tumor resection, and more. The model successfully mirrors the complexities of real cranial procedures, providing a realistic training experience. CONCLUSIONS: The presented modified placenta model serves as an effective tool for simulating the conditions encountered in deep cranial surgeries. By accurately replicating the challenges of deep operative fields, the model significantly enhances the training of neurosurgical residents. It successfully prepares trainees to navigate the intricacies and difficulties inherent in real cranial surgeries, thus contributing to improved surgical skills and readiness for neurosurgical practice.

Promoting the process of determining brain death through standardized training.

Objective: This study aims to explore the training mode for brain death determination to ensure the quality of subsequent brain death determination. Methods: A four-skill and four-step (FFT) training model was adopted, which included a clinical neurological examination, an electroencephalogram (EEG) examination, a short-latency somatosensory evoked potential (SLSEP) examination, and a transcranial Doppler (TCD) examination. Each skill is divided into four steps: multimedia theory teaching, bedside demonstration, one-on-one real or dummy simulation training, and assessment. The authors analyzed the training results of 1,577 professional and technical personnel who participated in the FFT training model from 2013 to 2020 (25 sessions), including error rate analysis of the written examination, knowledge gap analysis, and influencing factors analysis. Results: The total error rates for all four written examination topics were < 5%, at 4.13% for SLSEP, 4.11% for EEG, 3.71% for TCD, and 3.65% for clinical evaluation. The knowledge gap analysis of the four-skill test papers suggested that the trainees had different knowledge gaps. Based on the univariate analysis and the multiple linear regression analysis, among the six factors, specialty categories, professional and technical titles, and hospital level were the independent influencing factors of answer errors (p < 0.01). Conclusion: The FFT model is suitable for brain death (BD) determination training in China; however, the authors should pay attention to the professional characteristics of participants, strengthen the knowledge gap training, and strive to narrow the difference in training quality.

RM-GPT: Enhance the comprehensive generative ability of molecular GPT model via LocalRNN and RealFormer.

Due to the surging of cost, artificial intelligence-assisted de novo drug design has supplanted conventional methods and become an emerging option for drug discovery. Although there have arisen many successful examples of applying generative models to the molecular field, these methods struggle to deal with conditional generation that meet chemists' practical requirements which ask for a controllable process to generate new molecules or optimize basic molecules with appointed conditions. To address this problem, a Recurrent Molecular-Generative Pretrained Transformer model is proposed, supplemented by LocalRNN and Residual Attention Layer Transformer, referred to as RM-GPT. RM-GPT rebuilds GPT model's architecture by incorporating LocalRNN and Residual Attention Layer Transformer so that it is able to extract local information and build connectivity between attention blocks. The incorporation of Transformer in these two modules enables leveraging the parallel computing advantages of multi-head attention mechanisms while extracting local structural information effectively. Through exploring and learning in a large chemical space, RM-GPT absorbs the ability to generate drug-like molecules with conditions in demand, such as desired properties and scaffolds, precisely and stably. RM-GPT achieved better results than SOTA methods on conditional generation.

[A research on depression recognition based on voice pre-training model].

For the increasing number of patients with depression, this paper proposes an artificial intelligence method to effectively identify depression through voice signals, with the aim of improving the efficiency of diagnosis and treatment. Firstly, a pre-training model called wav2vec 2.0 is fine-tuned to encode and contextualize the speech, thereby obtaining high-quality voice features. This model is applied to the publicly available dataset - the distress analysis interview corpus-wizard of OZ (DAIC-WOZ). The results demonstrate a precision rate of 93.96%, a recall rate of 94.87%, and an F1 score of 94.41% for the binary classification task of depression recognition, resulting in an overall classification accuracy of 96.48%. For the four-class classification task evaluating the severity of depression, the precision rates are all above 92.59%, the recall rates are all above 92.89%, the F1 scores are all above 93.12%, and the overall classification accuracy is 94.80%. The research findings indicate that the proposed method effectively enhances classification accuracy in scenarios with limited data, exhibiting strong performance in depression identification and severity evaluation. In the future, this method has the potential to serve as a valuable supportive tool for depression diagnosis.

iSUMO-RsFPN: A predictor for identifying lysine SUMOylation sites based on multi-features and feature pyramid networks.

SUMOylation is a protein post-translational modification that plays an essential role in cellular functions. For predicting SUMO sites, numerous researchers have proposed advanced methods based on ordinary machine learning algorithms. These reported methods have shown excellent predictive performance, but there is room for improvement. In this study, we constructed a novel deep neural network Residual Pyramid Network (RsFPN), and developed an ensemble deep learning predictor called iSUMO-RsFPN. Initially, three feature extraction methods were employed to extract features from samples. Following this, weak classifiers were trained based on RsFPN for each feature type. Ultimately, the weak classifiers were integrated to construct the final classifier. Moreover, the predictor underwent systematically testing on an independent test dataset, where the results demonstrated a significant improvement over the existing state-of-the-art predictors. The code of iSUMO-RsFPN is free and available at https://github.com/454170054/iSUMO-RsFPN.

Participatory training evaluation: Steps from the Center for Native American Health Native-CHART symposium.

This paper presents a case example of the Native-CHART Training Evaluation and describes the process of planning and administering a paper evaluation during the Native-CHART symposium in November 2019 led by the Center for Native American Health (CNAH) and an external evaluator. Training evaluation methodologies and the data collection instrument were grounded in the Health Belief Model (HBM) where health-related chronic disease and risk factor knowledge translates to perceived susceptibility, benefits, barriers, and self-efficacy. Kirkpatrick's Four-level Training Evaluation Model explored learning, reaction, behaviors, and results. The evaluation aims centered around the following questions: 1)Who attended the symposium, and why did they attend? 2)What knowledge did participants gain at the symposium? 3)Will attendees change their behaviors as a result of attending the symposium? 4) What parts of the symposium were most valuable? And 5) How can the symposium be improved? Data collected at the symposium answered these questions. After the Native-CHART symposium, CNAH staff and the external evaluator met to reflect on the steps necessary to plan and implement a participatory training evaluation. From these discussions, eight steps emerged. This paper presents these steps along with recommendations for future work. Participatory and collaborative approaches in training evaluation and the steps included in this case example may be useful to evaluators, communities, and programs working on designing and evaluating various trainings with Tribal populations.

Towards detection of cancer biomarkers in human exhaled air by transfer-learning-powered analysis of odor-evoked calcium activity in rat olfactory bulb.

Detection of volatile organic compounds in exhaled air is a promising approach to non-invasive and scalable gastric cancer screening. This work proposes a new approach for the detection of volatile organic compounds by analyzing odor-evoked calcium responses in the rat olfactory bulb. We estimate the feasibility of gastric cancer biomarker detection added to the exhaled air of healthy participants. Our detector consists of a convolutional encoder and a similarity-based classifier over encoder outputs. To minimize overfitting on a small available training set, we involve a pre-training where the encoder is trained on synthetic data representing spatiotemporal patterns similar to real calcium responses in the olfactory bulb. We estimate the classification accuracy of exhaled air samples by matching their encodings with encodings of calibration samples of two classes: 1) exhaled air and 2) a mixture of exhaled air with the cancer biomarker. On our data, the accuracy increased from 0.68 on real data up to 0.74 if pre-training on synthetic data is involved. Our work is focused on proving the feasibility of proposed new approach rather than on comparing its efficiency with existing methods. Such detection is often performed with an electronic nose, but its output becomes unstable over time due to a sensor drift. In contrast to the electronic nose, rats can robustly detect low concentrations of biomarkers over lifetime. The feasibility of gastric cancer biomarker detection in exhaled air by bio-hybrid system is shown. Pre-training of neural models for images analysis increases the accuracy of detection.

Validation of a 3D-printed robot-assisted partial nephrectomy training model.

Objectives: Most renal tumours can be treated with a partial nephrectomy, with robot-assisted partial nephrectomy becoming the new gold standard. This procedure is challenging to learn in a live setting, especially the enucleation and renorraphy phases. In this study, we attempted to evaluate face, content, and preliminary construct validity of a 3D-printed silicone renal tumour model in robotic training for robot-assisted partial nephrectomy. Materials and Methods: We compared the operative results of three groups of surgeons with different experience levels (>20 partial nephrectomies, 1-20 partial nephrectomies and no experience at all) performing a robotic tumour excision of a newly developed silicone model with four embedded 3D-printed renal tumours. We evaluated the participants' performance using surgical margins, excision time, total preserved parenchyma, tumour injury and GEARS score (as assessed by two blinded experts) for construct validity. Postoperatively, the participants were asked to complete a survey to evaluate the usefulness, realism and difficulty of the model as a training and/or evaluation model. NASA-TLX scores were used to evaluate the operative workload. Results: Thirty-six participants were recruited, each group consisting of 10-14 participants. The operative performance was significantly better in the expert group as compared to the beginner group. NASA-TLX scores proved the model to be of an acceptable difficulty level.Expert group survey results showed an average score of 6.3/10 on realism of the model, 8.2/10 on the usefulness as training model and 6.9/10 score on the usefulness as an evaluation tool. GEARS scores showed a non-significant tendency to improve between trials, emphasizing its potential as a training model. Conclusion: Face and content validity of our 3D renal tumour model were demonstrated. The vast majority of participants found the model realistic and useful for training and for evaluation. To evaluate construct and predictive validity, we require further research, aiming to compare the results of 3D-model trained surgeons with those of untrained surgeons in real-life surgery.

Mechanical properties evaluation of two resin-based three-dimensional printing materials and dentine for endodontic training model fabrication: In vitro study.

The objective of the study was to compare 4 mechanical properties of two 3-D printing resins with dentine. Four mechanical tests were performed on dentine specimens, VeroClear resin and Splint resin with 15 samples each. Vickers hardness test, samples were subjected to a 300-g load for 10 s. Flexural strength test, 8-millimetre, beam-shaped specimens were tested using the three-point bending method. Drilling force was measured on flat-surface specimens. Intra-canal torque was measured on specimens imitating root canals. The results were analysed using the Kruskal-Wallis and Mann-Whitney tests with adjusted Bonferroni's p-value (p < 0.05). Dentine exhibited the highest mechanical properties in all the tests. VeroClear's flexural strength and drilling force were higher, while the surface hardness was lower than that of Splint resin. The intra-canal torque of dentine and VeroClear resin were not significant and higher than that of Splint resin. VeroClear's mechanical properties were closer to dentine than Splint resin.

A new training model using the self-healing properties of supramolecular hydrogels for endoscopic combined intrarenal surgery.

The combination of hydronephrosis formation, ureteroscopic imaging, and ultrasound delineation has not been included in any non-biological training model of percutaneous nephrolithotomy or endoscopic combined intrarenal surgery. We aimed to develop a realistic kidney phantom using the self-healing properties of supramolecular hydrogels for percutaneous nephrolithotomy and endoscopic combined intrarenal surgery and evaluate its suitability as a training model.Expert and resident urologists performed ultrasound-guided renal pelvic punctures and flexible ureteroscopies for endoscopic combined intrarenal surgery using a training model. Subsequently, the training model was evaluated using a 17-item Likert scale questionnaire (range, 1-5 points). After being filled with carrageenan, the collecting system was inflated, and the relationship between the collecting system volume and collecting system pressure was determined. The durability of the model was verified by repeatedly inserting a 16-Fr access sheath. Five novices and seven urology experts performed the procedure. The mean questionnaire score was 4.25 (standard deviation, 0.37). The model was able to hold 50 mL of air, and the pressure in the collecting system ranged from 6 to 33 mmHg. Repeated punctures were possible even when a 16-Fr access sheath was inserted. Our new training model included the self-healing properties of supramolecular hydrogels, which are tough and flexible and can be evaluated using ultrasonography. According to the questionnaire score, the model was highly satisfactory and has potential as a new educational tool.

The Effect of Preoperative Three Dimensional Modeling and Simulation on Outcome of Intracranial Aneursym Surgery.

Objective: Three-dimensional (3D) printing in vascular surgery is trending and is useful for the visualisation of intracranial aneurysms for both surgeons and trainees. The 3D models give the surgeon time to practice before hand and plan the surgery accordingly. The aim of this study was to examine the effect of preoperative planning with 3D printing models of aneurysms in terms of surgical time and patient outcomes. Methods: Forty patients were prospectively enrolled in this study and divided into two groups: Groups I and II. In group I, only the angiograms were studied before surgery. Solid 3D modelling was performed only for group II before the operation and was studied accordingly. All surgeries were performed by the same senior vascular neurosurgeon. Demographic data, surgical data, both preoperative and postoperative modified Rankin Scale scores (mRS), and Glasgow Outcome Scores (GOS) were evaluated. Results: The average time of surgery was shorter in Group II, and the difference was statistically significant between the two groups (p < 0.001). However, no major differences were found for the GOS, hospitalisation time, or mRS. Conclusion: This study is the first prospective study of the utility of 3D aneurysm models. We show that 3D models are useful in surgery preparation. In the near future, these models will be used widely to educate trainees and pre-plan surgical options for senior surgeons.

Beyond the Advanced Therapies Skills Training Network: An Instrumental Case Study of Life Sciences Skills Development for Biomedical Science Graduates in Scotland.

Biomedical sciences graduates are employed in a variety of different settings and form a significant part of the Life Sciences sector workforce in Scotland. Their degrees should equip them with the skills and knowledge to not only enter the workplace, but be adaptable in an environment that will inevitably change over the course of their careers. Industry and student feedback continue to identify perceived skills gaps, necessitating regular government-backed upskilling initiatives together with industry concerns about graduate readiness. For more than a decade, this Scottish Modern University has worked in partnership with industry and Scottish Government agencies to provide upskilling courses and incorporate relevant skills into the biomedical sciences curriculum, from problem solving and reflection to more applied, practical skills. Using the recent Advanced Therapies Skills Training Network collaboration as an instrumental case study this paper describes current best practice which has significantly impacted teaching and workplace training, ensuring biomedical sciences graduates have the knowledge and skills required for employment within the Life Science sector. Limits to the current life science skills model in Scotland are also identified (availability of placements, ad-hoc and inefficient collaborative structures, incompatible provider strategies) and recommendations made to ensure that biomedical sciences degrees continue to be part of a more sustainable, scalable solution to the skills gap. Recommendations include: better industry acknowledgement of accreditation, and more coherent, authentic and strategic collaboration which should improve skills advice and training, through a supported alliance between Industry and University Life Science Skills Committees and the establishment of regional training Centres of Excellence that would provide a focus for pooled resources and a simulated industry experience.

First evaluation of an ovine training model for sialendoscopy.

Objective: Sialendoscopy is a minimally invasive diagnostic and therapeutic technique used in the treatment of various salivary gland diseases. To date, there are very few suitable training models other than the pig's head, which has been used at the European Sialendoscopy Training Center for 22 years. The goal of this study was to describe an ovine model for sialendoscopy training and compare the ovine model's to the human anatomy. We propose a step-by-step approach for sialendoscopy training using this ex-vivo model. Methods: The anatomy of the ovine salivary ducts and glands was assessed by magnetic resonance imaging using one fresh ovine head. Thereafter, the model was designed during dissection by an experienced sialendoscopist. The various steps were then validated during consecutive dissections using a Likert-scale questionnaire. Results: The full model was described in the form of a dissection guide and allowed reliable diagnostic sialendoscopy in 10/10 Stenson's and in 5/10 Wharton's ducts. Moreover, interventional sialendoscopy was simulated to provide a training model for the removal of sialoliths in the Stenson's duct. The human and ovine anatomy are quite similar allowing a training experience close to reality. Conclusion: We developed and evaluated an ovine model with the goal of improving training in diagnostic and interventional sialendoscopy. In particular, the Stenson's duct can be successfully prepared, probed and subjected to sialendoscopy. The realistic anatomical environment and excellent tissue quality created a life-like training experience for an experienced sialendoscopist. Further studies with beginners are necessary to validate this model as a training model. Level of Evidence: 4.

Improving older adults' telehealth through a novel community-academic partnership: Preliminary data.

BACKGROUND: The COVID-19 pandemic increased the use of telehealth, which posed unique challenges for the provision of care to older adults who face numerous barriers to accessing and using technology. To improve older adults' online health-related abilities, the UCSF Geriatrics Workforce Enhancement Program (UCSF-GWEP) partnered with Little Brothers Friends of the Elderly-San Francisco (LBFE-SF) to develop a model telehealth training intervention. METHODS: LBFE-SF recruited older adults from their members with wi-fi and paired each one with a new device and volunteer trainer to cover seven lessons and four key tasks (emailing providers, video visits, accessing health information, and using patient portals). Older adults completed surveys to self-assess their skill level after training, and their confidence before, immediately after, and 3 months post training. A subset of trainees were also interviewed about their program goals and experiences. UCSF-GWEP conducted statistical analyses of survey data, and coded interview transcripts to identify aspects of the model supportive to learning and success. RESULTS: Of 43 participants, 31 completed training. Their median age was 75; 48% were non-white; 45% had no more than a high school education; and 63% reported yearly income below U.S. $20,000. Three months after completing the program, more than 50% of trainees reported that they needed little or no help performing all four key tasks, and confidence with video visits, online searches, and patient portals showed significant improvement. Additionally, in interviews participants reported improved health, social benefits, and explained that learning was facilitated by self-pacing, repetition, and longitudinal support from volunteer trainers. CONCLUSIONS: Older adults with various barriers to learning technology showed online independence and increased confidence with some telehealth tasks after a novel training intervention. Key characteristics of the model included a tablet device, one-on-one longitudinal support from volunteers, comprehensive learning materials, and community-academic partnership.

Percutaneous pelvic fixation model: an affordable and realistic simulator for pelvic trauma training.

PURPOSE: To describe the construction and use of a percutaneous pelvic fixation model, evaluate its translational validity among fellowship-trained orthopedic trauma surgeons, and investigate the importance of specific criteria for effective competency-based assessment of pelvic fixation techniques. METHODS: Five orthopedic trauma surgeons were asked to place percutaneous wires on a pelvic fixation model, including anterior column (antegrade/retrograde), posterior column (antegrade/retrograde), supra-acetabular, transsacral, and iliosacral. Evaluation criteria included successful wire placement, redirections, cortical breaches, procedure duration, radiation exposure, and quality of fluoroscopic views. Following completion, participants were provided a survey to rate the model. RESULTS: There were no differences between approaches on successful screw placement, wire redirections, or fluoroscopic quality. Antegrade approaches to the anterior and posterior columns took longer (p = 0.008) and used more radiation (p = 0.02). There was also a trend toward more cortical breaches with the antegrade anterior column approach (p = 0.07). Median ratings among surgeons were 4 out of 5 for their overall impression and its accuracy in tactile response, positioning constraints, and fluoroscopic projections. Learning parameters considered most important to the progression of trainees (most to least important) were successful screw placement, corridor breaches, wire redirections, quality of fluoroscopic views, radiation exposure, and procedure duration. CONCLUSION: In being affordable, accessible, and realistic, this percutaneous pelvic fixation model represents an opportunity to advance orthopedic surgery education globally. Future research is needed to validate the findings of this pilot study and to expand upon how trainees should be evaluated within simulations and the operating room to optimize skill progression.

Preliminary experience with robotic cholecystectomy illustrates feasibility in a canine cadaver model.

OBJECTIVE: To evaluate the feasibility and describe the relevant differences between robotic cholecystectomy (RC) and laparoscopic cholecystectomy in a canine model. SAMPLE: Canine cadavers (n = 4) weighing between 30 and 42 kg. METHODS: Dogs were positioned in dorsal recumbency. A surgical robot was used to perform the RC and was placed at the cranial aspect of the surgical table. One 12-mm and 3 8-mm robotic ports and 1 5-mm laparoscopic port were placed as needed to perform the RC. The specific steps of the procedure were described and timed. Perceived differences between psychomotor skills between robotics and laparoscopy were noted. RESULTS: RC was successful in all dogs, but minor intraoperative complications did occur during the manipulation of the gallbladder in 1 dog. The median length of time for ports to be appropriately docked was 19.5 minutes, and the median procedure time was 119.5 minutes. Psychomotor skills specific to robotics can be learned during this procedure. CLINICAL RELEVANCE: Robotic cholecystectomy is feasible. RC allowed for experience with the different psychomotor skills utilized with robotic instrumentation and may be an appropriate training procedure for veterinary surgeons wishing to gain basic experience with robotic instrumentation.

Training in Diagnostic Hysteroscopy: The "Arbor Vitae" Method.

Background and Objectives: Diagnostic hysteroscopy is the gold standard in the diagnosis of intrauterine pathology and is becoming an essential tool in the daily practice of gynecology. Training programs for physicians are necessary to ensure adequate preparation and learning curve before approaching patients. The aim of this study was to describe the "Arbor Vitae" method for training in diagnostic hysteroscopy and to test its impact on the knowledge and skills of trainees using a customized questionnaire. Materials and Methods: A three-day hysteroscopy workshop combining theory and practical "hands on "sessions with dry and wet labs has been described. The aim of the course is to teach indications, instruments, the basic principles of the technique by which the procedure should be performed, and how to recognize and manage the pathologies that can be identified by diagnostic hysteroscopy. To test this training method and its impact on the knowledge and skills of the trainees, a customized 10-question questionnaire was administered before and after the course. Results: The questionnaire was administered to 34 participants. All trainees completed the questionnaire, and no missing responses were recorded. Regarding the characteristics of the participants, 76.5% had less than 1 year of experience in performing diagnostic hysteroscopy and 55.9% reported performing fewer than 15 procedures in their career. For 9 of the 10 questions embedded in the questionnaire, there was a significant improvement in the scores between pre- and post-course, demonstrating a perceived significant improvement in theoretical/practical skills by the trainees. Conclusions: The Arbor Vitae training model is a realistic and effective way to improve the theoretical and practical skills required to perform correct diagnostic hysteroscopy. This training model has great potential for novice practitioners to achieve an adequate level of proficiency before performing diagnostic hysteroscopy on live patients.