Software Tools Research Articles

Biophysical essentials – A full stack open-source software framework for conserved and advanced analysis of patch-clamp recordings

Background and ObjectivesPatch-Clamp recordings allow for in depth electrophysiological characterization of single cells, their general biophysical properties as well as characteristics of voltage- and ligand-gated ionic currents. Different acquisition modes, such as whole-cell patch-clamp recordings in the current or voltage clamp configuration, capacitance measurements or single channel recordings from cultured cells as well as acute brain slices are routinely performed for these purposes. Nevertheless, multipurpose transparent and adaptable software tools to perform reproducible state-of-the-art analysis of multiple experiment types and to manage larger sets of experimental data are currently unavailable. MethodsBiophysical Essentials (BPE) was developed as an open-source full stack python software for transparent and reproducible analysis of electrophysiological recordings. For validation, BPE results were compared with manually analyzed single-cell patch-clamp data acquired from a human in vitro nociceptor-model and mouse dorsal root ganglia neurons. ResultsWhile initially designed to improve time consuming and repetitive analysis steps, BPE was further optimized as a technical software solution for entire workflow processing including data acquisition, data preprocessing, normalization and visualization and of single recordings up to stacked calculations and statistics of multiple experiments. BPE can operate with different file formats from different amplifier systems and producers. An in-process database logs all analysis steps reproducible review and serves as a central storage point for recordings. Statistical testing as well as advanced analysis functions like Boltzmann-fitting and dimensional reduction methods further support the researchers' needs in projects involving electrophysiology techniques. ConclusionsBPE extends beyond available patch-clamp specific, open source – and commercial analysis tools in particular because of reproducible and sharable analysis workflows. BPE enables full analysis from raw data acquisition to publication ready result visualizations – all within one single program. Thereby, BPE significantly enhances transparency in the analytical process of patch-clamp data analysis. BPEs function scope is completely accessible through an easy-to-use graphical user interface eliminating the need for programing language proficiency as required by many community patch-clamp analysis frameworks and algorithms.

Utilizing classical programming principles in the Intel Quantum SDK: implementation of quantum lattice Boltzmann method

We explore the use of classical programming techniques in implementing the quantum lattice Boltzmann method in the Intel Quantum SDK – a software tool for quantum circuit creation and execution on Intel quantum hardware. As hardware access is limited, we use the state vector simulator provided by the SDK. The novelty of this work lies in leveraging classical techniques for the implementation of quantum algorithms. We emphasize the refinement of algorithm implementation and devise strategies to enhance quantum circuits for better control over problem variables. To this end, we adopt classical principles such as modularization, which allows for systematic and controlled execution of complex algorithms. Furthermore, we discuss how the same implementation could be expanded from state vector simulations to execution on quantum hardware with minor adjustments in these configurations.

BioPipeline Creator—a user-friendly Java-based GUI for managing and customizing biological data pipelines

Bioinformatics tools are essential for performing analyses in the omics sciences. Given the numerous experimental opportunities arising from advances in the field of omics and easier access to high-throughput sequencing platforms, these tools play a fundamental role in research projects. Despite the considerable progress made possible by the development of bioinformatics tools, some tools are tailored to specific analytical goals, leading to challenges for non-bioinformaticians who need to integrate the results of these specific tools into a customized pipeline. To solve this problem, we have developed the BioPipeline Creator, a user-friendly Java-based GUI that allows different software tools to be integrated into the repertoire while ensuring easy user interaction via an accessible graphical interface. Consisting of client and server software components, BioPipeline Creator provides an intuitive graphical interface that simplifies the use of various bioinformatics tools for users without advanced computer skills. It can run on less sophisticated devices or workstations, allowing users to keep their operating system without having to switch to another compatible system. The server is responsible for the processing tasks and can perform the analysis in the user's local or remote network structure. Compatible with the most important operating systems, available at https://github.com/allanverasce/bpc.git.

Can We Screen for Limb Length Discrepancy on Spinal Radiographs of Patients With Adolescent Idiopathic Scoliosis?

The aim of this study was to determine whether height differences in the levels of the iliac crests and femoral heads on erect spinal radiographs can be used as indirect measurements for the screening and surveillance of limb length discrepancy (LLD) in patients with scoliosis. Whole body posteroanterior (PA) and lateral erect radiographs of patients with adolescent idiopathic scoliosis (AIS) were retrospectively reviewed. Patients with congenital, syndromic, and neuromuscular scoliosis were excluded. A direct measurement of each limb was taken from the highest point of the femoral head to the middle of the tibial plafond; any difference between the sides was recorded as the LLD. In addition, the PACS Software tool was used to measure femoral head height difference (FHHD) and iliac crest height difference (ICHD). Pearson's correlation, linear regression, and Bland-Altman plots were used to determine the relationships between LLD and FHHD, and LLD and ICHD. Radiographs of 141 patients (92 women, 49 men) with an average age of 12.0±2.65 years were analyzed. A strong correlation (r=0.730, P<0.001) was found between LLD and FHHD; the correlation between LLD and ICHD was weaker (r=0.585, P<0.001). The Bland-Altman analysis showed good agreements of LLD with FHHD and ICHD. Linear regression analysis predicted an LLD of ≤10mm based on an FHHD of ≤11.5mm or an ICHD of ≤15.3mm. FHHD and ICHD on spinal PA radiographs can be used for the screening and monitoring of LLD in patients with AIS with FHHD being the preferred indirect measurement. These measurements are readily learned and quick to perform. The FHHD and ICHD can be measured on any erect scoliosis PA radiograph. Therefore, these proxy measurements can be used to screen and monitor for LLD in patients with AIS. Level III.

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data.

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, we describe and illustrate PeakQC's functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

WEDAP: A Python Package for Streamlined Plotting of Molecular Simulation Data.

Given the growing interest in path sampling methods for extending the time scales of molecular dynamics (MD) simulations, there has been great interest in software tools that streamline the generation of plots for monitoring the progress of large-scale simulations. Here, we present the WEDAP Python package for simplifying the analysis of data generated from either conventional MD simulations or the weighted ensemble (WE) path sampling method, as implemented in the widely used WESTPA software package. WEDAP facilitates (i) the parsing of WE simulation data stored in highly compressed, hierarchical HDF5 files and (ii) incorporates trajectory weights from WE simulations into all generated plots. Our Python package consists of multiple user-friendly interfaces: a command-line interface, a graphical user interface, and a Python application programming interface. We demonstrate the plotting features of WEDAP through a series of examples using data from WE and conventional MD simulations that focus on the HIV-1 capsid protein's C-terminal domain dimer as a showcase system. The source code for WEDAP is freely available on GitHub at https://github.com/chonglab-pitt/wedap.

Формирование навыков командной деятельности и их объективная количественная оценка на основе квантовых представлений

&lt;p&gt;Presented are mathematical and software tools providing the formation and objective quantitative assessment of teamwork skills based on quantum representations. These tools utilize the formal representations of subjects' activities through probability matrices of transitions between the performed elementary operations. Analysis of the subjects' activities is based on comparisons of these matrices for a pattern of actions under study with relevant matrices for patterns of empirical data representing various variants of the subjects' work. When evaluating the teamwork skills, these comparisons are performed according to the "Triangle Scheme", which involves comparing the coordinated actions of the subjects performed in pairs and individually. For this purpose, the quantum spectral analysis is used, which provides effective quantitative comparisons of the hidden periodicities of performing typical elementary operations and their quantities in the spectral metric. The tools for the formation and assessment of teamwork skills are implemented in the form of both a flight simulator with the separation of control channels between pilots and a modified computer game "Sea Battle", which allows to evaluate the dynamics of partners&amp;rsquo; communication and cooperation by analyzing their moves as well as tips transmitted to each other. The presented approach to the formation and assessment of teamwork skills is quite universal and can be used in various applications areas, including the assessment and training of flight crews, operators of complex technical systems, students of various levels and other target groups.&lt;/p&gt;

Endophthalmitis: a bibliometric study and visualization analysis from 1993 to 2023.

This study is designed to generalize and depict the research hotspots of endophthalmitis through bibliometric methods and software and analyze the evolutive tendency of the work on this severe disease over the past 30 years. This study employed a rigorous bibliometric approach. We identified all endophthalmitis-related literature by conducting a comprehensive search of the Science Citation Index Expanded database under the Web of Science Core Collection. The data was then analyzed and visualized using CiteSpace and VOSviewer, two widely recognized software tools in the field of bibliometrics. CiteSpace was used to analyze the country distributions, dual map overlay of journals, keyword bursts, and co-cited references. VOSviewer was employed to describe the authors and co-cited authors, the journals, the co-cited journals, and the keywords co-occurrence network. This robust methodology ensures the reliability and validity of the study's findings. A total of 2960 publications, including 2695 articles and 265 reviews, were included in this bibliometric study. There has been no shortage of endophthalmitis-related publications since 1993, with an apparent upward trend during recent years. Possible correlations with the COVID-19 pandemic are also analyzed. These studies were finished by 11,048 authors from 75 countries worldwide, with the United States in the lead. In the keyword co-occurrence network, except for the endophthalmitis term, cataract surgery becomes the keyword with the highest frequency. Different categories of endophthalmitis, including postoperative, post-injection, post-traumatic, and endogenous endophthalmitis, and antibacterial and anti-inflammatory therapies of infectious endophthalmitis, are discussed by categories. From the perspective of the timeline, postoperative and post-injection endophthalmitis were the dominant forms before and after the year 2000, respectively. Co-citation analyses reveal that the Endophthalmitis Vitrectomy Study (EVS) conducted in 1995 provides pivotal guidance for later research. Diverse pathogenic bacteria (e.g., Coagulase-negative Staphylococci, Propionibacterium acnes, Viridians Streptococci, and Bacillus cereus) or fungi (e.g., Candida, Aspergillus, and Fusarium) contribute to varying treatment principles and clinical prognosis, which should be taken seriously. In addition, intravitreal and intracameral antibiotics are the mainstay for treating and preventing infectious endophthalmitis, respectively. Our bibliometric analysis provides an overview of dynamic evolution and structural relationships in the research field of endophthalmitis. The displayed hotspots and developmental directions have reference values for future investigation.

Research and implementation of three-dimensional modeling techniques for Chinese dragon

This paper delves into a new trend in the field of computer science, which involves a shift from complex code editing techniques of the past towards more intuitive visual software applications. Under this trend, modeling and rendering techniques have undergone long-term development and continuous iteration, becoming indispensable tools across various domains. Using the construction of a Chinese dragon model as a case study, this paper showcases the application and development of this new trend through a detailed description of the selected software tools' characteristics, classification of production steps, and the modeling process. Special emphasis was placed on shaping key details such as the dragon's body contour, scales, eyes, etc., during the dragon model construction process, as well as how these details are manifested in software applications. Software selection and utilization were carefully aligned with practical needs and technical features to ensure the efficiency and accuracy of the modeling process. In-depth research into the modeling process revealed the potential and advantages of this new technology, receiving widespread acclaim and recognition.

Research and implementation of three-dimensional modeling techniques for Chinese dragon

This paper delves into a new trend in the field of computer science, which involves a shift from complex code editing techniques of the past towards more intuitive visual software applications. Under this trend, modeling and rendering techniques have undergone long-term development and continuous iteration, becoming indispensable tools across various domains. Using the construction of a Chinese dragon model as a case study, this paper showcases the application and development of this new trend through a detailed description of the selected software tools' characteristics, classification of production steps, and the modeling process. Special emphasis was placed on shaping key details such as the dragon's body contour, scales, eyes, etc., during the dragon model construction process, as well as how these details are manifested in software applications. Software selection and utilization were carefully aligned with practical needs and technical features to ensure the efficiency and accuracy of the modeling process. In-depth research into the modeling process revealed the potential and advantages of this new technology, receiving widespread acclaim and recognition.

Development and Control of Virtual Industrial Process using Factory IO and MATLAB

In today's rapidly evolving business landscape, the strategic adoption of virtual manufacturing methods has emerged as a key driver for companies seeking to streamline operations and expedite product launches in a cost-effective manner. This progressive approach involves the creation of a synthetic and interconnected environment, empowered by advanced software tools and systems, including Virtual Reality and Simulation technologies, tailored to optimize industrial processes. Our methodology employs a unique combination of two simulation software tools: Factory I/O for process development and MATLAB for control program implementation. Furthermore, we explore the use of the Modbus TCP/IP communication protocol as the framework for seamless interaction between these software tools during simulation. This research presents practical insights into the transformative potential of virtual manufacturing, showcasing its real-world application in enhancing operational efficiency and agility within industrial settings.

A COMPARATIVE STUDY BETWEEN OPEN CHOLECYSTECTOMY VERSUS LAPAROSCOPIC CHOLECYSTECTOMY

Objective: This study aims to evaluate the comparative effectiveness of laparoscopic cholecystectomy (LC) versus open cholecystectomy (OC) in terms of surgery duration, blood loss, postoperative discomfort, hospital stay length, cost-effectiveness, and patient satisfaction. It also assesses differences in primary outcomes, such as mortality, complications, and symptom relief, as well as secondary outcomes, including conversion rates, operative time, and recovery. Methods: We conducted a prospective observational study involving 200 patients aged 10-70 with symptomatic gallstones confirmed via ultrasonography at Somani Hospital, Jaipur, from July 2021 to August 2023. Patients were randomly assigned to undergo either lC or OC. We collected data on surgical duration, blood loss, postoperative pain, hospitalization period, and complications, among other variables. Statistical analysis was performed using software tools. Results: Our study involved 200 patients, predominantly female (77%). The average duration of lC was shorter (67.37 min) compared to OC (93.95 min). lC patients had a shorter average hospital stay (2.8 d) compared to OC patients (5.1 d). The conversion rate from lC to OC was 6%, primarily due to anatomical and technical challenges. Complications were significantly lower in lC (17%) compared to OC (28%). Conclusion: lC is more efficient, entails fewer complications, and leads to a quicker recovery and shorter hospital stay compared to OC, supporting its preference in surgical practice for eligible patients with symptomatic gallstone disease. The lower rate of complications and shorter recovery time suggest that lC should be the standard care for cholecystectomy where feasible.

Drug-drug interactions and synergy: from pharmacological models to clinical application.

This review explores the concept of synergy in pharmacology, emphasizing its importance in optimizing treatment outcomes through the combination of drugs with different mechanisms of action. Synergy, defined as an effect greater than the expected additive effect elicited by individual agents according to specific predictive models, offers a promising approach to enhance therapeutic efficacy while minimizing adverse events. The historical evolution of synergy research, from ancient civilizations to modern pharmacology, highlights the ongoing quest to understand and harness synergistic interactions. Key concepts such as concentration-response curves, additive effects, and predictive models are discussed in detail, emphasizing the need for accurate assessment methods throughout translational drug development. While various mathematical models exist for synergy analysis, selecting the appropriate model and software tools remains a challenge, necessitating careful consideration of experimental design and data interpretation. Furthermore, this review addresses practical considerations in synergy assessment, including preclinical and clinical approaches, mechanism of action, and statistical analysis. Optimizing synergy requires attention to concentration/dose ratios, target site localization, and timing of drug administration, ensuring that the benefits of combination therapy detected at bench-side are translatable into clinical practice. Overall, the review advocates for a systematic approach to synergy assessment, incorporating robust statistical analysis, effective and simplified predictive models, and collaborative efforts across pivotal sectors such as academic institutions, pharmaceutical companies, and regulatory agencies. By overcoming critical challenges and maximizing therapeutic potential, effective synergy assessment in drug development holds promise for advancing patient care. Significance Statement Combining drugs with different mechanisms of action for synergistic interactions optimizes treatment efficacy and safety. Accurate interpretation of synergy requires the identification of the expected additive effect. Despite innovative models to predict the additive effect, consensus in drug interaction research is lacking, hindering the bench-to-bedside development of combination therapies. Collaboration among science, industry, and regulation is crucial for advancing combination therapy development, ensuring rigorous application of predictive models in clinical settings.

The renewable energy research contribution of Tanzania: A review

The central objectives of this study are to locate existing research on renewable energy, examine the energy policy of Tanzania, assess bibliometric factors, determine the direction of the current research, and comprehend unexplored research topics. This exploration focuses on a bibliometric-based study using computer-assisted software tools known as VOS viewer and RStudio in analyzing the Scopus data retrieved package for the key phrase of "Renewable energy" in the article titles published from 2002 to 2022. A total of 661 publications (which is only 0.45% and 6.3% of the global and continental publications from Africa respectively) were analysed after refining using different bibliometric criteria like study site, type of document, publication stage, language used in the document, and publication time interval. The results shows that Energy fuels, engineering, technology, environmental sciences, ecology, and business economics are the most frequently studied fields. Also, from a total of 661 publications, only 32 documents were published from Tanzania for 20 years from 2022 which is less than 2 publication/year. This study concludes that there is a notable lack of research output from Tanzania in this critical field. This gap underscores the need for greater investment in renewable energy research and development within the country, as well as targeted efforts to build research capacity and foster collaboration among academia, government, and industry stakeholders.

AscentAM: A Software Tool for the Thermo-Mechanical Process Simulation of Form Deviations and Residual Stresses in Powder Bed Fusion of Metals Using a Laser Beam

Due to the tool-less fabrication of parts and the high degree of geometric design freedom, additive manufacturing is experiencing increasing relevance for various industrial applications. In particular, the powder bed fusion of metals using a laser beam (PBF-LB/M) process allows for the metal-based manufacturing of complex parts with high mechanical properties. However, residual stresses form during PBF-LB/M due to high thermal gradients and a non-uniform cooling. These lead to a distortion of the parts, which reduces the dimensional accuracy and increases the amount of post-processing necessary to meet the defined requirements. To predict the resulting residual stress state and distortion prior to the actual PBF-LB/M process, this paper presents the finite-element-based simulation tool AscentAM with its core module and several sub-modules. The tool is based on open-source programs and utilizes a sequentially coupled thermo-mechanical simulation, in which the significant influences of the manufacturing process are considered by their physical relations. The simulation entirely emulates the PBF-LB/M process chain including the heat treatment. In addition, algorithms for the part pre-deformation and the export of a machine-specific file format were implemented. The simulation results were verified, and an experimental validation was performed for two benchmark geometries with regard to their distortion. The application of the optimization sub-module significantly minimized the form deviation from the nominal geometry. A high level of accuracy was observed for the prediction of the distortion at different manufacturing states. The process simulation provides an important contribution to the first-time-right manufacturing of parts fabricated by the PBF-LB/M process.

Management and Operator Control System based on Microservice Architecture and Application on the HIPr Accelerator

The paper describes the basic principles of developing a distributed control system (DCS) and a GARNET operator control system based on a microservice architecture as part of a high-availability cluster. The application of the operator’s control system as a DCS component is described. The main elements of software components of operator control and DCS are presented and described. The process of conveyor assembly and publication of software tools into a working product environment, which implements the principle of continuous integration, is described. The mechanism of interaction of key components among themselves is presented. The mechanism for hosting management services using the Docker containerization system and Kubernetes container orchestration is demonstrated. Examples of services for interaction with users in the environment of the GARNET operator control system being developed, separation of users by roles and access rights, integration of the data visualization service using Grafana are shown. The vector of further development of DCS and operator control tools is described, in particular, the possibility of using the practice of developing user web interfaces using the micro frontend approach. The components and results of the operation of a prototype system designed to interact with the measurement infrastructure of the linear heavy ion accelerator HIPR are presented.

Comparison of Transcranial Magnetic Stimulation Dosimetry between Structured and Unstructured Grids Using Different Solvers.

In recent years, the interest in transcranial magnetic stimulation (TMS) has surged, necessitating deeper understanding, development, and use of low-frequency (LF) numerical dosimetry for TMS studies. While various ad hoc dosimetric models exist, commercial software tools like SimNIBS v4.0 and Sim4Life v7.2.4 are preferred for their user-friendliness and versatility. SimNIBS utilizes unstructured tetrahedral mesh models, while Sim4Life employs voxel-based models on a structured grid, both evaluating induced electric fields using the finite element method (FEM) with different numerical solvers. Past studies primarily focused on uniform exposures and voxelized models, lacking realism. Our study compares these LF solvers across simplified and realistic anatomical models to assess their accuracy in evaluating induced electric fields. We examined three scenarios: a single-shell sphere, a sphere with an orthogonal slab, and a MRI-derived head model. The comparison revealed small discrepancies in induced electric fields, mainly in regions of low field intensity. Overall, the differences were contained (below 2% for spherical models and below 12% for the head model), showcasing the potential of computational tools in advancing exposure assessment required for TMS protocols in different bio-medical applications.

A comprehensive dataset of annotated oral cavity images for diagnosis of oral cancer and oral potentially malignant disorders

ObjectivesThis study aims to address the critical gap of unavailability of publicly accessible oral cavity image datasets for developing machine learning (ML) and artificial intelligence (AI) technologies for the diagnosis and prognosis of oral cancer (OCA) and oral potentially malignant disorders (OPMD), with a particular focus on the high prevalence and delayed diagnosis in Asia. Materials and methodsFollowing ethical approval and informed written consent, images of the oral cavity were obtained from mobile phone cameras and clinical data was extracted from hospital records from patients attending to the Dental Teaching Hospital, Peradeniya, Sri Lanka. After data management and hosting, image categorization and annotations were done by clinicians using a custom-made software tool developed by the research team. ResultsA dataset comprising 3000 high-quality, anonymized images obtained from 714 patients were classified into four distinct categories: healthy, benign, OPMD, and OCA. Images were annotated with polygonal shaped oral cavity and lesion boundaries. Each image is accompanied by patient metadata, including age, sex, diagnosis, and risk factor profiles such as smoking, alcohol, and betel chewing habits. ConclusionResearchers can utilize the annotated images in the COCO format, along with the patients’ metadata, to enhance ML and AI algorithm development.

GOTHIC and MELCOR benchmarking of the CNL strong condensation containment apparatus experiments

Understanding severe accident behaviour in water-cooled small modular reactors is crucial for their deployment, as well as having qualified software tools for safety analysis. A model benchmarking exercise was conducted where predictions from the software tools GOTHIC and MELCOR were compared against past experiments from the Strong Condensation Containment Apparatus (SCCA). Key phenomena that can be expected in small modular reactor (SMR) containments, given their small size and external passive water cooling, are explored, including how well the codes replicate stratification between a hot upper layer and a cooler under layer. This overall thermalhydraulics behaviour impacts other important phenomena, like heat transfer and aerosol deposition. MELCOR, an integrated severe accident code, and GOTHIC, a thermalhydraulic and containment code, were used in benchmarking activities, wherein the experimental results were compared to their simulation results. The findings demonstrated MELCOR’s capabilities to simulate the SCCA experiments and GOTHIC’s strength in predicting multiphase flow and thermalhydraulics in containment and cooling systems. In addition, the benchmark comparisons provided new insights toward modelling experiments with these codes as well as the behaviour observed in the SCCA experiment. These findings will guide accident management and emergency preparedness requirements for SMRs.

A cost modelling methodology based on machine learning for engineered-to-order products

Recent scientific studies are targeted at applying and assessing the effectiveness of Machine Learning (ML) approaches for cost estimation during the preliminary design phases. To train ML prediction models, comprehensive and structured datasets of historical data are required. This solution is inapplicable when such information is unavailable or sparse due to the lack of structured datasets. For engineered-to-order products, the number of historical records is often limited and strongly influenced by different purchasing or manufacturing strategies, thus requiring complex normalisation of such data.This method overcomes the above limitations by presenting an ML-based cost modelling methodology for the conceptual design that is applicable even when historical data are insufficient to train the prediction algorithms. The training dataset is generated through an analytical and automatic software tool for manufacturing cost estimation. Such a tool, starting from a 3D model of a product, can quickly and autonomously assess the related cost in different scenarios. An extensive and structured training dataset can be easily generated. The proposed methodology was based on CRISP-DM (Cross Industry Standard Process for Data Mining).Cost engineers of an Oil & Gas company used the method to develop parametric cost models for discs and spacers of an axial compressor. The solution guarantees lower error (7% vs 9%) and significant time-saving (minutes instead of hours) than estimations based on other approaches. Cost models are more comprehensive (capable of analysing different scenarios), explainable (not conceived as a black box), and self-learning (can be updated by extending the training dataset).