Statistical Analysis Of Data Research Articles

Associations of the Serum KL-6 with Severity and Prognosis in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

As a biomarker of alveolar-capillary basement membrane injury, Krebs von den Lungen-6 (KL-6) is involved in the occurrence and development of pulmonary diseases. However, the role of the KL-6 in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) has yet to be elucidated. This prospective study was designed to clarify the associations of the serum KL-6 with the severity and prognosis in patients with AECOPD. This study enrolled 199 eligible AECOPD patients. Demographic data and clinical characteristics were recorded. Follow-up was tracked to evaluate acute exacerbation and death. The serum KL-6 concentration was measured via an enzyme-linked immunosorbent assay. Serum KL-6 level at admission was higher in AECOPD patients than in control subjects. The serum KL-6 concentration gradually elevated with increasing severity of AECOPD. Pearson and Spearman analyses revealed that the serum KL-6 concentration was positively correlated with the severity score, monocyte count and concentrations of C-reactive protein, interleukin-6, uric acid, and lactate dehydrogenase in AECOPD patients during hospitalization. A statistical analysis of long-term follow-up data showed that elevated KL-6 level at admission was associated with longer hospital stays, an increased risk of future frequent acute exacerbations, and increased severity of exacerbation in COPD patients. Serum KL-6 level at admission is positively correlated with increased disease severity, prolonged hospital stay and increased risk of future acute exacerbations in COPD patients. There are positive dose-response associations of elevated serum KL-6 with severity and poor prognosis in COPD patients. The serum KL-6 concentration could be a novel diagnostic and prognostic biomarker in AECOPD patients.

Climate temperature and seasonal influences on the prevalence of temporomandibular disorders in South Korea

This study aimed to explore seasonal variations in temporomandibular disorder (TMD) prevalence in South Korea, utilizing nationwide population-based big data. Data corresponding to the Korean Standard Classification of Diseases code of K07.6, which identifies TMD, were extracted from the Health Insurance Review and Assessment Service online platform for the period from 2010 to 2022. Additionally, we integrated these data with climate temperature records from the Korean Meteorological Administration. We subsequently conducted a statistical analysis of TMD patient data on a monthly and seasonal basis over the past 13 years to assess prevalence. Over the past 13 years, the number of TMD patients in Korea has steadily increased. The prevalence of TMD rose from 0.48% (224,708 out of a total population of 50,515,666) in 2010 to 0.94% (482,241 out of a total population of 51,439,038) in 2022, marking a 1.96-fold increase. Among children under 10 years of age, no significant differences were observed in TMD prevalence between boys and girls. However, a distinct female predominance emerged after the age of 10, with an average female-to-male ratio of 1.51:1. The peak prevalence of TMD occurred in individuals in their 20 s, followed by adolescents in their late 10 s. The majority of TMD patients were concentrated in Seoul and Gyeonggi province, with metropolitan areas accounting for 50% of the total patient count. Seasonally, TMD patient numbers showed no significant increase in winter compared with spring or summer. The temperature difference, defined as the absolute difference between the highest and lowest temperatures for each month, showed a positive correlation with TMD patient counts. A greater temperature difference was associated with higher patient counts. The strongest correlation between temperature differences and TMD patient numbers was observed in winter (r = 0.480, p < 0.01), followed by summer (r = 0.443, p < 0.01), and spring (r = 0.366, p < 0.05). Temperature differences demonstrated a significantly stronger correlation with the increase in the number of TMD patients than absolute climate temperatures. This aspect should be a key consideration when examining seasonal trends in TMD prevalence in South Korea.

Industry sector’s influence on the narratives in environmental disclosures in the opinion of reports preparers. Evidence from Poland

The narrative phenomenon in accounting concerns, i.e., the disclosure of environmental information and the impression management of stakeholders. The study examines and assesses the dependence between the company’s industry of activity and the narration perception adopted by the preparers of environmental reports, in particular, the impression management techniques used. To achieve the purpose of the article, an in-depth survey was conducted covering a non-random sample of the employees of Polish enterprises involved in the preparation and reporting of environmental information. Contingency tables and association measures for categorical variables were used in the statistical analysis of the survey data. The analysis results of the collected empirical data confirmed that the company’s industry of activity impacts the way report preparers evaluate the scope and apply narrative strategies, especially impression management techniques. The research expands knowledge on the perception of the importance of environmental disclosures and the issue of environmental narrative practices from an enterprise perspective. The results of the analysis indicated a level of pro-environmental awareness and confirmed the knowledge of narrative strategies and techniques. This study contributes to the discussion on the effects of environmental narrative in accounting, offering yet another element of the current practice diagnosis in this area in Poland.

H-Wave® Device Stimulation for Chronic Neck Pain: A Patient-Reported Outcome Measures (PROMs) Study.

Chronic neck pain (cNP) is one of the leading causes of disability worldwide, often being refractory to conventional forms of treatment. Various forms of electrical stimulation have been proposed to decrease pain and improve function. Patient-reported outcome measures (PROMs) for treatment of cNP have rarely been published. An independent retrospective statistical analysis of PROMs data for users of H-Wave® device stimulation (HWDS), prospectively collected by the device manufacturer over a 4-year period, was conducted. Final surveys for 34,192 pain management patients were filtered for pain chronicity limited to 3-24months and device use of 22-365days, resulting in 11,503 patients with "all diagnoses"; this number was further reduced to 1482 patients with cNP, sprain, or strain. Neck pain was reduced by 3.13 points (0-10 pain scale), with significant (≥20%) relief in 86.6%. Function/activities of daily living (ADL) improved in 96.19%, while improved work performance was reported in 84.76%. Medication use decreased or stopped in 65.42% and sleep improved in 60.39%. Over 95% reported having expectations met or exceeded, service satisfaction, and confidence in device use, while no adverse events were reported. Subgroup analyses found positive benefit associations with longer duration of device use. Near-equivalent outcomes were self-reported by cNP HWDS patients as for (previously published) chronic low back pain (cLBP) patients. HWDS provided effective and safe cNP relief, improvements in function and ADL, along with additional benefits including decreased medication use, better sleep, and improved work performance.

Analysis of Multiple Scattering Characteristics of Cable-Stayed Bridges with Multi-band SAR

Abstract. Accurate localization of multi-scattering features of cable-stayed bridges in multi-band Synthetic Aperture Radar (SAR) imagery is crucial for intelligent recognition of bridge targets within images, as well as for precise water level extraction. This study focuses on the Badong Yangtze River Bridge, utilizing Unmanned Aerial Vehicle (UAV) LiDAR data of the bridge, and analyzes the multi-scattering characteristics of different bridge structural targets based on Geometric Optics (GO) methods and the Range-Doppler principle. Furthermore, the study integrates LiDAR data of the bridge's cable-stays to examine their multi-scattering phenomena, finding that the undulations of the Yangtze River's surface waves significantly contribute to the pronounced double scattering features of the bridge's cable-stays. Additionally, statistical analysis of multi-source SAR data indicates that this phenomenon is not directly correlated with radar wavelength, implying no direct connection to surface roughness. Utilizing LiDAR point cloud data from the bridge's street lamps, this paper proposes a novel method for estimating water level elevation by identifying the center position of spots formed by double scattering from lamp posts. The results show that using TerraSAR ascending and descending orbit images, this method achieves a water level elevation accuracy of approximately 0.2 meters.

Use of Alkaline-Activated Energy Waste Raw Materials in Geopolymer Concrete

Silica fly ash, Certyd aggregate, and an alkaline solution were used to produce lightweight geopolymer concretes. The compressive strength, water absorption, and bulk density results, along with SEM photos showing the structure of the obtained composite, were obtained. Tests conducted on the specifications of lightweight geopolymer concretes have revealed significant chemical interactions between the ash aggregate and the geopolymer mortar, particularly when the coarse aggregate surface has been pre-treated with an alkaline solution. A statistical analysis of the experimental data, which investigated the influence of three key variables on the compressive strength, water absorption, and bulk density of lightweight geopolymer concrete (LBG), identified the following factors as having the most substantial impact: the quantity of alkali used, the curing temperature, and the concentration of alkali in the mixture. The optimal test series exhibited a commendable compressive strength of 20.14 megapascals (MPa), accompanied by a water absorption rate of 14.72%, and a bulk density of 1486.6 kg per cubic meter (kg/m³). These findings underscore the importance of alkali content, curing temperature, and alkali concentration in tailoring the properties of lightweight geopolymer concrete to meet specific performance requirements.

EFFECT OF TOURIST TRAFFIC ON THE ECOSYSTEM OF LAKE MORSKIE OKO

Abstract. The Tatra National Park is the most frequently visited national park in Poland. Its most popular tourist trail is the route to Lake Morskie Oko, the second largest lake in the Tatra Mountains, and the best known mountain lake in Poland. The paper is based on results of field observations, and the analysis of literature and statistical data. The ecosystem of Morskie Oko in this paper is defined as the area of the lake’s catchment. The unique character of Morskie Oko is reflected by its recognition by “The Wall Street Journal” as one of five most beautiful lakes in the world. This results in exceptionally high interest of tourists in the lake despite the difficulties reaching the place. It takes walking a nine-kilometre route with a height difference of 420 m. Study results show the annual attendance of the place by more than a million people, whereas the number of tourists per day can exceed 10,000. The tourist traffic evidently intensifies between June and September. It results in high human pressure on the lake’s waters and surroundings, leading to the degradation of most components of the natural environment. Such high traffic intensity is frequently a nuisance for tourists using the trails themselves. Moreover, high tourist traffic contributes to the intensification of slope processes, resulting in mass movements in the form of debris and snow avalanches, potentially changing the course of the trails.

COSGAP: COntainerized statistical genetics analysis pipelines

Abstract The collection and analysis of sensitive data in large-scale consortia for statistical genetics is hampered by multiple challenges, due to their non-shareable nature. Time-consuming issues in installing software frequently arise due to different operating systems, software dependencies, and limited internet access. For federated analysis across sites, it can be challenging to resolve different problems, including format requirements, data wrangling, setting up analysis on high-performance computing facilities, etc. Easier, more standardized, automated protocols and pipelines can be solutions to overcome these issues. We have developed one such solution for statistical genetic data analysis using software container technologies. This solution, named COSGAP: “COntainerized Statistical Genetics Analysis Pipelines”, consists of already established software tools placed into Singularity containers, alongside corresponding code and instructions on how to perform statistical genetic analyses, such as genome-wide association studies, polygenic scoring, LD score regression, Gaussian Mixture Models, and gene-set analysis. Using provided helper scripts written in Python, users can obtain auto-generated scripts to conduct the desired analysis either on HPC facilities or on a personal computer. COSGAP is actively being applied by users from different countries and projects to conduct genetic data analyses without spending much effort on software installation, converting data formats, and other technical requirements. Availability COSGAP is freely available on GitHub (https://github.com/comorment/containers) under the GPLv3 license.

New statistical framework for interlaboratory evaluation of anti-doping testing results by WADA

AbstractThe World Anti-doping Agency (WADA) International Standard for Laboratories (ISL), developed as part of the World Anti-Doping Program, requires satisfactory laboratory performance in the WADA External Quality Assessment Scheme (EQAS) in order to obtain and maintain WADA accreditation. Under this mandate, WADA regularly distributes urine and blood test samples to anti-doping laboratories to continuously monitor their proficiency. Over the years, WADA has employed classical, generic statistical methods, in accordance to ISO 13528, to evaluate quantitative EQAS results. Here, we set out the rationale for a modern statistical approach that recognizes and addresses the particular features of the measurement results typically obtained in such tests and present an approach involving Bayesian measurement models and statistical data analysis that is tailored specifically to anti-doping testing.

Use possibility analysis for wind energy in autonomous car interior heating

Introduction. When driving cars in winter on intercity routes, problems may arise if the highways are covered with snow as a result of heavy snowfalls, which can last for several days or more, and movement during this period becomes impossible. An analysis of statistical data on weather events in winter has shown that in many regions, the closure of trails as a result of prolonged snowfalls can reach up to fifteen percent. In this case, an autonomous energy source, which it receives through the use of environmental properties, can provide significant assistance in improving the situation and increasing safety. The paper considers the technical solution and carries out a theoretical analysis of its characteristics aimed at solving the problem of autonomous power supply of the car interior in severe weather conditions.Materials and methods. The paper presents a technical solution and a theoretical analysis of its characteristics aimed at solving the problem of autonomous power supply of the car interior in severe weather conditions.Results. Based on the results of the information search, the design of a compact low-power wind power plant is proposed. The calculation of the heat loss of the car interior, the characteristics of a compact wind power plant was performed and the generated power required to heat the car interior in an extreme situation was determined.Discussion and conclusions. It has been established that the presented design of a low-power wind power plant can be used as a prototype for the development of an industrial design of an autonomous energy source for heating a car in extreme conditions. Similar installations can be used in other industries, for example, tourism, agriculture, and geological exploration.

The Effect of Providing Sugarcane Bagasse Compost (Saccharum Sp.) on the Growth of Tomato Plants (Solanum Lycopersicum) in Polybags

This research aims to make bagasse compost an alternative organic material to improve soil properties, making it ideal for the growth of tomato plants. The nutrient content in bagasse compost is N 1.18%, P 1.23%, K 1.90%, C 30.92%, and the C/N ratio is 26.2. The results of the descriptive analysis showed that after four weeks of watering and fertilizing with bagasse compost, the average height of the tomato plants was 45.5 cm, the length of the longest leaf was 5.7 cm, the width of the widest leaf was 3.3 cm, and the number of leaves was 80 pieces. on the plant, the root length was 23 cm, and the wet and dry weight of the plant was 38.35 and 22.81 grams respectively. Based on statistical data analysis, it can be seen that the growth of tomato plants is not affected by the use of bagasse compost. It can be seen that of the seven variables observed, only one variable, namely the widest leaf width, has an influence.

A Comprehensive Approach to Azo Dichlorotriazine Dye Treatment: Assessing the Impact of Physical, Chemical, and Biological Treatment Methods through Statistical Analysis of Experimental Data

This exploration investigates integrated treatment systems combining advanced oxidation processes (Fenton and photo-Fenton) with biological methods for the effective elimination of stubborn organic compounds in simulated textile wastewater composed of azo Dichlorotriazine dye. A comprehensive optimization of key process factors including catalyst dosage, hydrogen peroxide quantity, irradiation duration, etc. was systematically conducted for both Fenton and photo-Fenton processes to realize maximum COD and color removal. Under ideal conditions (0.4 g/L photocatalyst, 1 mL/L H2O2, and 75-Watt UV intensity for 60 min), the photo-Fenton process realized 80% COD elimination and complete decolorization, meeting industrial discharge limits without needing extra biological treatment. Statistical models correlating process parameters to treatment efficiency were developed, giving important design insights. For Fenton, effluent COD exceeded discharge thresholds, so a post-biological treatment using activated sludge was essential to comply with regulations. This integrated Fenton–biological scheme utilizes synergism between chemical and biological processes for enhanced overall treatment. Notable economic benefits were achieved by photo-Fenton over conventional UV-only and UV/H2O2 methods regarding energy consumption and operating costs. Overall, this pioneering work successfully proves integrated advanced oxidation–biological systems as a superior, sustainable alternative to traditional techniques for economically removing obstinate pollutants, such as azo Dichlorotriazine dye, as it is a simulated textile wastewater treatment used to satisfy environmental standards.

Co-seismic deformation and related hazards associated with the 2022 Mw 5.6 Cianjur earthquake in West Java, Indonesia: insights from combined seismological analysis, DInSAR, and geomorphological investigations

IntroductionOn November 21, 2022, a magnitude Mw 5.6 earthquake struck Cianjur Regency in the West Java Province of Indonesia. It was followed by at least 512 aftershocks that persisted from November to June 2023. This seismic event occurred in an area previously unrecognized as an active fault zone. The consequences of this earthquake in Cianjur were severe, leading to both loss of life and extensive structural damage. The substantial damage to buildings was likely a result of abrupt alterations in the local topography due to surface deformation effects.ObjectivesThis research endeavor aims to spatially determine the patterns of ground surface deformation and its relationship with local geomorphological setting due to earthquakes in Cianjur in 2022.MethodsIn this study we conduct seismological analysis of 45 seismic stations, statistical analysis of mainshock and aftershocks data, RADAR Sentinel-1 imagery and employed the DInSAR methodology. Field survey was also conducted to determine the geomorphological characteristics in the study area.ResultsThe outcomes disclosed that the deformation encompassed both subsidence and uplift. The results signify that there was subsidence deformation in the vicinity of Cianjur and its environs during the primary earthquake on November 21, 2022, with an average deformation value of approximately -5 cm. In contrast, the measured deformation during the aftershocks exhibited uplift deformation, with an average value of 10 cm. The examination of deformation patterns amid the 2022 Cianjur earthquake sequence detects elevated deformation values in the vicinity of Cugenang district, with an orientation running from northwest to southeast. The geomorphological investigation conducted indicates that the region of Cianjur encompasses a variety of landforms, such as volcanic, structural, fluvial, and denudational. These landforms exhibit distinct responses to seismic activities. Co-seismic hazards, such as landslides frequently occur as a consequence of seismic events in mountainous terrain.Main ConclusionsSpatio-temporal variation of ground deformation could arise from various causes, such as the number and distribution of aftershocks, stress redistribution, fault interactions, secondary effects, and local geological settings. The mainshocks release accumulated stress along a fault, resulting in particular types of deformation, whereas aftershocks may redistribute stress exhibiting on adjacent faults. Secondary effects triggered by aftershocks, coupled with local geological and geomorphological conditions, further contribute to the diverse patterns of ground deformation observed during seismic events. The results of the study revealed that ground deformation had the greatest impact on fluvial, volcanic, and denudational processes, resulting in notable subsidence and uplift in specific regions. The occurrence and magnitude of co-seismic landslides were triggered by both mainshock and aftershock events, which occurred on weathered geological materials. These effects were further amplified by the simultaneous presence of the rainy season.ImplicationsThe knowledge gained from this research can be applied to evaluate the impacts of earthquakes and to proactively reduce future risks.

Effectiveness of language-related Youtube videos on EFL learning motivation

YouTube is a widely popular platform that offers a vast array of video content. This study aimed to explore the elements of YouTube videos that contribute to sustaining learners’ motivation. A survey was conducted among 349 young adult Indonesian learners. Statistical data analysis revealed that three types of language-related YouTube videos—language lessons, language tips, and language immersions—significantly influenced learners’ motivation to study English. However, language immersion videos exhibited a modestly lower level of effectiveness compared to the other video types. Additionally, it was observed that non-native English-speaker (NNES) videos were more effective in maintaining motivation across all proficiency levels, except for advanced learners, who responded better to native English speaker (NES) videos. Furthermore, the study concluded that videos ranging from 5 to 15 minutes were more effective in sustaining learners’ motivation, as opposed to shorter or longer videos. These findings explain that teachers consider incorporating explicit instruction or tips in their content to enhance learners’ motivation. The findings also indicate that teachers and designers should utilize NNES videos for beginners and intermediate learners, while NES videos may be more effective for advanced learners. Lastly, when choosing instructional videos, the video length should be considered to ensure that learners remain motivated.

Analisis Perbandingan Kinerja Perusahaan Sebelum dan Sesudah Employee Stock Option Program (ESOP) (Studi Empiris pada Perusahaan Manufaktur yang Listing di Bursa Efek Indonesia Tahun 2017-2020)

Implementation of the Employee Stock Option Program in this study aims to compare the company's performance both before and after the implementation of the Employee Stock Option Program for manufacturing companies listed on the IDX in 2017-2020. This research is a manufacturing issuer with as many as 193 companies. Purposive Sampling used in the sampling technique, so that a sample of 11 companies. Available analytical methods include descriptive statistical data analysis, normality test which also uses other tests (paired sample t test), and hypothesis testing with the Paired Sample Test and Wilcoxon test. The results of the study concluded that there were no differences in ROA, ROE, NPM, and TATO before and after the implementation of ESOP in manufacturing companies listed on the IDX for the 2017-2020 period.

The Comparison of Physical and Chemical Properties of Pellets and Briquettes from Hemp (Cannabis sativa L.)

The Comparison of Physical and Chemical Properties of Pellets and Briquettes from Hemp (Cannabis sativa L.)

Planning For Resilience: Examining Gaps in Cyclone Preparedness and Impacts on Marginalized Communities in India's East coast cities

Cyclones and associated storm surges pose a major threat to coastal communities in India, especially along the Bay of Bengal where their intensity is higher. This paper examines cyclone resilience planning in four coastal cities - Visakhapatnam, Puri, Rameshwaram, and Velankanni. A multi-dimensional analysis is undertaken to focus on disaster preparedness, tourism economy contributions, socio-economic inclusion, and sustainability principles. The key objective is to study the integration of cyclone resilience with equitable, tourism-based development to strengthen vulnerable communities through conceptual modeling. The research methodology employs a mixed methods approach combining literature review, secondary data analysis of resilience infrastructure and tourism statistics, and conceptual model development. Findings highlight continued infrastructure and preparedness gaps alongside persisting socio-economic disparities limiting resilience access for marginalized groups. While progress is visible on early warnings, shelters, and evacuations, constraints exist regarding storm-proofing of amenities, customized enterprise support, secure housing, and risk financing tools. The study concludes that resilient, sustainable outcomes require planning processes that engage tourism-dependent communities through bottom-up participation. Coupled with hazard-resilient land use standards, customized livelihood protection schemes, resilient affordable housing programs, and coherent governance; tourism-centric coastal cities can enhance capacities to absorb cyclone impacts and enable inclusive rebuilding. Key Words: Cyclone resilience, Coastal city planning, Socio-economic vulnerabilities, Tourism economies

The Influence of Commitment and Job Satisfaction on Employee Performance in Megamendung Bogor

The aim of this research is to determine the effect of commitment and job satisfaction on employee performance in the Bogor Megamendung detective training. This research uses a quantitative method, namely a research method that is post-positivism, namely researching a certain population or sample, where data collection uses research instruments and statistical data analysis with the aim of testing the hypotheses that have been determined so that direct or indirect relationships between variables can be identified. The number of respondents taken was 55 people. Several data collection methods were used, namely questionnaires, direct observation, literature study, documentation. Technical data analysis uses a Likert scale and regression method through the SPSS program. The research results show data that commitment has a positive effect on employee performance, job satisfaction has a positive effect on employee performance, commitment and job satisfaction have a positive effect on employee performance.

The effect of lean tool on research culture and research performance in Indonesia’s higher education institutions

Quality Assurance in higher education is a lean tool to improve the quality and performance of HEIs, including lecturer research performance. This study examines the effect of implementing Quality Assurance in higher education as a lean tool on the research culture and research performance of lecturers at Indonesia’s private HEIs. The data represent respondents’ perceptions of the research variable indicators. 184 questionnaires were suitable for processing. Data were collected from 184 lecturers from approximately 25 private HEIs in Jakarta, Indonesia. A 5-point Likert scale was used to measure indicators of research variables. Statistical data analysis was carried out using Structural Equation Modeling with the Smart-PLS ™ program. The results show that Quality Assurance as a lean tool has a significant impact on research performance (β = 0.643; p = 0.000) and research culture (β = 0.361; p = 0.000). Research culture affected research performance significantly (β = 0.281; p = 0.000), and research culture significantly mediates the effect of Quality Assurance as a lean tool on the research performance (β = 0.102; p = 0.010), and the effect is strong (Ѵ = 0.181). Research findings reveal that the successful implementation of Quality Assurance as a lean tool is determined more by organizational readiness than individual readiness; this is reflected in the existence of effective research centers. An effective research center will support the standardization of research processes through continuous improvement so that lecturers behave more actively in scientific activities and perform research more productively.

The screening of cannabis addiction using machine learning, MoCA, and anxiety/depression tests

A new cannabis addiction screening approach is developed based on the use of Machine Learning (ML) alongside with psychological and cognitive assessment tests. The Hospital Anxiety and Depression (HAD) test is used to determine the Absence of Anxiety and Depression “No Disorder” or the presence of “Anxiety Only”, “Depression Only”, and both “Anxiety and Depression”. These features are considered to evaluate the psychological effects of cannabis use. In addition to that, the Montreal Cognitive Assessment (MoCA) test is chosen as a feature to assess the cognitive state of the participants. Also, the Age of First Cannabis Use (AFCU) is included as a feature to incorporate participants with no prior cannabis use alongside with those who have used cannabis before. The portion of participants with prior experience consuming cannabis comprises a subset containing passive users and a subset of users that have developed cannabis addiction. This 6-month study was conducted in Marrakech, Morocco in a center affiliated to the National Association of Drug-Risk Reduction of Morocco known as RdR-Maroc with the participation of 146 subjects. The participants in this study are grouped into two groups of 73 participants each. Both case and control groups were clinically assessed by a professional. In this paper, the classical statistical data analysis for the AFCU (M=15.6; SD=2.4), MoCA (M=25.0; SD=2.4), and HAD (58 cases with no disorder, 88 cases with disorder) failed to separate between the two classes. Also, the feature selection for modeling is performed using Spearman correlation, Kendall correlation, and the Odds Ratio (OR). These statistics showed that the selected features were associated to addiction except for “Anxiety Only”. Moreover, ML models such as Logistic Regression (LR), Support Vector Machine (SVM), Artificial Neural Network (ANN), kth-Nearest Neighbor (KNN), and Decision Tree (DT) were used to classify participants into two categories (Addict vs. Non-Addict) based on the selected features mentioned earlier. The Receiver Operating Characteristic (ROC) curve is used to overview the quality of the models and showed that they all captured the nonlinearities underlined in the data. On the other hand, the Area Under the Curve (AUC) allowed the ranking of these models and indicated that the SVM model outperformed all other models with an AUC of 0.97. After that, the SVM model was compared to the Cannabis Use Disorder (CUD) based screening method issued by the fifth edition of the Diagnostic and Statistical Manual of mental disorders (DSM-5). The SVM model's accuracy of 96.6 % outperformed the CUD questionnaires accuracy of 87.7 %. The validity of the proposed approach was investigated where the SVM model presented high validity characteristics (sensitivity=1, specificity=0.93) compared to the CUD questionnaire (sensitivity=0.75, specificity=1). Hence, the proposed approach provided satisfactory results compared to current adopted CUD based screening test. Our findings expand current research on the development of simple and powerful tools for cannabis addiction screening with the purpose of early detection in order to establish preventive and therapeutic strategies that could potentially mitigate the prevalence of cannabis addiction.