Generate Regression Equations Research Articles

The application of information technologies in system of support of decision making in osteopathy

The implementation of information technologies into treatment practice of modern health care significantly increases efficiency of diagnosis and treatment of dorsopathies. The purpose of the study is to develop software module to evaluate post-urological status of patients with spine dorsopathy to optimize diagnostic process and treatment planning. The article describes application of original software module to assess the post-urological status of patients with spine dorsopathy. The proposed software module is designed for objective assessment of post-urological status of patients with spine dorsopathy based on photographic images of examined patient. The most important advantage of software module is built-in forecasting function that is implemented by calculation of severity of pain perceptions and movement disorders using generated regression equations. The possibility to record data obtained during measurements permits to store information in single system. The implementation of software module into clinical practice will contribute to qualitative improvement of diagnostic processes, simplify work of osteopath and reduce the time spent on examination.

Multi-objective optimization and price performance factor evaluation of polyaniline nanofibers-palm oil nanofluids for thermal energy storage application

The application of nanofluid in thermal energy storage technology has attracted interest among researchers in the development of novel nanofluids with high thermal conductivity behavior. Therefore, it is crucial to study the thermal physical behavior of formulated nanofluids prior to extend use in greener energy production. In this study, response surface methodology (RSM) is employed to optimize the density, viscosity and thermal conductivity behavior of formulated polyaniline-palm oil nanofluids. RSM based central composite design (CCD) is applied to extract the significant impact of temperature in the range of 30–60 °C and volume concentration of nanoadditives in the range of 0.01–0.5 vol% to the thermal physical properties of polyaniline-palm oil nanofluids and to generate empirical mathematical model for prediction purpose. Finally, the price performance factor of the studied polyaniline-palm oil nanofluids is evaluated for the first time in this research. Analysis of variance is employed to verify that the generated mathematical regression model is reliable. The formation of 45° angle line in the middle of the predicted vs actual data graph with acceptable R2 of 94.43% for density model, 99.43% for viscosity model, and 94.18% for the thermal conductivity model showing an excellent agreement of both predicted and actual data and verified the reliability of the generated regression equation for response prediction. Optimal density, viscosity and thermal conductivity of polyaniline-palm oil nanofluids found to be 0.8878 g/mL, 25.8251 mPa s and 0.2877 W/mK respectively with the critical parameters for temperature and volume concentration of polyaniline are 60 °C and 0.0347 vol% respectively. The PPF evaluation shows that the higher thermal conductivity of nanofluids are not economical. The formulated polyaniline-palm oil nanofluid evaluated properties expose the possibility of alternative advanced heat transfer fluid for thermal energy storage application due to their superior inherent qualities.

An efficient method for estimating energy losses in distribution's feeder

This paper explains a simple and efficient methodology for calculating monthly energy losses (EL) using the load loss factor technique and a representative composite load profile. One of the important benefits of the proposed work is a simpler, more efficient and less rigorous method to estimate the system-wide energy loss of an extensive distribution network with reasonable accuracy. The sum of all EL provided by each feeder section is used to calculate the total feeder EL. A base case feeder with a typical cable type and power factor is used to generate regression equations, a peak power loss function to estimate the EL. A case study is then used to show the models and techniques that have been established. The result indicates a high level of agreement with the time-series load flow simulations (smaller than 10% deviations). With this model, an approach to estimate the EL of all radial feeders of various configurations and characteristics could be extended and implemented. The spreadsheet approach is ideal for completing a quick energy audit of existing distribution feeder EL and determining the sensitivity of distribution network efficiency to changes in feeder sections and load characteristics.

An efficient method for estimating energy losses in distribution's feeder

This paper explains a simple and efficient methodology for calculating monthly energy losses (EL) using the load loss factor technique and a representative composite load profile. One of the important benefits of the proposed work is a simpler, more efficient and less rigorous method to estimate the system-wide energy loss of an extensive distribution network with reasonable accuracy. The sum of all EL provided by each feeder section is used to calculate the total feeder EL. A base case feeder with a typical cable type and power factor is used to generate regression equations, a peak power loss function to estimate the EL. A case study is then used to show the models and techniques that have been established. The result indicates a high level of agreement with the time-series load flow simulations (smaller than 10% deviations). With this model, an approach to estimate the EL of all radial feeders of various configurations and characteristics could be extended and implemented. The spreadsheet approach is ideal for completing a quick energy audit of existing distribution feeder EL and determining the sensitivity of distribution network efficiency to changes in feeder sections and load characteristics.

B-mode shear wave elastography can be an alternative method to vibration-controlled transient elastography according to a moderate-scale population study.

We aimed to compare vibration-controlled transient elastography (VCTE) with shear wave elastography (SWE) without previous analysis and generate regression equations between VCTE and new point SWE using combination-elastography. Overall, 829 patients with chronic liver disease were enrolled in this study. Patients with a skin-liver capsule distance > 25mm were excluded. The reproducibility of VCTE and SWE was confirmed in a phantom study and a clinical study. Considering that combination-elastography allows measurement based on strain elastography, a similar analysis was performed for the liver fibrosis index (LFI), which is a quantitative value for evaluation of liver fibrosis calculated using strain elastography image features. Regression equations between the VCTE and SWE values were obtained based on linear regression analysis. In the phantom study and clinical study, there was a strong correlation between VCTE and SWE [r = 0.995 (p < 0.001) and r = 0.747 (p < 0.001), respectively). The regression equation between VCTE and SWE was VCTE (kPa) = 1.09 × point SWE (kPa) - 0.17. The Bland-Altman plots revealed no statistically significant bias. Meanwhile, there was no correlation between VCTE and LFI (r = 0.279). There was a statistically significant bias between VCTE and LFI in the Bland-Altman plots. The inter-operator reliability showed a good intraclass correlation coefficient of 0.760 (95% confidence interval: 0.720-0.779). Liver stiffness measured using point SWE was comparable to that measured using VCTE.

The Use of Mathematical and Statistical Analysis in Selecting of Best Regression Equation for Quercus Infectoria G.Olivier

The purpose of this study is to use mathematical and statistical analysis in testing the performance ability of standard volume models in volume prediction of Gall Oak trees. A sample of 205 non - destructive trees was purposely selected from Duhok Governorate, Kurdistan region, Iraq. Of which 157 were used for estimating the parameters of regression models and the rest (48) trees served as validation data. Using computer facilities, the available software packages, and tools including STATGRAPHIC Centurion and Excel tool, the parameters of 28 models were estimated. A multistage procedure was used for screening the generated regression equations and selecting the most appropriate one, which underwent validation with independent data. In this study, a new criterion was proposed and used for testing the accuracy of regression equations in the prediction of the dependent variable. At the end of this process, the regression equation Vt = 0.00442+0.0108D^1.917H was finally selected as the most appropriate one that fits the data.

Regression equations for stature reconstruction from the lower limb bones of contemporary White South Africans

ABSTRACT In 2008, Dayal and colleagues generated regression equations to estimate the total skeletal height (TSH) of White South Africans. However, the validity of these equations has been questioned. The magnetic resonance imaging scanograms of 74 White South African adults were used to assess the reliability of these equations. The physiological lengths of the femur (FEPL) and tibia (TPL) were measured from these scans and input into the appropriate equations by Dayal and colleagues to calculate TSHD. Paired t-tests, mean differences (MD), and mean absolute differences (MAD) were used to compare TSHD with the measured TSH (TSHMeas) taken directly from the scanograms and ELS were compared with the measured stature (LSM) taken of participants prior to their scans. Although there were no significant differences between TSHMeas and TSHD for males and TSHMeas and TSHD(TPL) for females, all ELSL were significantly different to LSM, and the ELSC using the FEPL were significantly different to LSM. These significant differences and associated large MD and MAD conclude that the equations by Dayal and colleagues are no longer valid. New stature estimation equations were derived for the estimation of stature of White South Africans, characterized by strong correlations and low SEEs.

Development of Gender-Specific Equations for Estimating Body Weight and Height Based on Anthropometric Measurements in Adults from Shiraz, Iran

Background: In various situations, such as determining nutrition requirements, medication dosage, mechanical ventilation, and resuscitation, height, weight, and BMI are considered. Anthropometric body measurements differ among populations of different genders and ethnicities. Objectives: This study aimed to develop gender-specific equations for estimating body weight and height based on anthropometric measurements in Iranian adults. Methods: This cross-sectional study was conducted in Shiraz, Iran, over six months. Healthy volunteers aged 18-80 were included. Exclusion criteria were limb(s) amputation or immobilization and pregnancy. Participants were randomly divided into modeling (n = 400) and validation (n = 78) groups. We used the modeling group to generate regression equations based on gender and the validation group to test them. Results: Demi-span, age, knee height, and arm span could predict height with reasonable accuracy. Calf, waist, neck, and wrist circumferences entered our regression for predicting weight. Waist and calf circumferences entered the regression for BMI prediction in both genders. Arm circumference in men and neck circumference in women is strongly correlated with BMI. Conclusions: Many different equations have been suggested to predict height, weight, and BMI. Linear and circumferential body measures are usually used to predict height and weight. The suggested equations in this study are simple, and the anthropometric measurements require only a cloth tape measure and have good predictive ability. Complimentary studies are necessary to evaluate the precision of these formulas in other samples from other regions of Iran and in immobilized patients.

Body size estimation of Caimaninae specimens from the Miocene of South America

Living crocodylians are frequently regarded as morphologically and ecologically conservative, contrasting with the group's rich fossil record, which reveals a much higher diversity. In particular, Caimaninae is a striking example of such diversity, with only six extant species but a myriad of extinct taxa, exhibiting remarkable morphological variation. Their skulls vary substantially, with robust and flattened shapes, ranging from short to long snouts, and serve as a basis for many evolutionary studies in the group. Previous works have demonstrated that the skull is a good proxy to estimate the body size of extinct crocodylians. In this study, we estimate the body size of large Caimaninae specimens from the Miocene of South America, including Purussaurus and Mourasuchus. For that, we elaborated a comprehensive dataset of body size data collected from living crocodylians to generate regression equations. We performed regression analyses both including and excluding juvenile/subadult specimens, to account for the possible influence of ontogeny on the relationship between cranial measurements and body size. Furthermore, we also employed two different approaches (phylogenetic and non-phylogenetic) for estimating the body size of these Miocene caimanines. Our results indicate a significant influence of ontogeny on the body proportions of crocodylians, suggesting that datasets used for estimating the body size of extinct taxa should not include juvenile specimens. Moreover, the phylogenetic approach provided more conservative estimates, possibly as a result of the phylogenetic position of the analyzed taxa, given that the body size metrics are strongly phylogenetically structured in crocodylians. This is the first study to infer the body size of fossil caimanines using different methods and skeletal measurements, as well as a dataset comprised of solely adult crocodylians. In the light of our results, we also discuss the paleobiological implications of the large size of these Miocene caimanines.

Development and validation of rapid and cost-effective protocol for estimation of amylose and amylopectin in maize kernels.

Maize possesses wide variation in amylose and amylopectin which assumes significance as a part of both food-chain and different industrial applications. Estimation of amylose and amylopectin in maize kernels is important for developing suitable hybrids. The existing protocols for estimation of amylose and amylopectin in maize are elaborate and lengthy, and involve high cost. Here, we developed a rapid and cost-effective method for estimation of amylose and amylopectin in maize kernels. 10% toluene and 80% ethanol were used for removal of proteins (~ 10%) and lipids (~ 4%) from maize flour. The over-estimation of amylose was minimized using NaOH with KI to stop free KI to bind with amylopectin. Standards were improved by mixing amylose and amylopectin in different concentrations (0-100%), rather than using amylose or amylopectin alone. Standard curve generated regression equation of y = 90.436x + 0.8535 with R 2 = 0.9989. Two types of samples viz., (1) protein, amylose and amylopectin (2) amylose and amylopectin, showed thatstarch fractions were highly comparable to expected values with correlation coefficient (r) of 0.9998 and mean standard deviation of 0.54. The protocol successfully estimated wide range of amylose (2.79-50.04%) and amylopectin (59.96-97.21%) among diverse maize inbreds including amylose extender1 (ae1) and waxy1 (wx1) mutants. Present protocol required 75% less time and 92.5% less cost compared to existing protocols. The newly developed method would be highly useful in developing maize hybrids high in amylose or amylopectin. This is the first report of rapid and cost-effective protocol for estimation of starch fractions in maize kernels.

Enhanced synergistic antitumor efficacy with topotecan (camptothecin derivative) and curcumin analogs coadministration in novel proniosomal formulations

Background: In the modern era of therapeutics, the proniosomal system has been identified as the most intriguing one among various novel systems, thus considerably enhancing the bioavailability of low-soluble drugs. The current study aimed to study the enhancement of therapeutic efficacy of topotecan (TPT) with curcumin (CUR) coadministration. Materials and Methods: We optimized the preparation of niosomes, concerning concentrations of lecithin, span 60, and cholesterol. Seventeen trials were proposed by the selected design. All these batches were initially evaluated only for entrapment efficacy (EE), vesicle size (VS), and percentage of TPT release by the end of 12 h. Analysis of variance and generated regression equations were assisted to study the significant variables and magnitude of impact. Results: The desirability of 0.893 was achieved with the optimum concentrations of selected independent variables in attaining the highest EE (90.393%), minimum VS (386.264 nm), and percentage of TPT release (98.614% at 12 h). TPT and CUR release from the optimized formulation were found to be anomalous or non-Fickian diffusion, as evident from the n value of Peppas model. The cytotoxic studies demonstrated that TPT and CUR in liposomal and free forms were found to be less cytotoxic on MCF-7 model cells. All these findings indicate that the coadministration of CUR with TPT proniosomes can be a promising strategy to enhance the antitumor treatment.

Stakeholders' impact on the leadership potential of small and medium-sized construction enterprises

PurposeThis study aimed to develop a methodological approach to assessing the impact of stakeholders on leadership potential of small and medium-sized construction enterprises.Design/methodology/approachThe research methodology was based on taxonomic analysis to determine the coefficient of leadership potential in the following areas: financial growth of an enterprise, internal processes, human resources development and market potential. The examination process was grounded on the materials from small and medium-sized construction companies located in Russia and China.FindingsSubgroups of companies with positive dynamics of indicators, an unstable situation and negative trends of leadership potential formation are identified. Russian small and medium-sized construction companies prioritize the development of sales policies and the management of internal business processes, while Chinese companies–human potential. The generated regression equations indicate a direct relationship between stakeholder engagement and the leadership potential of construction companies in both countries.Originality/valueThe scientific contribution of this study is the proposed methodological approach to assessing the development of the leadership potential of an enterprise and diagnosing the degree of stakeholders' influence on the latter. This is facilitated by comprehensive analysis, which includes an assessment of leadership potential based on the results of taxonomic analysis, construction of vector diagrams and regression analysis. This study can be useful for persons conducting research in the direction of small and medium-sized business management, forming a strategy for business development and competition policy to form a company's leadership position in the market.

Left ventricular longitudinal wall fractional shortening accurately predicts longitudinal strain in critically ill patients with septic shock

BackgroundLeft ventricular longitudinal strain (LVLS) may be a sensitive indicator of left ventricular (LV) systolic function in patients with sepsis, but is dependent on high image quality and analysis software. Mitral annular plane systolic excursion (MAPSE) and the novel left ventricular longitudinal wall fractional shortening (LV-LWFS) are bedside echocardiographic indicators of LV systolic function that are less dependent on image quality. Both are sparsely investigated in the critically ill population, and may potentially be used as surrogates for LVLS. We assessed if LVLS may be predicted by LV-LWFS and MAPSE in patients with septic shock. We also assessed the repeatability and inter-rater agreement of LVLS, LV-LWFS and MAPSE measurements.Results122 TTE studies from 3 echocardiographic data repositories of patients admitted to ICU with septic shock were retrospectively assessed, of which 73 were suitable for LVLS analysis using speckle tracking. The correlations between LVLS vs. LV-LWFS and LVLS vs. MAPSE were 0.89 (p < 0.001) and 0.81 (p < 0.001) with mean squared errors of 5.8% and 9.1%, respectively. Using the generated regression equation, LV-LWFS predicted LVLS with a high degree of accuracy and precision, with bias and limits of agreement of -0.044 ± 4.7% and mean squared prediction error of 5.8%. Interobserver repeatability was good, with high intraclass correlation coefficients (0.96–0.97), small bias and tight limits of agreement (≤ 4.1% for all analyses) between observers for all measurements.ConclusionsLV-LWFS may be used to estimate LVLS in patients with septic shock. MAPSE also performed well, but was slightly inferior compared to LV-LWFS in estimating LVLS. Feasibility of MAPSE and LV-LWFS was excellent, as was interobserver repeatability.

Reexamining Relative Bar Performance as a Function of Non-Linearity, Heteroscedasticity, and a New Independent Variable

One might think that if a law school’s graduates do better on the bar exam than their credentials on entering law school would have predicted, the law school’s faculty must have done a good job. Indeed, some scholarship makes that claim. But it is empirically untrue. What actually yields such superficially impressive results is not pedagogy but rather prestidigitation. When law schools manipulate their matriculant pools via academic attrition and transfer, that sleight of hand improves their bar performance rates. This article reveals the math behind the magic. We challenge the assertion that effective pedagogy is the primary driver of a school’s overperformance on the bar examination by demonstrating the model misspecification of the linear regressions in support of that assertion. Our analyses, based on original code written for the program Mathematica, generate regression equations that clearly illustrate the error of applying linear regression to heteroscedastic, non-linear data, and the bias in favor of schools with mid-range LSAT and UGPA matriculants this misapplication causes. Over and under performance on the bar examination, relative to the entering credentials of a school’s matriculants, can be explained in large part by combining the institutions’ academic attrition and net transfer rates into a single independent variable. We demonstrate the marked difference in the value of this variable between schools identified as overperforming and those identified as underperforming their matriculation credentials on the bar examination. The article concludes by emphasizing the harm to legal education that stems from the unwarranted attribution of bar success to pedagogy and especially the harm this causes to untenured academic support faculty. We also raise the question of whether ABA standard 316-mandating a certain level of bar passage by law schools’ graduates-is ethically and morally supportable given the ability of schools to manipulate bar passage rates by modulating academic attrition and transfer rates.

Optimization of machining parameters in abrasive water jet cutting of stainless steel 304

Abrasive waterjet cutting is a newer machining process effectively used for cutting various materials ranging from soft materials like rubber to hard materials like Inconel. This paper addresses the influence of input process parameters on material removal rate and kerf top width in processing stainless steel grade 304. The main input parameters are water jet pressure, feed rate and abrasive flow rate. Three different levels of input parameters are selected to generate a design table using L27 orthogonal array. Experiments were conducted and the effect of input parameters on output responses are studied.. The optimum values of the parameters found using Grey Relational Analysis and Response Surface Methodology are in accordance with each other. A study of the response graph shows that Material Removal Rate is influenced by Water Jet Pressure and Feed Rate while the influencing factors for Kerf Top Width are Feed Rate and Abrasive Flow Rate. The optimum parameter values are also used in the generated Regression Equations and the resulting responses have been validated with the experimental values. The validation showed that the error between the experimental and regression equation values are within limits and so the regression equations can be used for calculations.

Converting and Standardizing Various Measures of Arterial Stiffness to Pulse Wave Velocity

Background: A variety of arterial stiffness measures have been used to assess the impacts of disease states and various interventions without clear consensus among them. One of the primary problems faced by investigators conducting systematic reviews and meta-analyses is the lack of standardized methodology with a same unit to evaluate and compare investigations using different arterial stiffness measures. Therefore, the purpose of this study was to derive and summarize standardized equations to convert commonly used image-based measures of arterial stiffness to local pulse wave velocity (PWV). Methods: We first conducted a literature search to obtain and summarize conversion equations in the published literature such that these equations can be found in one convenient location. Then, we generated regression equations using the data collected in a well-controlled laboratory-based study, in which all measures of arterial stiffness were obtained in 49 apparently healthy participants. Results: All literature-based conversion equations produced similar local PWV values and were moderately and significantly correlated with directly measured carotid-femoral PWV (cfPWV) with a Pearson’s r ranging from 0.41 to 0.50. The local PWV using laboratory-based equations were modestly associated with cfPWV (r = 0.39–0.49) with an exception of incremental elastic modulus (r = 0.15, p > 0.05). Conclusion: Commonly used measures of ultrasound-based arterial stiffness can be converted to local PWV and compared with a reference standard measure of arterial stiffness.

Testing regression and mean model approaches to facial soft-tissue thickness estimation.

Average facial soft-tissue thickness (FSTT) databanks are continuously developed and applied within craniofacial identification. This study considered and tested a subject-specific regression model alternative for estimating the FSTT values for oral midline landmarks using skeletal projection measurements. Measurements were taken from cone-beam computed tomography scans of 100 South African individuals (60 male, 40 female; Mage = 35 years). Regression equations incorporating sex categories were generated. This significantly improved the goodness-of-fit (r2-value). Validation tests compared the constructed regression models with mean FSTT data collected from this study, existing South African FSTT data, a universal total weighted mean approach with pooled demographic data and collection techniques and a regression model approach that uses bizygomatic width and maximum cranial breadth dimensions. The generated regression equations demonstrated individualised results, presenting a total mean inaccuracy (TMI) of 1.53 mm using dental projection measurements and 1.55 mm using cemento-enamel junction projection measurements. These slightly outperformed most tested mean models (TMI ranged from 1.42 to 4.43 mm), and substantially outperformed the pre-existing regression model approach (TMI = 5.12 mm). The newly devised regressions offer a subject-specific solution to FSTT estimation within a South African population. A continued development in sample size and validation testing may help substantiate its application within craniofacial identification.

Impact of physico‐geographical factors and climate variability on flow intermittency in the rivers of water surplus zone

AbstractClimate change is inevitably altering the hydrological regime of water bodies. The interest in changing behaviour of intermittent rivers is increasing in many countries. This research was focused on intermittent rivers (rivers which naturally, periodically cease to flow) in Lithuania. The purpose of this research was to provide an overview of flow intermittency phenomena according to available data in a historical period and to evaluate the impact of catchment geographical features and climate variability on zero‐flow events. The calculated indices of flow intermittency showed that the selected rivers had very different flow regimes. The threshold for the separation of typically intermittent rivers from only occasionally intermittent ones was suggested. Multiple linear regression analysis defined the crucial role of catchment size and watercourse slope on the river cessation process in Lithuania. The applied non‐parametric Wilcoxon–Mann–Whitney test revealed the significance of the relationship between precipitation (in June–September) and zero‐flow duration. Flow intermittency phenomena in Lithuanian rivers were linked to a low‐frequency teleconnection pattern (SCAND index). A methodology of estimating the relation between river intermittency and large‐scale atmospheric circulation pattern (based on SCAND index) was created. The generated regression equations between flow intermittency indices and catchment characteristics might be useful for the estimation of zero‐flows in ungauged river catchments. The main aspect of future investigations might be related to forecasting flow intermittency using modern hydrological models and climate scenarios as well as the defined relationships between zero‐flow indices and physico‐geographical features of river catchments.

Prediction of Spirometric Indices Using Forced Oscillometric Indices in Patients with Asthma, COPD, and Interstitial Lung Disease.

Background and ObjectiveSpirometry is sometimes difficult to perform in elderly patients and patients with cognitive impairment. Forced oscillometry (FOT) is a simple, noninvasive technique used for measuring respiratory impedance. The aim of this study was to develop regression equations to estimate vital capacity (VC), forced vital capacity (FVC), and forced expiratory volume in 1 s (FEV1.0) on the basis of FOT indices and to evaluate the accuracy of these equations in patients with asthma, chronic obstructive pulmonary disease (COPD), and interstitial lung disease (ILD).Materials and MethodsWe retrospectively included data on 683 consecutive patients with asthma (388), COPD (128), or ILD (167) in this study. We generated regression equations for VC, FVC, and FEV1.0 by multivariate linear regression analysis and used them to estimate the corresponding values. We determined whether the estimated data reflected spirometric indices.ResultsActual and estimated VC, FVC, and FEV1.0 values showed significant correlations (all r > 0.8 and P < 0.001) in all groups. Biases between the actual data and estimated data for VC, FVC, and FEV1.0 in the asthma group were −0.073 L, −0.069 L, and 0.017 L, respectively. The corresponding values were −0.064 L, 0.027 L, and 0.069 L, respectively, in the COPD group and −0.040 L, −0.071 L, and −0.002 L, respectively, in the ILD group. The estimated data in the present study did not completely correspond to the actual data. In addition, sensitivity for an FEV1.0/FVC ratio of <0.7 and the diagnostic accuracy for the classification of COPD grade using estimated data were low.ConclusionThese results suggest that our method is not highly accurate. Further studies are needed to generate more accurate regression equations for estimating spirometric indices based on FOT measurements.

Equations To Predict Antimicrobial MICs in Neisseria gonorrhoeae Using Molecular Antimicrobial Resistance Determinants.

The emergence of Neisseria gonorrhoeae strains that are resistant to azithromycin and extended-spectrum cephalosporins represents a public health threat, that of untreatable gonorrhea infections. Multivariate regression modeling was used to determine the contributions of molecular antimicrobial resistance determinants to the overall antimicrobial MICs for ceftriaxone, cefixime, azithromycin, tetracycline, ciprofloxacin, and penicillin. A training data set consisting of 1,280 N. gonorrhoeae strains was used to generate regression equations which were then applied to validation data sets of Canadian (n = 1,095) and international (n = 431) strains. The predicted MICs for extended-spectrum cephalosporins (ceftriaxone and cefixime) were fully explained by 5 amino acid substitutions in PenA, A311V, A501P/T/V, N513Y, A517G, and G543S; the presence of a disrupted mtrR promoter; and the PorB G120 and PonA L421P mutations. The correlation of predicted MICs within one doubling dilution to phenotypically determined MICs of the Canadian validation data set was 95.0% for ceftriaxone, 95.6% for cefixime, 91.4% for azithromycin, 98.2% for tetracycline, 90.4% for ciprofloxacin, and 92.3% for penicillin, with an overall sensitivity of 99.9% and specificity of 97.1%. The correlations of predicted MIC values to the phenotypically determined MICs were similar to those from phenotype MIC-only comparison studies. The ability to acquire detailed antimicrobial resistance information directly from molecular data will facilitate the transition to whole-genome sequencing analysis from phenotypic testing and can fill the surveillance gap in an era of increased reliance on nucleic acid assay testing (NAAT) diagnostics to better monitor the dynamics of N. gonorrhoeae.