Displaying publications 41 - 58 of 58 in total

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  1. Mohd Ali SH, Omar N, Shafie MS, Nik Ismail NA, Hadi H, Nor FM
    Anat Cell Biol, 2020 Mar;53(1):27-35.
    PMID: 32274246 DOI: 10.5115/acb.19.135
    Research in forensic anthropology is recent in Malaysia due to limited access to documented skeletal collections. However, advanced imaging techniques provide virtual bone samples for use in morphometric studies to establish population-specific standards by virtual anthropology. This study examined sexual dimorphism in the subpubic angle using a three-dimensional computed tomography model of the pelvis, in a contemporary Malaysian population. The sample comprised multidetector computed tomography (MDCT) scans of 50 male and 50 female adults. Segmentation of the MDCT scans was performed using 3D Slicer, and four landmarks were acquired using Stratovan Checkpoint for the subpubic angle measurement. The technical error of measurement (TEM), relative TEM, and coefficient of reliability (R) exhibited high reliability in measurements. Results showed that the subpubic angle in males was 68.6°±7.6° and in females 87.4°±6.5°. The subpubic angle in females was significantly larger than in males (P<0.001). Inverse correlation was found between the subpubic angle and age, in both males (r=-0.449, P<0.01) and females (r=-0.385, P<0.01). The overall accuracy of sex estimation using the subpubic angle was 94% (P<0.001). The subpubic angle, with a demarcating point of 78.6°, showed a sensitivity and specificity of 94% in the classification of female individuals. In conclusion, sex estimation using the subpu bic angle is highly accurate, with a high degree of expected sensitivity and specificity in the Malaysian population.
  2. Abdul Wahab P, Mohd Yusoff D, Abdul Kadir A, Ali SH, Yeong Yeh L
    Clin Nurs Res, 2022 Feb;31(2):348-355.
    PMID: 34340590 DOI: 10.1177/10547738211033934
    This study aimed to determine the prevalence, symptoms, and associated factors of chronic constipation among older adults in the North-East of Peninsular Malaysia. A cross-sectional study was conducted among older patients from four health clinics. A total of 400 older patients participated, with a mean age of 68.7 (SD = 6.4) years. The prevalence of chronic constipation was 14.8%. The highest symptom reported was the inability to pass stool (98.3%). Chronic constipation was significantly associated with older age (OR = 2.97; 95% CI [1.17, 7.54]; p = .022), inadequate plain water intake per day (OR = 2.13; 95% CI [1.13, 4.02]; p = .020), hypertension (OR = 2.22; 95% CI [1.07, 4.61]; p = .033), and hyperlipidemia (OR = 2.52; 95% CI [1.24, 5.11]; p = .010). Identification of chronic constipation should be done as part of routine clinic visits, especially for older patients with cardiovascular disease.
  3. Hussein-Al-Ali SH, Abudoleh SM, Hussein MZ, Bullo S, Palanisamy A
    IET Nanobiotechnol, 2021 Feb;15(1):79-89.
    PMID: 34694731 DOI: 10.1049/nbt2.12009
    In this study, ellagic acid (ELA), a skin anticancer drug, is capped on the surface(s) of functionalised graphene oxide (GO) nano-sheets through electrostatic and π-π staking interactions. The prepared ELA-GO nanocomposite have been thoroughly characterised by using eight techniques: Fourier-transform infrared spectroscopy (FTIR), zeta potential, X-ray diffraction (XRD), thermogravimetric analysis (TGA), Raman spectroscopy, atomic force microscopy (AFM) topographic imaging, transmission electron microscopy (TEM), and surface morphology via scanning electron microscopy (SEM). Furthermore, ELA drug loading and release behaviours from ELA-GO nanocomposite were studied. The ELA-GO nanocomposite has a uniform size distribution averaging 88 nm and high drug loading capacity of 30 wt.%. The in vitro drug release behaviour of ELA from the nanocomposite was investigated by UV-Vis spectrometry at a wavelength of λmax 257 nm. The data confirmed prolonged ELA release over 5000 min at physiological pH (7.4). Finally, the IC50 of this ELA-GO nanocomposite was found to be 6.16 µg/ml against B16 cell line; ELA and GO did not show any cytotoxic effects up to 50 µg/ml on the same cell lines.
  4. Kamba SA, Ismail M, Hussein-Al-Ali SH, Ibrahim TA, Zakaria ZA
    Molecules, 2013 Aug 30;18(9):10580-98.
    PMID: 23999729 DOI: 10.3390/molecules180910580
    Drug delivery systems are designed to achieve drug therapeutic index and enhance the efficacy of controlled drug release targeting with specificity and selectivity by successful delivery of therapeutic agents at the desired sites without affecting the non-diseased neighbouring cells or tissues. In this research, we developed and demonstrated a bio-based calcium carbonate nanocrystals carrier that can be loaded with anticancer drug and selectively deliver it to cancer cells with high specificity by achieving the effective osteosarcoma cancer cell death without inducing specific toxicity. The results showed pH sensitivity of the controlled release characteristics of the drug at normal physiological pH 7.4 with approximately 80% released within 1,200 min but when exposed pH 4.8 the corresponding 80% was released in 50 min. This study showed that the DOX-loaded CaCO₃ nanocrystals have promising applications in delivery of anticancer drugs.
  5. Hussein-Al-Ali SH, Abudoleh SM, Abualassal QIA, Abudayeh Z, Aldalahmah Y, Hussein MZ
    IET Nanobiotechnol, 2022 May;16(3):92-101.
    PMID: 35332980 DOI: 10.1049/nbt2.12081
    Silver nanoparticles (AgNPs) have shown potential applications in drug delivery. In this study, the AgNPs was prepared from silver nitrate in the presence of alginate as a capping agent. The ciprofloxacin (Cipro) was loaded on the surface of AgNPs to produce Cipro-AgNPs nanocomposite. The characteristics of the Cipro-AgNPs nanocomposite were studied by X-ray diffraction (XRD), UV-Vis, transmission electron microscopy (TEM), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), Fourier-transform infra-red analysis (FT-IR) and zeta potential analyses. The XRD of AgNPs and Cipro-AgNPs nanocomposite data showed that both have a crystalline structure in nature. The FT-IR data indicate that the AgNPs have been wrapped by the alginate and loaded with the Cipro drug. The TEM image showed that the Cipro-AgNPs nanocomposites have an average size of 96 nm with a spherical shape. The SEM image for AgNPs and Cipro-AgNPs nanocomposites confirmed the needle-lumpy shape. The zeta potential for Cipro-AgNPs nanocomposites exhibited a positive charge with a value of 6.5 mV. The TGA for Cipro-AgNPs nanocomposites showed loss of 79.7% in total mass compared to 57.6% for AgNPs which is due to the Cipro loaded in the AgNPs. The release of Cipro from Cipro-AgNPs nanocomposites showed slow release properties which reached 98% release within 750 min, and followed the Hixson-Crowell kinetic model. In addition, the toxicity of AgNPs and Cipro-AgNPs nanocomposites was evaluated using normal (3T3) cell line. The present work suggests that Cipro-AgNPs are suitable for drug delivery.
  6. Al-Qazzaz NK, Sabir MK, Bin Mohd Ali SH, Ahmad SA, Grammer K
    J Healthc Eng, 2021;2021:8537000.
    PMID: 34603651 DOI: 10.1155/2021/8537000
    Investigating gender differences based on emotional changes becomes essential to understand various human behaviors in our daily life. Ten students from the University of Vienna have been recruited by recording the electroencephalogram (EEG) dataset while watching four short emotional video clips (anger, happiness, sadness, and neutral) of audiovisual stimuli. In this study, conventional filter and wavelet (WT) denoising techniques were applied as a preprocessing stage and Hurst exponent (Hur) and amplitude-aware permutation entropy (AAPE) features were extracted from the EEG dataset. k-nearest neighbors (kNN) and support vector machine (SVM) classification techniques were considered for automatic gender recognition from emotional-based EEGs. The main novelty of this paper is twofold: first, to investigate Hur as a complexity feature and AAPE as an irregularity parameter for the emotional-based EEGs using two-way analysis of variance (ANOVA) and then integrating these features to propose a new CompEn hybrid feature fusion method towards developing the novel WT_CompEn gender recognition framework as a core for an automated gender recognition model to be sensitive for identifying gender roles in the brain-emotion relationship for females and males. The results illustrated the effectiveness of Hur and AAPE features as remarkable indices for investigating gender-based anger, sadness, happiness, and neutral emotional state. Moreover, the proposed WT_CompEn framework achieved significant enhancement in SVM classification accuracy of 100%, indicating that the novel WT_CompEn may offer a useful way for reliable enhancement of gender recognition of different emotional states. Therefore, the novel WT_CompEn framework is a crucial goal for improving the process of automatic gender recognition from emotional-based EEG signals allowing for more comprehensive insights to understand various gender differences and human behavior effects of an intervention on the brain.
  7. Hussein-Al-Ali SH, El Zowalaty ME, Hussein MZ, Ismail M, Webster TJ
    Int J Nanomedicine, 2014;9:549-57.
    PMID: 24549109 DOI: 10.2147/IJN.S53079
    This study describes the preparation, characterization, and controlled release of a streptomycin-chitosan-magnetic nanoparticle-based antibiotic in an effort to improve the treatment of bacterial infections. Specifically, chitosan-magnetic nanoparticles were synthesized by an incorporation method and were characterized by Fourier transform infrared spectroscopy, X-ray diffraction, thermogravimetric analysis, and vibrating sample magnetometry. Streptomycin was incorporated into the nanoparticles to form a streptomycin-coated chitosan-magnetic nanoparticle (Strep-CS-MNP) nanocomposite. The release profiles showed an initially fast release, which became slower as time progressed. The percentage of drug released after 350 minutes was around 100%, and the best fit mathematical model for drug release was the pseudo-second order model. The Strep-CS-MNP nanocomposite showed enhanced antibacterial activity against methicillin-resistant Staphylococcus aureus. This study forms a significant basis for further investigation of the Strep-CS-MNP nanocomposite in the treatment of various bacterial infections.
  8. Zhang H, Ramamoorthy A, Rengarajan T, Iyappan P, Alahmadi TA, Wainwright M, et al.
    J Biochem Mol Toxicol, 2024 Jan;38(1):e23578.
    PMID: 37927152 DOI: 10.1002/jbt.23578
    Lung cancer is one of the most common cancers in men. Although many diagnostic and treatment regimens have been followed in the treatment for lung cancer, increasing mortality rate due to lung cancer is depressing and hence requires alternative plant based therapeutics with with less side-effects. Myrtenol exhibits anti-inflammatory and antioxidant properties. Hence we intended to study the effect of Myrtenol on B(a)P-induced lung cancer. Our study showed that B(a)P lowered hematological count, decreased phagocyte and avidity indices, nitroblue tetrazolium (NBT) reduction, levels of immunoglubulins, antioxidant levels, whereas Myrtenol treatment restored them back to normal levels. On the other hand, xenobiotic and liver dysfunction marker enzymes and pro-inflammatory cytokines were elevated on B(a)P exposure, which retuned back to normal by Myrtenol. This study thus describes the immunomodulatory and antioxidant effects of Myrtenol on B[a]P-induced immune destruction.
  9. Cheah KJ, Abdul Manaf Z, Fitri Mat Ludin A, Razalli NH, Mohd Mokhtar N, Md Ali SH
    JMIR Mhealth Uhealth, 2024 Mar 12;12:e49055.
    PMID: 38532298 DOI: 10.2196/49055
    BACKGROUND: The success of mobile apps in improving the lifestyle of patients with noncommunicable diseases through self-management interventions is contingent upon the emerging growth in this field. While users of mobile health (mHealth) apps continue to grow in number, little is known about the quality of available apps that provide self-management for common noncommunicable diseases such as diabetes, hypertension, and obesity.

    OBJECTIVE: We aimed to investigate the availability, characteristics, and quality of mHealth apps for common noncommunicable disease health management that included dietary aspects (based on the developer's description), as well as their features for promoting health outcomes and self-monitoring.

    METHODS: A systematic search of English-language apps on the Google Play Store (Google LLC) and Apple App Store (Apple Inc) was conducted between August 7, 2022, and September 13, 2022. The search terms used included weight management, obesity, diabetes, hypertension, cardiovascular diseases, stroke, and diet. The selected mHealth apps' titles and content were screened based on the description that was provided. Apps that were not designed with self-management features were excluded. We analyzed the mHealth apps by category and whether they involved health care professionals, were based on scientific testing, and had self-monitoring features. A validated and multidimensional tool, the Mobile App Rating Scale (MARS), was used to evaluate each mHealth app's quality based on a 5-point Likert scale from 1 (inadequate) to 5 (excellent).

    RESULTS: Overall, 42 apps were identified. Diabetes-specific mHealth apps accounted for 7% (n=3) of the market, hypertension apps for 12% (n=5), and general noncommunicable disease management apps for 21% (n=9). About 38% (n=16) of the apps were for managing chronic diseases, while 74% (n=31) were for weight management. Self-management features such as weight tracking, BMI calculators, diet tracking, and fluid intake tracking were seen in 86% (n=36) of the apps. Most mHealth apps (n=37, 88%) did not indicate whether there was involvement of health professionals in app development. Additionally, none of the apps reported scientific evidence demonstrating their efficacy in managing health. The overall mean MARS score was 3.2 of 5, with a range of 2.0 to 4.1. Functionality was the best-rated category (mean score 3.9, SD 0.5), followed by aesthetics (mean score 3.2, SD 0.9), information (mean score 3.1, SD 0.7), and engagement (mean score 2.9, SD 0.6).

    CONCLUSIONS: The quality of mHealth apps for managing chronic diseases was heterogeneous, with roughly half of them falling short of acceptable standards for both quality and content. The majority of apps contained scant information about scientific evidence and the developer's history. To increase user confidence and accomplish desired health outcomes, mHealth apps should be optimized with the help of health care professionals. Future studies on mHealth content analysis should focus on other diseases as well.

  10. Hussein-Al-Ali SH, El Zowalaty ME, Kura AU, Geilich B, Fakurazi S, Webster TJ, et al.
    Biomed Res Int, 2014;2014:651831.
    PMID: 24900976 DOI: 10.1155/2014/651831
    Nystatin is a tetraene diene polyene antibiotic showing a broad spectrum of antifungal activity. In the present study, we prepared a nystatin nanocomposite (Nyst-CS-MNP) by loading nystatin (Nyst) on chitosan (CS) coated magnetic nanoparticles (MNPs). The magnetic nanocomposites were characterized by X-ray powder diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), thermogravimetry analysis (TGA), vibrating sample magnetometer (VSM), and scanning electron microscopy (SEM). The XRD results showed that the MNPs and nanocomposite are pure magnetite. The FTIR analysis confirmed the binding of CS on the surface of the MNPs and also the loading of Nyst in the nanocomposite. The Nyst drug loading was estimated using UV-Vis instrumentation and showing a 14.9% loading in the nanocomposite. The TEM size image of the MNPs, CS-MNP, and Nyst-CS-MNP was 13, 11, and 8 nm, respectively. The release profile of the Nyst drug from the nanocomposite followed a pseudo-second-order kinetic model. The antimicrobial activity of the as-synthesized Nyst and Nyst-CS-MNP nanocomposite was evaluated using an agar diffusion method and showed enhanced antifungal activity against Candida albicans. In this manner, this study introduces a novel nanocomposite that can decrease fungus activity on-demand for numerous medical applications.
  11. Dorniani D, Kura AU, Hussein-Al-Ali SH, bin Hussein MZ, Fakurazi S, Shaari AH, et al.
    ScientificWorldJournal, 2014;2014:972501.
    PMID: 24895684 DOI: 10.1155/2014/972501
    The coating of an active drug, 6-mercaptopurine, into the iron oxide nanoparticles-polyethylene glycol (FNPs-PEG) in order to form a new nanocomposite, FPEGMP-2, was accomplished using coprecipitation technique. The resulting nanosized with a narrow size distribution magnetic polymeric particles show the superparamagnetic properties with 38.6 emu/g saturation magnetization at room temperature. Fourier transform infrared spectroscopy and the thermal analysis study supported the formation of the nanocomposite and the enhancement of thermal stability in the resulting nanocomposite comparing with its counterpart in free state. The loading of 6-mercaptopurine (MP) in the FPEGMP-2 nanocomposite was estimated to be about 5.6% and the kinetic experimental data properly correlated with the pseudo-second order model. Also, the release of MP from the FPEGMP-2 nanocomposite shows the sustained release manner which is remarkably lower in phosphate buffered solution at pH 7.4 than pH 4.8, due to different release mechanism. The maximum percentage release of MP from the nanocomposite reached about 60% and 97% within about 92 and 74 hours when exposed to pH 7.4 and 4.8, respectively.
  12. Dorniani D, Kura AU, Hussein-Al-Ali SH, Bin Hussein MZ, Fakurazi S, Shaari AH, et al.
    ScientificWorldJournal, 2014;2014:416354.
    PMID: 24737969 DOI: 10.1155/2014/416354
    The efficacy of two nanocarriers polyethylene glycol and polyvinyl alcohol magnetic nanoparticles coated with gallic acid (GA) was accomplished via X-ray diffraction, infrared spectroscopy, magnetic measurements, thermal analysis, and TEM. X-ray diffraction and TEM results showed that Fe3O4 nanoparticles were pure iron oxide having spherical shape with the average diameter of 9 nm, compared with 31 nm and 35 nm after coating with polyethylene glycol-GA (FPEGG) and polyvinyl alcohol-GA (FPVAG), respectively. Thermogravimetric analyses proved that after coating the thermal stability was markedly enhanced. Magnetic measurements and Fourier transform infrared (FTIR) revealed that superparamagnetic iron oxide nanoparticles could be successfully coated with two polymers (PEG and PVA) and gallic acid as an active drug. Release behavior of gallic acid from two nanocomposites showed that FPEGG and FPVAG nanocomposites were found to be sustained and governed by pseudo-second-order kinetics. Anticancer activity of the two nanocomposites shows that the FPEGG demonstrated higher anticancer effect on the breast cancer cell lines in almost all concentrations tested compared to FPVAG.
  13. Saddki N, Sulaiman Z, Ali SH, Tengku Hassan TN, Abdullah S, Ab Rahman A, et al.
    J Interpers Violence, 2013 Aug;28(12):2557-80.
    PMID: 23508088 DOI: 10.1177/0886260513479029
    The Women's Health and Life Experiences questionnaire measures the prevalence, health implications, and risk factors for domestic violence. This cross-sectional study was conducted to determine the validity and reliability of the Malay version of World Health Organization (WHO) Women's Health and Life Experiences Questionnaire. Construct validity and reliability assessment of the Malay version of the questionnaire was done on 20 specific items that measure four types of intimate partner violence (IPV) act; controlling behaviors (CB), emotional violence (EV), physical violence (PV), and sexual violence (SV), which were considered as the domains of interest. Face-to-face interviewing method was used for data collection. A total of 922 women completed the interviews. The results showed that exploratory factor analysis of four factors with eigenvalues above 1 accounted for 63.83% of the variance. Exploratory factor analysis revealed that all items loaded above 0.40 and the majority of items loaded on factors that were generally consistent with the proposed construct. The internal consistency reliability was good. The Cronbach's α values ranged from 0.767 to 0.858 across domains. The Malay version of WHO Women's Health and Life Experiences Questionnaire is a valid and reliable measure of women's health and experiences of IPV in Malaysia.
  14. Rahman AA, Rahman RA, Ismail SB, Ibrahim MI, Ali SH, Salleh H, et al.
    Asia Pac J Public Health, 2015 Mar;27(2):NP1549-56.
    PMID: 22751680 DOI: 10.1177/1010539512449856
    The objective of this cross-sectional study was to determine the factors associated with the attitudes toward premarital sexual activities among school-going adolescents in Kelantan, Malaysia. It was conducted among 1032 secondary school students using a self-administered validated questionnaire. Multiple logistic regression revealed that the risk factors for having permissive attitudes toward practice of premarital sexual activities were male students (odds ratio [OR] = 1.83; 95% confidence interval [CI] = 1.34-2.48), being less religious (OR = 2.02; 95% CI = 1.49-2.73), and younger age group of students (13 to 14 years old; OR = 1.42; 95% CI = 1.05-1.92). Having good knowledge on sexual and reproductive health was a protective factor against permissive sexual attitude (OR = 0.27; 95% CI = 0.20-0.36). In conclusion, male and young adolescents were at risk of having permissive attitudes toward sexual behaviors, but good knowledge on sexual and reproductive health and being more religious may protect them from it.
  15. Ab Rahman A, Ab Rahman R, Ibrahim MI, Salleh H, Ismail SB, Ali SH, et al.
    PMID: 21706952
    The objectives of this study were to describe the knowledge of sexual and reproductive health among adolescents attending school and to compare the levels of knowledge between males and females and between older and younger groups of adolescents. A cross-sectional study was conducted among 1,034 secondary school students using a self administered validated questionnaire. The items with the fewest correct responses included: whether one can get pregnant after a single act of sexual intercourse (30.4%), whether sexual intercourse causes sexually transmitted diseases (STDs) (12.4%) and whether washing the vagina after sexual intercourse prevents pregnancy (17.0%). Their main source of sexual information was friends (64.4%). An independent t-test revealed the mean knowledge score was significantly higher among females than males on items assessing whether the genitalia may be touched freely by family members, females having attained menarche may become pregnant if having sex, whether pregnancy will occur if there is penetration of the penis into the vagina, whether premarital sexual intercourse causes pregnancy and if there is a relationship between abandoned babies and premarital pregnancies. The mean knowledge score assessing whether pregnancy can be prevented using condoms was higher among males than females. The mean knowledge scores were significantly higher among form four and form five students than forms one, two and three students. Lack of knowledge regarding important aspects of sexual and reproductive health warrant the need to strengthen sexual and reproductive health education.
  16. Khandakar A, Chowdhury MEH, Ibne Reaz MB, Md Ali SH, Hasan MA, Kiranyaz S, et al.
    Comput Biol Med, 2021 10;137:104838.
    PMID: 34534794 DOI: 10.1016/j.compbiomed.2021.104838
    Diabetes foot ulceration (DFU) and amputation are a cause of significant morbidity. The prevention of DFU may be achieved by the identification of patients at risk of DFU and the institution of preventative measures through education and offloading. Several studies have reported that thermogram images may help to detect an increase in plantar temperature prior to DFU. However, the distribution of plantar temperature may be heterogeneous, making it difficult to quantify and utilize to predict outcomes. We have compared a machine learning-based scoring technique with feature selection and optimization techniques and learning classifiers to several state-of-the-art Convolutional Neural Networks (CNNs) on foot thermogram images and propose a robust solution to identify the diabetic foot. A comparatively shallow CNN model, MobilenetV2 achieved an F1 score of ∼95% for a two-feet thermogram image-based classification and the AdaBoost Classifier used 10 features and achieved an F1 score of 97%. A comparison of the inference time for the best-performing networks confirmed that the proposed algorithm can be deployed as a smartphone application to allow the user to monitor the progression of the DFU in a home setting.
  17. Haque F, Ibne Reaz MB, Chowdhury MEH, Md Ali SH, Ashrif A Bakar A, Rahman T, et al.
    Comput Biol Med, 2021 12;139:104954.
    PMID: 34715551 DOI: 10.1016/j.compbiomed.2021.104954
    BACKGROUND: Diabetic Sensorimotor polyneuropathy (DSPN) is one of the major indelible complications in diabetic patients. Michigan neuropathy screening instrumentation (MNSI) is one of the most common screening techniques used for DSPN, however, it does not provide any direct severity grading system.

    METHOD: For designing and modeling the DSPN severity grading systems for MNSI, 19 years of data from Epidemiology of Diabetes Interventions and Complications (EDIC) clinical trials were used. Different Machine learning-based feature ranking techniques were investigated to identify the important MNSI features associated with DSPN diagnosis. A multivariable logistic regression-based nomogram was generated and validated for DSPN severity grading using the best performing top-ranked MNSI features.

    RESULTS: Top-10 ranked features from MNSI features: Appearance of Feet (R), Ankle Reflexes (R), Vibration perception (L), Vibration perception (R), Appearance of Feet (L), 10-gm filament (L), Ankle Reflexes (L), 10-gm filament (R), Bed Cover Touch, and Ulceration (R) were identified as important features for identifying DSPN by Multi-Tree Extreme Gradient Boost model. The nomogram-based prediction model exhibited an accuracy of 97.95% and 98.84% for the EDIC test set and an independent test set, respectively. A DSPN severity score technique was generated for MNSI from the DSPN severity prediction model. DSPN patients were stratified into four severity levels: absent, mild, moderate, and severe using the cut-off values of 17.6, 19.1, 20.5 for the DSPN probability less than 50%, 75%-90%, and above 90%, respectively.

    CONCLUSIONS: The findings of this work provide a machine learning-based MNSI severity grading system which has the potential to be used as a secondary decision support system by health professionals in clinical applications and large clinical trials to identify high-risk DSPN patients.

  18. Alhasa KM, Mohd Nadzir MS, Olalekan P, Latif MT, Yusup Y, Iqbal Faruque MR, et al.
    Sensors (Basel), 2018 Dec 11;18(12).
    PMID: 30544953 DOI: 10.3390/s18124380
    Conventional air quality monitoring systems, such as gas analysers, are commonly used in many developed and developing countries to monitor air quality. However, these techniques have high costs associated with both installation and maintenance. One possible solution to complement these techniques is the application of low-cost air quality sensors (LAQSs), which have the potential to give higher spatial and temporal data of gas pollutants with high precision and accuracy. In this paper, we present DiracSense, a custom-made LAQS that monitors the gas pollutants ozone (O₃), nitrogen dioxide (NO₂), and carbon monoxide (CO). The aim of this study is to investigate its performance based on laboratory calibration and field experiments. Several model calibrations were developed to improve the accuracy and performance of the LAQS. Laboratory calibrations were carried out to determine the zero offset and sensitivities of each sensor. The results showed that the sensor performed with a highly linear correlation with the reference instrument with a response-time range from 0.5 to 1.7 min. The performance of several calibration models including a calibrated simple equation and supervised learning algorithms (adaptive neuro-fuzzy inference system or ANFIS and the multilayer feed-forward perceptron or MLP) were compared. The field calibration focused on O₃ measurements due to the lack of a reference instrument for CO and NO₂. Combinations of inputs were evaluated during the development of the supervised learning algorithm. The validation results demonstrated that the ANFIS model with four inputs (WE OX, AE OX, T, and NO₂) had the lowest error in terms of statistical performance and the highest correlation coefficients with respect to the reference instrument (0.8 < r < 0.95). These results suggest that the ANFIS model is promising as a calibration tool since it has the capability to improve the accuracy and performance of the low-cost electrochemical sensor.
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