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- 저자 : Kaisar, Nazia (검색결과 11 건)
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Developmental dyslexia detection using machine learning techniques : A survey
Shahriar Kaisar 한국통신학회 2020 ICT Express Vol.6 No.3
Developmental dyslexia is a learning disability that occurs mostly in children during their early childhood. Dyslexic children face difficulties while reading, spelling and writing words despite having average or above-average intelligence. As a consequence, dyslexic children often suffer from negative feelings, such as low self-esteem, frustration, and anger. Therefore, early detection of dyslexia is very important to support dyslexic children right from the start. Researchers have proposed a wide range of techniques to detect developmental dyslexia, which includes game-based techniques, reading and writing tests, facial image capture and analysis, eye tracking, Magnetic reasoning imaging (MRI) and Electroencephalography (EEG) scans. This survey paper critically analyzes recent contributions in detecting dyslexia using machine learning techniques and identify potential opportunities for future research.
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Shahriar Kaisar,Abdullahi Chowdhury 한국통신학회 2022 ICT Express Vol.8 No.4
Developmental Dyslexia is a learning disorder often discovered in school-aged children who face difficulties while reading or spelling words even though they may have average or above-average levels of intelligence. This ultimately results in anger, frustration, low self-esteem, and other negative feelings. Early detection of Dyslexia can be highly beneficial for dyslexic children as their learning needs can be properly addressed. Researchers have used several testing techniques for early discovery where the data is collected from reading and writing tests, online games, Magnetic reasoning imaging (MRI) and Electroencephalography (EEG) scans, picture and video recording. Several Machine learning techniques have also been used in this regard recently. However, existing works did not focus on the problem of the imbalanced dataset where the percentage of dyslexic participants is much higher compared to non-dyslexic participants, which is expected to be the case for pre-screening among a random population. This paper addresses the imbalanced dataset obtained from dyslexia pre-screening tests and proposes an oversampling and ensemble-based machine learning technique for the detection of Dyslexia. Simulation results show that the proposed approach improves the detection accuracy of the minority class, i.e., dyslexic patients from 80.61% to 83.52%.
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Parvez, M. Masud,Kaisar, Nazia,Shin, Ho Jung,Jung, Jin Ah,Shin, Jae-Gook American Society for Microbiology 2016 Antimicrobial Agents and Chemotherapy Vol.60 No.11
<B>ABSTRACT</B><P>Twenty-two currently marketed antituberculosis drugs were comprehensively evaluated for their inhibitory effect on organic anionic transporter (OAT)- and organic cation transporter (OCT)-mediated uptake using stably transfected HEK293 cells<I>in vitro</I>. We observed moderate to strong inhibitory effects on OAT1- and OAT3-mediated<I>para</I>-aminohippurate (PAH) uptake and OCT1- and OCT2-mediated<I>N</I>-methyl-4-phenylpylidinium acetate (MPP<SUP>+</SUP>) uptake. Ciprofloxacin, linezolid,<I>para</I>-aminosalicylic acid (PAS), and rifampin were observed to have strong inhibitory effects, with the concentrations for a 50% inhibitory effect (IC50s) being 35.1, 31.1, 37.6, and 48.1 μM, respectively, for OAT1 and >100, 21.9, 24.6, and 30.2 μM, respectively, for OAT3. Similarly, pyrazinamide, rifabutin, and levofloxacin were observed to have inhibitory effects, with IC50values being 36.5, 42.7, and 30.3 μM, respectively, for OCT1 and with the IC50value for PAS being 94.2 μM for OCT2. In addition, we used zidovudine and metformin as clinically prescribed substrates of OATs and OCTs, respectively, and zidovudine and metformin uptake was also strongly inhibited by the antituberculosis drugs. Among the tested drugs, the highest drug-drug interaction (DDI) indexes were found for PAS, which were 9.3 to 13.9 for OAT1 and 12.0 to 17.7 for OAT3, and linezolid, which were 1.18 to 2.15 for OAT1 and 1.7 to 3.01 for OAT3. Similarly, the DDI indexes of pyrazinamide and levofloxacin were 0.57 and 0.30, respectively, for OCT1, and the DDI index of PAS was 3.8 for OCT2, suggesting a stronger possibility (DDI index value cutoff, >0.1) of<I>in vivo</I>DDIs. This is the first comprehensive report of the inhibitory potential of anti-TB drugs on OAT- and OCT-mediated uptake of prototype and clinically prescribed substrate drugs<I>in vitro</I>, providing an ability to predict DDIs between anti-TB drugs and other coprescribed drugs in clinical studies<I>in vivo</I>.</P>
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Parvez, M. M.,Kaisar, Nazia,Shin, Ho Jung,Lee, Yoon Jae,Shin, Jae-Gook American Society for Microbiology 2018 Antimicrobial Agents and Chemotherapy Vol.62 No.9
<P>The substrate potentials of antituberculosis drugs on solute carrier (SLC) transporters are not well characterized to date, despite a well-established understanding of their drug dispositions and pharmacokinetics. In this study, we investigated comprehensively the substrate potentials of the 22 currently available antituberculosis drugs for SLC family transporter-mediated uptake, using Xenopus laevis oocytes and stably transfected HEK-293 cells in vitro. The result suggested that ethambutol, isoniazid, amoxicillin, and prothionamide act as novel substrates for the SLC transporters. In addition, in the presence of representative transporter inhibitors, the uptake of the antituberculosis drugs was markedly decreased compared with the uptake in the absence of inhibitor, suggesting involvement of the corresponding transporters. A cellular uptake study was performed, and the K-m values of ethambutol were found to be 526.1 +/- 15.6, 212.0 +/- 20.1, 336.8 +/- 20.1, and 455.0 +/- 28 mu M for organic cation transporter 1 (OCT1), OCT2, OCTN1, and OCTN2, respectively. Similarly, the K-m of prothionamide was 805.8 +/- 23.4 mu M for OCT1, while the K-m values of isoniazid and amoxicillin for organic anion transporter 3 (OAT3) were 233.7 +/- 14.1 and 161.4 +/- 10.6 mu M, respectively. The estimated in vivo drug-drug interaction indexes from in vitro transporter inhibition kinetics for verapamil, probenecid, and ibuprofen against ethambutol, prothionamide, isoniazid, and amoxicillin were found to show potential for clinical drug interactions. In conclusion, this is the first study that demonstrated 22 antituberculosis drug interactions with transporters. This study will be helpful for mechanistic understanding of the disposition, drug-drug interactions, and pharmacokinetics of these antituberculosis drugs.</P>
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A critical analysis of transport models for refueling of MOF-5 based hydrogen adsorption system
P. Sridhar,Niket S. Kaisare 한국공업화학회 2020 Journal of Industrial and Engineering Chemistry Vol.85 No.-
This work presents a critical analysis of 2D model of refueling a hydrogen storage tank containing MOF-5adsorbent under cryogenic and room temperature conditions. Three isotherm models, viz. Unilan,modified Dubinin–Astakhov DA and Tóth, werefitted with experimental data of hydrogen adsorptionfrom the literature, and their effect on refueling of adsorbent bed is analyzed. The choice of isotherm hasthe greatest impact on predicting refueling behavior, for bothflow-through and end-flow (i.e., batch)systems. A comparison between the ideal gas assumption and virial equation of state indicates that theformer reasonably captures the overall behavior at lower computational cost. Analysis of the role ofmomentum balance, solved as full Navier–Stokes model and with Darcy’s approximation, indicates samehydrogen uptake in the adsorbent bed and only a minor difference in the predicted velocity profiles. Finally, effect of temperature-dependent physical properties of gas, adsorbent and walls is analyzed.
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( Chi-dung Nguyen ),( Md Masud Parvez ),( Nazia Kaisar ),( Yong-soon Cho ),( Jae-gook Shin ) 대한결핵 및 호흡기학회 2020 대한결핵 및 호흡기학회 추계학술대회 초록집 Vol.128 No.-
Background Ethambutol (EMB) is a first-line antituberculosis drug of which renal elimination is the primary route of elimination. EMB has been proven to be a substrate of OCT2. The EMB concentration significantly increases in renal failure patients. It is of importance to evaluate renal function, OCT2 genotypes as well as the interplay among them on EMB pharmacokinetics. Therefore, we aimed to develop a physiologically based pharmacokinetic (PBPK) model implying those variables to understand more in detail and predict EMB exposure in individual patients. Methods The effect of OCT2 genetic variants on OCT2-mediated uptake of EMB was estimated using in vitro stably transfected HEK293 cells with OCT2 wild type and variants. A PBPK model for EMB was constructed in Simcyp (V.17) and validated against clinical data. The validated model was used to predict the effect of OCT2 genotypes and renal impairment on EMB disposition. The predicted EMB exposure in “virtual twins” tuberculosis patients was compared with clinical data. Results OCT2-genetic variants showed a significant decrease in OCT2-mediated uptake of EMB in vitro compared to wild type. EMB plasma concentration predicted by EMB PBPK model compared well with published clinical data. OCT2-T199I increases EMB AUCinf by 42% and decreases renal clearance (CLr) by 46% compared to that of wild type. An increased AUCinf ratio of 1.3 and 1.5 among GFR 30-60 and GFR 15-30 groups is predicted, with significantly reduced CLr than healthy. Most importantly, terminally impaired GFR and OCT2-T199I combined caused approximately 2 fold increase of EMB AUCinf, reduced about 4.5 fold CLr than healthy subjects. The model predicted quite good observed data in "virtual twin" tuberculosis patients. Conclusion To the best of our knowledge, this is the first PBPK model showing a significant effect of renal impairment and transporter genotypes on EMB pharmacokinetics, a roadmap towards personalized dose estimation.
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Hussain, Mohammad Arafat,Alam, S Kaisar,Lees, Soo Yeol,Hasan, Md Kamrul Academic Press 2012 Ultrasonic imaging Vol.34 No.2
<P>In ultrasound elastography, the strain in compressed tissue due to external deformation is estimated and is smaller in harder than softer tissue. With increased stress, the nonaxial motions of tissue elements increase and result in noisier strain images. At high strain, the envelope of the rf signal exhibits robustness to signal decorrelation. However, the precision of strain estimates using envelope signals is much worse compared to that using the rf signals. In this paper, we propose a novel approach for robust strain estimation by combining weighted rf cross-correlation and envelope cross-correlation functions. An applied strain-dependent piecewise-linear-weight is used for this purpose. In addition, we introduce nonlinear diffusion filtering to further enhance the resulting strain image. The results of our algorithm are demonstrated for up to 10% applied strain using a finite-element modelling (FEM) simulation phantom. It reveals that the elastographic signal-to-noise ratio (SNRe) and the elastographic contrast-to-noise ratio (CNRe) of the strain images can be improved more significantly than with other algorithms used in this paper. In addition, comparative results in terms of the mean structural similarity (MSSIM) using in vivo breast data show that the strain image quality can be improved noticeably by the proposed method than with the techniques employed in this work.</P>
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