Muhammad Abdul Kadir

@du.ac.bd

Associate Professor, Department of Biomedical Physics and Technology, Faculty of Science
University of Dhaka

Muhammad Abdul Kadir


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https://researchid.co/kadir221

RESEARCH INTERESTS

Biomedical instrumentation and medical applications of electrical bioimpedance techniques, Biomedical signal & image analysis and machine learning techniques for disease diagnosis.
30

Scopus Publications

4999

Scholar Citations

16

Scholar h-index

20

Scholar i10-index

Scopus Publications

  • Genitourinary System Imaging with Low-Cost Portable Ultrasound Device in the Context of Telemedicine Implementation
    Afroza Naznin, Muhammad Abdul Kadir, Fatima Begum, Khondkar Siddique-e Rabbani
    Global Clinical Engineering Journal, 2026
    Background: The integration of digital diagnostic tools is essential for strengthening telemedicine infrastructure, particularly in remote and resource-limited settings. Ultrasound is a promising imaging modality because of its noninvasive disposition, absence of ionizing radiation, and ability to provide rapid, real-time diagnostic information. Among the wide range of ultrasound systems, cost-effective and portable devices with acceptable diagnostic performance are needed to improve accessibility. This study aimed to evaluate the performance of a commercially available low-cost portable ultrasound device, with a specific focus on imaging the genitourinary (GU) system. Methods: This cross-sectional study was conducted between December 2022 and July 2023 and included 169 participants. Each participant underwent ultrasound examinations using both a low-cost portable ultrasound device and a conventional ultrasound machine, which served as the reference (gold) standard. The assessment included measurement of organ sizes and detecting pathological conditions in the kidneys, urinary bladder, uterus, ovaries, and prostate. Results: The portable ultrasound device demonstrated high diagnostic accuracy for detecting renal cysts (98.7%), uterine masses (97.2%), polycystic ovaries (98.7%), and adnexal cystic lesions (96.3%). Relatively lower accuracy was observed for the detection of renal parenchymal disease (93.7%) and ovarian enlargement (91.5%). Agreement between the portable and conventional devices for organ size measurements showed moderate to strong correlations. The coefficients of determination (r2) for bipolar lengths of the right and left kidneys, uterine length, and uterine anteroposterior diameter were 0.5907, 0.6345, 0.8637, and 0.8444, respectively. Conclusion: These findings suggest that low-cost portable ultrasound devices can provide acceptable performance for imaging of the GU system. Their integration into telemedicine and tele-ultrasound services could enhance diagnostic capabilities and improve access to essential imaging in resource-limited and underserved populations.
  • Finite element modeling of human thorax for electrical bioimpedance based monitoring of pulmonary fluid accumulation
    Frijia Mortuza, Md. Shahriar Kabir, Md. Zaman Molla, Md. Ibrahim Al Imran, Muhammad Abdul Kadir
    Journal of Electrical Bioimpedance, 2026
    Monitoring fluid accumulation in the lungs is critical in conditions such as pulmonary edema and pneumonia. Current diagnostic modalities, including auscultation, chest X-ray, computed tomography, magnetic resonance imaging, and ultrasonography, either involve ionizing radiation or are not suitable for continuous long-term monitoring. This study investigated the feasibility of a non-invasive, non-ionizing electrical impedance–based approach for continuous assessment of pulmonary fluid accumulation using computational modeling. Firstly, CT images of human subjects were used to build a simplified thorax model. Different parts of human thorax including airways, left and right lungs, and soft tissue were segmented using a segmentation software Materialise Mimics ® and imported into COMSOL Multiphysics ® for finite element analysis. Tetrapolar transfer impedance was computed at multiple vertical electrode positions under baseline (air-filled lung) and fluid-accumulation conditions. The results demonstrated a measurable reduction in impedance in the presence of fluid, particularly at electrode levels corresponding to the fluid-filled lower lobes. A linear relationship between impedance and fluid volume was observed (R 2 = 0.9972 for the left lung and R 2 = 0.9998 for the right lung), with sensitivities of −466.74 mΩ/100 mL and −754.75 mΩ/100 mL, respectively. For clinically relevant fluid accumulations (≥300 mL), the predicted impedance change exceeded 2 Ω, indicating practical detectability. Frequency-domain analysis (5–1000 kHz) further demonstrated consistent impedance contrast across the investigated range. These findings suggest that tetrapolar electrical impedance measurements have the potential for continuous monitoring of pulmonary fluid changes and provide a foundation for future experimental validation in human subjects.
  • Secure Remote Patient Monitoring in Smart Wards using Blockchain and Encryption Techniques: A Functional Prototype
    Md. Abu Sayed, Md. Alimul Islam, Hasan Ahmed, Md. Imran Hossain, Muhammad Abdul Kadir
    6th IEEE International Conference on Telecommunications and Photonics Ictp 2025, 2025
  • Automated lumbar intervertebral disc identification and herniation detection in MR images using cascade CNN architecture
    Md Abu Sayed, Ashiqur Rahman, Sadman Mohammad Nasif, Sudipto Halder, Akram Hossain, et al.
    Informatics in Medicine Unlocked, 2025
  • Comparative Performance of Low-Cost Portable Scanner in Pregnancy Profile Ultrasonography: A Promising Adjunct to Telemedicine
    Afroza Naznin, Muhammad Abdul Kadir, Fatima Begum, Khondkar Siddique-e Rabbani
    Global Clinical Engineering Journal, 2024
    Background and Objective: Ultrasound scanners are widely used in various clinical settings, but conventional devices are too expensive to deploy in every healthcare facility in low-resource countries. Alternative, less costly instruments with comparable efficacy are required to ensure this diagnostic service is available in even remotest areas. This study evaluated the effectiveness of a commercially available low-cost portable ultrasound machine, particularly focusing on pregnancy profiling. Material and Methods: A total of 77 pregnant females were scanned for basic obstetric parameters with two devices, first the low-cost scanner, and then a conventional ultrasound machine, considering the latter as the gold standard. The key obstetric parameters observed were the number of fetuses, the presence of cardiac pulsation and fetal movement, fetal biometry including Crown Rump Length (CRL), Bi-Parietal Diameter (BPD), and Femoral Length (FL), gestational age, placental location, amniotic fluid volume, and presentation of the fetus. Results: The portable device performed well compared with the standard machine in observing the fetal number, presentation, movement, heartbeat, placental location, and amniotic fluid volume. The correlation coefficients (r²) for measuring BPD, FL, CRL, and gestational age using the portable and standard devices were 0.9578, 0.9415, 0.8230, and 0.983, respectively. The mean absolute error (MAE) in the measurement of BPD, FL, CRL, and gestational age were 2.24 mm, 2.14 mm, 6.5 mm, and 0.94 weeks, respectively. Conclusion: The results demonstrated the potential of low-cost portable ultrasound devices in pregnancy profile scanning. Further studies with larger sample sizes are needed to explore their full potential. With appropriate data transfer arrangements, these devices have significant potential for integration into telemedicine services.
  • MediSign: An Attention-Based CNN-BiLSTM Approach of Classifying Word Level Signs for Patient-Doctor Interaction in Hearing Impaired Community
    Md. Amimul Ihsan, Abrar Faiaz Eram, Lutfun Nahar, Muhammad Abdul Kadir
    IEEE Access, 2024
    Along with day-to-day communication, receiving medical care is quite challenging for the hearing impaired and mute population, especially in developing countries where medical facilities are not as modernized as in the West. A word-level sign language interpretation system that is aimed toward detecting medically relevant signs can allow smooth communication between doctors and hearing impaired patients, ensuring seamless medical care. To that end, a dataset from twenty distinct signers of diverse backgrounds performing 30 frequently used words in patient-doctor interaction was created. The proposed system has been built employing MobileNetV2 in conjunction with an attention-based Bidirectional LSTM network to achieve robust classification, where the validation accuracy and f1- scores were 95.83% and 93%, respectively. Notably, the accuracy of the proposed model surpasses the recent word-level sign language classification method in a medical context by 5%. Furthermore, the comparison of evaluation metrics with contemporary word-level sign language recognition models in American, Arabic, and German Sign Language further affirmed the capability of the proposed architecture.
  • Effects of temperature on electrical impedance of biological tissues: Ex-vivo measurements
    Safia Aktar Dipa, Muralee Monohara Pramanik, Mamun Rabbani, Muhammad Abdul Kadir
    Journal of Electrical Bioimpedance, 2024
    Bioelectrical impedance techniques have been useful in various applications, including body composition analysis, impedance plethysmography, impedance cardiography, lung ventilation, perfusion, and tissue characterization. Electrical impedance methods have also been useful in characterizing different foods like meat, fruits, and beverages. However, the temperature of tissue samples can change their dielectric properties, affecting their impedance. This research investigated the effects of temperature on the impedance of various biological tissues over the frequency range of 10 Hz to 5 MHz. Freshly excised animal tissues (lamb, cow, chicken), fish, fruits, and plants were considered as biological samples. The samples were placed in a test cell and submerged in a water bath heated by a hot plate to vary the temperature. Impedance measurements were conducted using a bioimpedance spectrometer in 2 °C steps within the temperature range of 20 °C to 50 °C. Impedance values decreased with increased temperature across all measurement frequencies for all biological samples. Curve fitting indicated that impedance decreased linearly with temperature, with a mean correlation coefficient of 0.972 for all samples. For all biological samples under investigation, the relative impedance change ranged from −0.58% to −2.27% per °C, with a mean and standard deviation of (−1.42±0.34) %/°C. On average, animal samples exhibited a higher relative temperature coefficient of −1.56% per °C (±0.41) across the frequency range, compared to −1.31% per °C (±0.26) for fruit and vegetable samples. Additionally, the relative temperature coefficient values were generally higher at lower frequencies than at higher frequencies. The findings of this research can be valuable for studies or biomedical applications involving variable tissue temperatures.
  • Enhancement of Sensitivity in Electrical Bioimpedance Measurements Using Contrast Agents
    Chitra Roy, Md. Sohag Ali, Md. Tushar Abdullah, Md. Ibrahim Al Imran, Muhammad Abdul Kadir
    Proceedings 6th International Conference on Electrical Engineering and Information and Communication Technology Iceeict 2024, 2024
    Electrical bioimpedance, a noninvasive and non-ionizing technique utilized for assessing physiological parameters, faces challenges in obtaining localized information from specific tissues within the human body. This research aims to enhance localized sensitivity in bioimpedance measurements by introducing contrast agents to improve the differentiation between malignant and healthy tissues. The study utilized finite element-based simulations in COMSOL Multiphysics to analyze sensitivity distribution within a breast model with a tumor. Results indicated that introducing contrast agents, such as an ionic liquid (with a conductivity of 0.39 S/m), significantly enhanced sensitivity within the designated region. For experimental validation, a breast phantom with a spherical tumor was created using Agar solution in a 3D printed hemispherical shell, and multi-frequency electrical impedance was measured with an impedance spectrometer. Results demonstrated a markedly higher impedance ratio (2.6) between malignant and normal tissues in the presence of ionic liquids compared to scenarios without them (1.5). This comprehensive investigation shows promising results, particularly in optimizing bioimpedance measurements through the use of ionic liquids as contrast agents. The findings hold significant potential for advancing diagnostic procedures in healthcare, providing a reliable means of detecting and localizing tumors.
  • Thermodynamics of mechanopeptide sidechains
    Md. Mozzammel Haque, Muhammad Abdul Kadir, Richard Bayford
    Aip Advances, 2023
    Biological systems are often exposed to mechanical perturbations, which may modulate many biochemical processes. Ligand binding involves a wide range of structural changes in the receptor protein, from hinge movement of entire domains to minor sidechain rearrangements in the binding pocket residues. Hydrophobic ligand binding to protein alters the system’s vibrational free energy, allowing different conformational states of allosteric proteins. Excess hydrophobicity in protein–ligand binding generates mechanical force along the peptide backbone through the hydrophobic effect. We describe mechanically strained peptide structures involved in protein aggregation to determine the transition between the initial condensation of hydrophobic polypeptide chains into ordered fibrillar structures. This transition is due to the excess attractive hydrophobic force by ligand binding within proteins into fibrillar assemblies. The process of fibrillar formation has a mechanosensitive nature, which significantly influences the pathogenesis of several neurodegenerative diseases.
  • Signer-Independent Arabic Sign Language Recognition System Using Deep Learning Model
    Kanchon Kanti Podder, Maymouna Ezeddin, Muhammad E. H. Chowdhury, Md. Shaheenur Islam Sumon, Anas M. Tahir, et al.
    Sensors, 2023
    Every one of us has a unique manner of communicating to explore the world, and such communication helps to interpret life. Sign language is the popular language of communication for hearing and speech-disabled people. When a sign language user interacts with a non-sign language user, it becomes difficult for a signer to express themselves to another person. A sign language recognition system can help a signer to interpret the sign of a non-sign language user. This study presents a sign language recognition system that is capable of recognizing Arabic Sign Language from recorded RGB videos. To achieve this, two datasets were considered, such as (1) the raw dataset and (2) the face–hand region-based segmented dataset produced from the raw dataset. Moreover, operational layer-based multi-layer perceptron “SelfMLP” is proposed in this study to build CNN-LSTM-SelfMLP models for Arabic Sign Language recognition. MobileNetV2 and ResNet18-based CNN backbones and three SelfMLPs were used to construct six different models of CNN-LSTM-SelfMLP architecture for performance comparison of Arabic Sign Language recognition. This study examined the signer-independent mode to deal with real-time application circumstances. As a result, MobileNetV2-LSTM-SelfMLP on the segmented dataset achieved the best accuracy of 87.69% with 88.57% precision, 87.69% recall, 87.72% F1 score, and 99.75% specificity. Overall, face–hand region-based segmentation and SelfMLP-infused MobileNetV2-LSTM-SelfMLP surpassed the previous findings on Arabic Sign Language recognition by 10.970% accuracy.
  • Multi-Modal Portable Respiratory Rate Monitoring Device for Childhood Pneumonia Detection
    Sadeque Reza Khan, Xiaohan Wang, Tiantao Jiang, Wei Ju, Norbert Radacsi, et al.
    Micromachines, 2023
  • Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs
    Arafat Rahman, Muhammad E.H. Chowdhury, Amith Khandakar, Anas M. Tahir, Nabil Ibtehaz, et al.
    Computers in Biology and Medicine, 2022
  • Probing deep lung regions using a new 6-electrode tetrapolar impedance method
    Mahjabin Mobarak, Muhammad Abdul Kadir, K Siddique-e Rabbani
    Journal of Electrical Bioimpedance, 2022
  • Bangla Sign Language (BdSL) Alphabets and Numerals Classification Using a Deep Learning Model
    Kanchon Kanti Podder, Muhammad E. H. Chowdhury, Anas M. Tahir, Zaid Bin Mahbub, Amith Khandakar, et al.
    Sensors, 2022
  • Video based non-contact monitoring of respiratory rate and chest indrawing in children with pneumonia
    Ferdous Karim Lucy, Khadiza Tun Suha, Sumaiya Tabassum Dipty, Md Sharjis Ibne Wadud, Muhammad Abdul Kadir
    Physiological Measurement, 2021
  • Switching Algorithm and Data Acquisition for Pigeon Hole Imaging System
    Bikash Kumar Bhawmick, Muhammad Abdul Kadir, Khondkar Siddique-e Rabbani
    Proceedings of International Conference on Electronics Communications and Information Technology Icecit 2021, 2021
  • Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
    Arafat Rahman, Muhammad E. H. Chowdhury, Amith Khandakar, Serkan Kiranyaz, Kh Shahriya Zaman, et al.
    IEEE Access, 2021
  • Transfer learning with deep Convolutional Neural Network (CNN) for pneumonia detection using chest X-ray
    Tawsifur Rahman, Muhammad E. H. Chowdhury, Amith Khandakar, Khandaker R. Islam, Khandaker F. Islam, et al.
    Applied Sciences Switzerland, 2020
  • Can AI Help in Screening Viral and COVID-19 Pneumonia?
    Muhammad E. H. Chowdhury, Tawsifur Rahman, Amith Khandakar, Rashid Mazhar, Muhammad Abdul Kadir, et al.
    IEEE Access, 2020
  • Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization
    Tawsifur Rahman, Amith Khandakar, Muhammad Abdul Kadir, Khandaker Rejaul Islam, Khandakar F. Islam, et al.
    IEEE Access, 2020
  • Probing for stomach using the Focused Impedance Method (FIM)
    Rashida Haque, Muhammad Abdul Kadir, K Siddique-e Rabbani
    Journal of Electrical Bioimpedance, 2019
  • A new six-electrode electrical impedance technique for probing deep organs in the human body
    Shamor Kanti Roy, Mohammad Abu Sayem Karal, Muhammad Abdul Kadir, Khondkar Siddique-e Rabbani
    European Biophysics Journal, 2019
  • Use of a conical conducting layer with an electrical impedance probe to enhance sensitivity in epithelial tissues
    Muhammad Abdul Kadir, K. Siddique-e Rabbani
    Journal of Electrical Bioimpedance, 2018
  • Subcutaneous vein detection using pigeon hole imaging: Simulation study
    Rushdi Zahid Rusho, M Abdul Kadir
    5th IEEE Region 10 Humanitarian Technology Conference 2017 R10 Htc 2017, 2018
  • Reconstruction algorithm for Pigeon Hole Imaging (PHI)
    Rushdi Zahid Rusho, M Abdul Kadir
    3rd International Conference on Electrical Information and Communication Technology Eict 2017, 2017

RECENT SCHOLAR PUBLICATIONS

  • Finite element modeling of human thorax for electrical bioimpedance based monitoring of pulmonary fluid accumulation
    F Mortuza, MS Kabir, MZ Molla, MI Al Imran, MA Kadir
    Journal of Electrical Bioimpedance 17 (1), 4 , 2026
    2026
  • Secure Remote Patient Monitoring in Smart Wards using Blockchain and Encryption Techniques: A Functional Prototype
    MA Sayed, MA Islam, H Ahmed, MI Hossain, MA Kadir
    2025 IEEE International Conference on Telecommunications and Photonics (ICTP … , 2025
    2025
  • A deep learning pipeline for predicting length of stay and patient discharge outcomes in critical care units
    MA Sayed, MA Islam, A Rahman, N Shabab, MA Kadir
    IUPESM World Congress on Medical Physics and Biomedical Engineering 2025 … , 2025
    2025
  • Reconstruction algorithm for improving resolution in bioelectrical impedance based Pigeon Hole Imaging
    MA Kadir, F Mortuza, HC Barman, C Roy, MA Sayed, MIA Imran
    IUPESM World Congress on Medical Physics and Biomedical Engineering 2025 … , 2025
    2025
  • Designing Potential Inhibitors Against RET PROTEIN TYROSINE KINASE DOMAIN to Fight Sporadic Medullary Thyroid Carcinoma: A Virtual Screening and Molecular Dynamics Simulation …
    T Roy, A Abdullah, A Mubasharah, AI Zamee, MIA Imran, MEK Talukder, ...
    Journal of Carcinogenesis 24 (3), 519-540 , 2025
    2025
  • Automated lumbar intervertebral disc identification and herniation detection in MR images using cascade CNN architecture
    MA Sayed, A Rahman, SM Nasif, S Halder, A Hossain, H Ahmed, ...
    Informatics in Medicine Unlocked 55, 101648 , 2025
    2025
    Citations: 2
  • Effects of temperature on electrical impedance of biological tissues: ex-vivo measurements
    SA Dipa, MM Pramanik, M Rabbani, MA Kadir
    Journal of Electrical Bioimpedance 15 (1), 116-124 , 2024
    2024
    Citations: 13
  • Comparative Performance of Low-Cost Portable Scanner in Pregnancy Profile Ultrasonography: A Promising Adjunct to Telemedicine
    A Naznin, MA Kadir, F Begum, KS Rabbani
    Global Clinical Engineering Journal 6 (3), 26–36 , 2024
    2024
  • Enhancement of Sensitivity in Electrical Bioimpedance Measurements Using Contrast Agents
    C Roy, MS Ali, MT Abdullah, MI Al Imran, MA Kadir
    2024 6th International Conference on Electrical Engineering and Information … , 2024
    2024
  • MediSign: An Attention-based CNN-BiLSTM Approach of Classifying Word Level Signs for Patient-Doctor Interaction in Hearing Impaired Community
    MA Ihsan, AF Eram, L Nahar, MA Kadir
    IEEE Access 12 , 2024
    2024
    Citations: 23
  • Signer-independent Arabic Sign Language recognition system using deep learning model
    KK Podder, M Ezeddin, MEH Chowdhury, MSI Sumon, AM Tahir, ...
    Sensors 23 (16), 7156 , 2023
    2023
    Citations: 68
  • Thermodynamics of mechanopeptide sidechains
    MM Haque, MA Kadir, R Bayford
    AIP Advances 13 (8) , 2023
    2023
  • Multi-Modal Portable Respiratory Rate Monitoring Device for Childhood Pneumonia Detection
    SR Khan, X Wang, T Jiang, W Ju, N Radacsi, MA Kadir, KS Rabbani, ...
    Micromachines 14 (4), 708 , 2023
    2023
    Citations: 6
  • Probing deep lung regions using a new 6-electrode tetrapolar impedance method
    M Mobarak, MA Kadir, KSE Rabbani
    Journal of Electrical Bioimpedance 13 (1), 116 , 2023
    2023
    Citations: 8
  • Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs
    A Rahman, MEH Chowdhury, A Khandakar, AM Tahir, N Ibtehaz, ...
    Computers in Biology and Medicine 142, 105238 , 2022
    2022
    Citations: 42
  • Bangla sign language (bdsl) alphabets and numerals classification using a deep learning model
    KK Podder, MEH Chowdhury, AM Tahir, ZB Mahbub, A Khandakar, ...
    Sensors 22 (2), 574 , 2022
    2022
    Citations: 91
  • A Multi-Frequency Focused Impedance Measurement System Based on Analogue Synchronous Peak Detection
    MA Kadir, AJ Wilson, K Rabbani
    Frontiers in Electronics 2, 23 , 2021
    2021
    Citations: 7
  • Video based non-contact monitoring of respiratory rate and chest indrawing in children with pneumonia
    FK Lucy, KT Suha, ST Dipty, MSI Wadud, MA Kadir
    Physiological Measurement 42 (10), 105017 , 2021
    2021
    Citations: 9
  • Switching Algorithm and Data Acquisition for Pigeon Hole Imaging System
    BK Bhawmick, MA Kadir, KS Rabbani
    2021 International Conference on Electronics, Communications and Information … , 2021
    2021
  • Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
    A Rahman, MEH Chowdhury, A Khandakar, S Kiranyaz, KS Zaman, ...
    IEEE Access 9, 94625-94643 , 2021
    2021
    Citations: 93

MOST CITED SCHOLAR PUBLICATIONS

  • Can AI help in screening viral and COVID-19 pneumonia?
    MEH Chowdhury, T Rahman, A Khandakar, R Mazhar, MA Kadir, ...
    IEEE Access 8, 132665-132676 , 2020
    2020
    Citations: 2385
  • Transfer learning with deep convolutional neural network (CNN) for pneumonia detection using chest X-ray
    T Rahman, MEH Chowdhury, A Khandakar, KR Islam, KF Islam, ...
    Applied Sciences 10 (9), 3233 , 2020
    2020
    Citations: 794
  • Reliable tuberculosis detection using chest X-ray with deep learning, segmentation and visualization
    T Rahman, A Khandakar, MA Kadir, KR Islam, KF Islam, R Mazhar, ...
    Ieee Access 8, 191586-191601 , 2020
    2020
    Citations: 771
  • COVID-19 Radiography Database
    T Rahman, MEH Chowdhury, A Khandakar, R Mazhar, MA Kadir, ...
    https://www.kaggle.com/tawsifurrahman/covid19-radiography-database , 2020
    2020
    Citations: 308
  • Role of telemedicine in healthcare during COVID-19 pandemic in developing countries
    MA Kadir
    Telehealth and Medicine Today 5 (2) , 2020
    2020
    Citations: 136
  • Multimodal EEG and Keystroke Dynamics Based Biometric System Using Machine Learning Algorithms
    A Rahman, MEH Chowdhury, A Khandakar, S Kiranyaz, KS Zaman, ...
    IEEE Access 9, 94625-94643 , 2021
    2021
    Citations: 93
  • Bangla sign language (bdsl) alphabets and numerals classification using a deep learning model
    KK Podder, MEH Chowdhury, AM Tahir, ZB Mahbub, A Khandakar, ...
    Sensors 22 (2), 574 , 2022
    2022
    Citations: 91
  • Signer-independent Arabic Sign Language recognition system using deep learning model
    KK Podder, M Ezeddin, MEH Chowdhury, MSI Sumon, AM Tahir, ...
    Sensors 23 (16), 7156 , 2023
    2023
    Citations: 68
  • Classification of breast tumour using electrical impedance and machine learning techniques
    AA Amin, S Parvin, MA Kadir, T Tahmid, SK Alam, K Siddique-e Rabbani
    Physiological measurement 35 (6), 965-974 , 2014
    2014
    Citations: 43
  • Robust biometric system using session invariant multimodal EEG and keystroke dynamics by the ensemble of self-ONNs
    A Rahman, MEH Chowdhury, A Khandakar, AM Tahir, N Ibtehaz, ...
    Computers in Biology and Medicine 142, 105238 , 2022
    2022
    Citations: 42
  • A new six-electrode electrical impedance technique for probing deep organs in the human body
    SK Roy, MAS Karal, MA Kadir, KS Rabbani
    European Biophysics Journal 48 (8), 711-719 , 2019
    2019
    Citations: 27
  • Bangla Sign Language Alphabet Recognition Using Transfer Learning Based Convolutional Neural Network
    KK Podder, MEH Chowdhury, ZB Mahbub, MA Kadir
    Bangladesh Journal of Scientific Research 31 (1), 20-26 , 2020
    2020
    Citations: 25
  • MediSign: An Attention-based CNN-BiLSTM Approach of Classifying Word Level Signs for Patient-Doctor Interaction in Hearing Impaired Community
    MA Ihsan, AF Eram, L Nahar, MA Kadir
    IEEE Access 12 , 2024
    2024
    Citations: 23
  • Possible applications of Focused Impedance Method (FIM) in biomedical and other areas of study
    KS Rabbani, MA Kadir
    Bangladesh Journal of Medical Physics 4 (1), 67-74 , 2011
    2011
    Citations: 22
  • Focused impedance method to detect localized lung ventilation disorders in combination with conventional spirometry
    MA Kadir, TN Baig, KS Rabbani
    Biomedical Engineering: Applications, Basis and Communications 27 (03), 1550029 , 2015
    2015
    Citations: 16
  • Ventilation mapping of chest using Focused Impedance Method (FIM)
    MA Kadir, H Ferdous, TN Baig, KS Rabbani
    Journal of Physics: Conference Series 224, 012031 , 2010
    2010
    Citations: 16
  • Application of the Focused Impedance Method (FIM) to Determine the Volume of an Object Within a Volume Conductor
    MA Kadir, SP Ahmed, GD Al Quaderi, R Rahman, KS Rabbani
    COMSOL Conference Bangalore 2013 , 2013
    2013
    Citations: 15
  • Can AI help in screening viral and covid-19 pneumonia? arXiv
    MEH Chowdhury, T Rahman, A Khandakar, R Mazhar, MA Kadir, ...
    arXiv preprint arXiv:2003.13145 , 2020
    2020
    Citations: 14
  • Effects of temperature on electrical impedance of biological tissues: ex-vivo measurements
    SA Dipa, MM Pramanik, M Rabbani, MA Kadir
    Journal of Electrical Bioimpedance 15 (1), 116-124 , 2024
    2024
    Citations: 13
  • Thyroid Uptake of Tc-99m and Its Agreement with I-131 for Evaluation of Hyperthyroid Function
    M Ohiduzzaman, R Khatun, S Reza, MA Kadir, S Akter, MF Uddin, ...
    Universal Journal of Public Health 7 (5), 201-206 , 2019
    2019
    Citations: 13