Amanullah Asraf

ORCID: 0000-0003-0342-9796
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About
Contact & Profiles
Research Areas
  • COVID-19 diagnosis using AI
  • AI in cancer detection
  • Radiomics and Machine Learning in Medical Imaging
  • Digital Imaging for Blood Diseases
  • Lung Cancer Diagnosis and Treatment
  • VLSI and Analog Circuit Testing
  • Artificial Intelligence in Healthcare
  • Low-power high-performance VLSI design
  • Autonomous Vehicle Technology and Safety
  • Radiation Effects in Electronics
  • Anomaly Detection Techniques and Applications

Khulna University of Engineering and Technology
2020-2024

Nowadays, automatic disease detection has become a crucial issue in medical science due to rapid population growth. An framework assists doctors the diagnosis of and provides exact, consistent, fast results reduces death rate. Coronavirus (COVID-19) one most severe acute diseases recent times spread globally. Therefore, an automated system, as fastest diagnostic option, should be implemented impede COVID-19 from spreading. This paper aims introduce deep learning technique based on...

10.1016/j.imu.2020.100412 article EN cc-by-nc-nd Informatics in Medicine Unlocked 2020-01-01

Abstract Nowadays automatic disease detection has become a crucial issue in medical science with the rapid growth of population. Coronavirus (COVID-19) one most severe and acute diseases very recent times that been spread globally. Automatic framework assists doctors diagnosis provides exact, consistent, fast reply as well reduces death rate. Therefore, an automated system should be implemented fastest way diagnostic option to impede COVID-19 from spreading. This paper aims introduce deep...

10.1101/2020.06.18.20134718 preprint EN cc-by-nc-nd medRxiv (Cold Spring Harbor Laboratory) 2020-06-20

Abstract The confrontation of COVID-19 pandemic has become one the promising challenges world healthcare. Accurate and fast diagnosis cases is essential for correct medical treatment to control this pandemic. Compared with reverse-transcription polymerase chain reaction (RT-PCR) method, chest radiography imaging techniques are shown be more effective detect coronavirus. For limitation available images, transfer learning better suited classify patterns in images. This paper presents a...

10.1101/2020.08.24.20181339 preprint EN cc-by-nc-nd medRxiv (Cold Spring Harbor Laboratory) 2020-08-31

Combating the COVID-19 pandemic has emerged as one of most promising issues in global healthcare. Accurate and fast diagnosis cases is required for right medical treatment to control this pandemic. Chest radiography imaging techniques are more effective than reverse-transcription polymerase chain reaction (RT-PCR) method detecting coronavirus. Due limited availability images, transfer learning better suited classify patterns images. This paper presents a combined architecture convolutional...

10.1016/j.tbench.2023.100088 article EN cc-by-nc-nd BenchCouncil Transactions on Benchmarks Standards and Evaluations 2022-10-01
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