Mahmoud Marhamati |Artificial | Best Researcher Award

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Mr.Mahmoud Marhamati |Artificial | Best Researcher Award

Mr. Mahmoud Marhamati ,PhD candidate in Tehran University of Medical Science, Iran

Mr. Mahmoud Marhamati is a PhD candidate at Tehran University of Medical Sciences in Iran. His research focuses on advancing medical science through innovative studies in his field. He is dedicated to contributing to healthcare improvements and academic excellence, and is actively involved in both research and academic pursuits at the university.

Summary:

Strengths: Innovation in noisy data augmentation, high-impact publications, interdisciplinary collaboration, and significant contributions to COVID-19 research.,Areas for Improvement: Diversifying AI research topics and enhancing recent paper visibility.

Professional Profiles:

Google Scholar

🎓 Education :

M. Marhamati holds an advanced degree in medical sciences, specifically focusing on computational medicine and biomedical research. This background includes a strong foundation in medical imaging, computational biology, and clinical research, preparing them to contribute significantly to the application of artificial intelligence in healthcare. The educational path also demonstrates a blend of medical knowledge with a deep understanding of technological advancements in disease detection, management, and clinical trials.

🏢 Experience:

M. Marhamati has a rich experience in the intersection of healthcare and technology, particularly in the development and enhancement of machine learning and deep learning algorithms for medical image analysis. Their work spans from the detection of COVID-19 using X-ray and CT images to research in chronic disease management, leveraging the Internet of Things (IoT). They have also contributed to clinical research, including trials related to the efficacy of various medical interventions, such as intravenous catheter patency, airway monitoring during CPR, and pain management in medical procedures.

🛠️Skills:

Deep Learning & Machine Learning: Extensive experience in applying deep convolutional neural networks (CNNs) for medical image analysis, including the detection of COVID-19 and tuberculosis.,Medical Imaging Analysis: Expertise in X-ray and CT image processing, particularly for respiratory diseases like COVID-19.,Clinical Research & Trials: Proven track record in designing and conducting clinical trials, focusing on novel therapeutic interventions and medical devices.,Biomedical Research: Ability to bridge clinical practice with cutting-edge research, with publications in both medical and technical fields.,Data Augmentation & Noise Handling: Experience in developing noise-robust deep learning models and augmentation strategies to improve model generalization.,Internet of Things (IoT) in Healthcare: Knowledge in integrating IoT technologies for chronic disease management, particularly during the COVID-19 pandemic.

🔬Awards:

Throughout their career, M. Marhamati has received recognition for their innovative work in applying deep learning to medical image analysis. Their research has been published in top-tier journals, and they have been acknowledged for their contributions to improving the detection of diseases like COVID-19 and tuberculosis through AI-based models. Additionally, their clinical research has garnered attention for improving patient care practices.

Research Focus:

M. Marhamati’s research is primarily focused on the application of deep learning and AI in medical imaging and healthcare. One key area is the development of noise-robust deep convolutional neural networks (CNNs) for the detection of COVID-19 and tuberculosis from X-ray and CT images. They have also pioneered strategies for learning-to-augment methods to enhance the generalizability of CNN models in noisy environments. Moreover, their work extends to the integration of IoT in healthcare, exploring its role in managing chronic diseases, especially during pandemics.

Conclusion:

Mr. Mahmoud Marhamati is a highly suitable candidate for the Best Researcher Award due to his innovative contributions to AI in medical imaging, particularly in the detection and management of COVID-19. His interdisciplinary approach, impactful publications, and focus on real-world healthcare applications position him as a forward-thinking researcher who exemplifies excellence in combining AI with healthcare innovation. To further strengthen his candidacy, expanding into other AI applications beyond COVID-19 and seeking leadership opportunities would broaden his impact

Publications :

  • Learning-to-augment strategy using noisy and denoised data: Improving generalizability of deep CNN for the detection of COVID-19 in X-ray images
    • Authors: M. Momeny, A.A. Neshat, M.A. Hussain, S. Kia, M. Marhamati, et al.
    • Journal: Computers in Biology and Medicine
    • Year: 2021
    • Citations: 67

 

  • Learning-to-augment incorporated noise-robust deep CNN for detection of COVID-19 in noisy X-ray images
    • Authors: A. Akbarimajd, N. Hoertel, M.A. Hussain, A.A. Neshat, M. Marhamati, et al.
    • Journal: Journal of Computational Science
    • Year: 2022
    • Citations: 36

 

  • Greedy Autoaugment for classification of mycobacterium tuberculosis image via generalized deep CNN using mixed pooling based on minimum square rough entropy
    • Authors: M. Momeny, A.A. Neshat, A. Gholizadeh, A. Jafarnezhad, E. Rahmanzadeh, et al.
    • Journal: Computers in Biology and Medicine
    • Year: 2022
    • Citations: 32

 

  • Retracted: Internet of things in the management of chronic diseases during the COVID‐19 pandemic: A systematic review
    • Authors: A. Shamsabadi, Z. Pashaei, A. Karimi, P. Mirzapour, K. Qaderi, M. Marhamati, et al.
    • Journal: Health Science Reports
    • Year: 2022
    • Citations: 27

 

  • LAIU-Net: a learning-to-augment incorporated robust U-Net for depressed humans’ tongue segmentation
    • Authors: M. Marhamati, A.A.L. Zadeh, M.M. Fard, M.A. Hussain, K. Jafarnezhad, et al.
    • Journal: Displays
    • Year: 2023
    • Citations: 18

 

  • Active deep learning from a noisy teacher for semi-supervised 3D image segmentation: Application to COVID-19 pneumonia infection in CT
    • Authors: M.A. Hussain, Z. Mirikharaji, M. Momeny, M. Marhamati, A.A. Neshat, R. Garbi, et al.
    • Journal: Computerized Medical Imaging and Graphics
    • Year: 2022
    • Citations: 11

 

  • Comparing Serum Levels of Vitamin D and Zinc in Novel Coronavirus–Infected Patients and Healthy Individuals in Northeastern Iran, 2020
    • Authors: S.J. Hosseini, B. Moradi, M. Marhamati, A.A. Firouzian, E. Ildarabadi, A. Abedi, et al.
    • Journal: Infectious Diseases in Clinical Practice
    • Year: 2021
    • Citations: 6

 

  • Comparing the effects of pulsatile and continuous flushing on time and type of peripheral intravenous catheters patency: a randomized clinical trial
    • Authors: S.J. Hosseini, F. Eidy, M. Kianmehr, A.A. Firouzian, F. Hajiabadi, M. Marhamati, et al.
    • Journal: Journal of Caring Sciences
    • Year: 2021
    • Citations: 4

 

  • Emergency Medical Service Personnel Satisfaction Regarding Ambulance Service Facilities and Welfare
    • Authors: A. Jesmi, H.M. Ziyarat, M. Marhamati, T. Mollaei, H. Chenari
    • Journal: Iranian Journal of Emergency Medicine
    • Year: 2015
    • Citations: 2

 

  • Patient’s airway monitoring during cardiopulmonary resuscitation using deep networks
    • Authors: M. Marhamati, B. Dorry, S. Imannezhad, M.A. Hussain, A.A. Neshat, et al.
    • Journal: Medical Engineering & Physics
    • Year: 2024
    • Citations: 1

 

  • Comparison of using cold versus regular temperature tube on successful nasogastric intubation for patients in toxicology emergency department: a randomized clinical trial
    • Authors: S.R. Mazlom, A.A. Firouzian, H.M. Norozi, A.G. Toussi, M. Marhamati
    • Journal: Journal of Caring Sciences
    • Year: 2020
    • Citations: 1

 

  • Comparison of using cooled and regular-temperature nasogastric tubes on the success of nasogastric intubation
    • Authors: S. Mazlom, M. Marhamati, H. Norozi, A. Ghasemi Toosi
    • Journal: Evidence Based Care
    • Year: 2015
    • Citations: 1

 

 

Patrícia Takaki | Artificial Intelligence | Best Researcher Award

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 Prof . Patrícia Takaki | Artificial Intelligence | Best Researcher Award

 Prof , Patrícia Takaki ,State University of Montes Claros, Brazil

Prof. Patrícia Takaki is a distinguished academic at the State University of Montes Claros, Brazil. She holds a PhD in [specific field, if known], showcasing her deep expertise and commitment to advancing knowledge in her area of specialization. Prof. Takaki has made significant contributions through her research, which includes numerous publications in reputed journals and conference presentations. Her work primarily focuses on [specific research interests, if known], where she has developed innovative approaches and solutions. In addition to her research, Prof. Takaki is dedicated to teaching and mentoring students, fostering the next generation of scholars and professionals. She is actively involved in various academic and professional communities, contributing to the broader discourse in her field. Prof. Takaki’s dedication to excellence in both research and education has earned her recognition and respect within the academic community.

 

Professional Profiles:

Scopus

Education :

Doctorate in Information Science,Universidade Federal de Santa Catarina (UFSC), Florianopolis, Brazil, 2019
Title: Ciência de Dados aplicada à EaD
Advisor: Moisés Lima Dutra,Keywords: Information Science, Educational Data Mining,Knowledge Areas: Information Science, Computer Science, Information Management,Master’s in Computer Science,Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil, 2001 – 2007,Title: Variações e aplicações do algoritmo de Dijkstra
Advisor: Prof. Dr. Orlando Lee,Keywords: Dijkstra’s Algorithm, Graph Theory, Shortest Paths, Data Structures, Point-to-Point Problem
Knowledge Areas: Graph Theory, Analysis of Algorithms and Computational Complexity,Specialization in Computação Aplicada à Educação
Universidade de São Paulo (USP), Sao Paulo, Brazil, 2018 – 2020,Title: Predição de reprovação na educação a distância: um estudo comparativo,Advisor: Seiji IsotaniGraduation in Computação – ênfase em Sistemas de Informação
Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil, 1996 – 2000,Graduation in Biologia – Licenciatura
Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil,,1997 – 2000Improvement Course in Engenharia de Software,Universidade Estadual de Montes Claros (UNIMONTES), Montes Claros, Brazil,,2007

Professional Experience:

Universidade Estadual de Montes Claros (UNIMONTES), 2003 – Present,Position: Full-time University Professor at the Department of Computer Science (DCC), Center for Exact and Technological Sciences (CCET),Responsibilities,Faculty member involved in various teaching, research, and administrative roles.,Active in distance education projects at the Open University of Brazil (UAB) at UNIMONTES since 2008.,Coordinated the largest institutional proposal in Brazil under Call 015/CAPES/DED for promoting the use of ICT in undergraduate programs.,Developed educational materials and interactive objects for the training of 43,000 PMMG police officers for TCO registration.,Coordinated the Information Systems Course and Pedagogical Support at the Distance Education Center at UNIMONTES.,Member of the Editorial Board of Unimontes Press and the Business Incubator at Unimontes (Inemontes).

Research and Projects:

Project: Construção de um supercomputador de baixo custo para processamento de alto desempenho utilizando o sistema Beowulf (2008-2009),Description: Installation, configuration, and comparative testing of a high-performance Beowulf cluster.,Members: Patrícia Takaki Neves, Renato Dourado Maia, Hércules Mohamed.

Awards and Recognitions:

  • 2023:,Madrinha da Turma, Formandos do Curso de Sistemas de Informação – UNIMONTES.,Orientadora do trabalho vencedor do Prêmio de Melhor Iniciação Científica da área de Ciências Exatas – UNIMONTES.
  • 2022: Approved for the position of Agente de Tecnologia da Informação, Banco do Brasil.
  • 2020: Professora Homenageada, Formandos do Curso de Sistemas de Informação – UNIMONTES.
  • 2018: Professora Homenageada, Formandos do Curso de Sistemas de Informação – UNIMONTES.
  • 2017:  Madrinhade Formatura Formandos do Curso de istemas de Informação – UNIMONTES.

Publications :

  • 2023: Text mining applied to distance higher education in Education and Information Technologies.
  • 2022: A Proposed Framework for Evaluating the Academic-failure Prediction in Distance Learning in Mobile Networks and Applications.
  • 2012: Utilização de um framework metodológico para avaliação da usabilidade do ambiente virtual de aprendizagem da Unimontes: Virtualmontes in Revista Multitexto.
  • 2012: Sistema de informação para apoio ao controle da leishmaniose visceral na cidade de Montes Claros/MG in Revista Clique.
  • 2002: Interval graphs with repeats and the DNA fragment assembly problem in IC Technical Reports.
  • 2021: Ciência de Dados na Educação: contribuições interdisciplinares at IV Workshop de Informação, Dados e Tecnologia.
  • 2021: Lançamentos dos livros on Competência em Informação at IV Seminário de Pesquisas e Práticas sobre Competência em Informação de Santa Catarina.
  • 2021: Mineração de Dados Educacionais at Congresso Internacional de Tecnologia na Educação.