M
Md Shadiqul Hoque
Researcher
faculty
College of Medicine Administration
6 h-index
13 pubs
133 cited
Research Areas
Links
Biography and Research Information
OverviewAI-generated summary
Md Shadiqul Hoque's research focuses on healthcare quality improvement and the application of advanced medical imaging techniques for disease prognostication. He has contributed to studies investigating the prediction of disease progression in relapsed multiple myeloma, utilizing traditional risk models alongside PET-CT imaging and minimal residual disease status. Hoque also participated in the "RQUEST" committee, an institutional initiative aimed at enhancing quality improvement education and project implementation for hematology/oncology fellows.
His work involves collaborations with researchers at the University of Arkansas for Medical Sciences, including Jim Zhongning Chen, Alan Baltz, Sajjad Akbar Bhatti, and Troy Schmit. Hoque's scholarly output includes four publications with an h-index of 2 and 5 total citations. He remains an active researcher, with his most recent publication in 2023.
Metrics
- h-index: 6
- Publications: 13
- Citations: 133
Selected Publications
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Participation in a multidisciplinary institutional committee, “RQUEST,” to enhance quality improvement education, project design, and implementation for hematology/oncology fellows. (2023)
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Feasibility of Outpatient Stem Cell Transplantation in Multiple Myeloma and Risk Factors Predictive of Hospital Admission (2022)
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Eight-Color Flow Cytometry Phenotypic Markers and Disease Progression in Monoclonal Gammopathy of Unknown Significance (2021)
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Salvage Autologous Stem Cell Transplantation in Daratumumab-Refractory Multiple Myeloma (2021)
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Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status (2021)
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Salvage autologous stem cell transplantation in daratumumab refractory multiple myeloma (MM). (2021)
Collaboration Network
Top Collaborators
David L. Baker
Winthrop Rockefeller Foundation (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Milan Bimali
Arkansas Children's Hospital
1 shared publication
In database
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Luis F. Carrillo
University of Arkansas for Medical Sciences (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Archana Sachedina
University of Arkansas for Medical Sciences (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Daisy Alapat
University of Arkansas for Medical Sciences (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Mathew Kottarathara
Winthrop Rockefeller Foundation (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Richa Parikh
University of Arkansas for Medical Sciences (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Amani Erra
University of Arkansas for Medical Sciences
1 shared publication
In database
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Angel Mitma
Winthrop Rockefeller Foundation (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Pankaj Mathur
University of Arkansas for Medical Sciences (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Yetunde Ogunsesan
University of Arkansas for Medical Sciences (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Lakshmi Yarlagadda
University of Arkansas for Medical Sciences (US)
1 shared publication
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Sravani Gundarlapalli
University of Arkansas for Medical Sciences
1 shared publication
In database
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Sharmilan Thanendrarajan
University of Arkansas for Medical Sciences
1 shared publication
In database
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
Maurizio Zangari
University of Arkansas for Medical Sciences
1 shared publication
In database
- Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status
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