Miaomiao Ma | Engineering | Best Researcher Award

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Prof. Miaomiao Ma | Engineering | Best Researcher Award

Prof. Miaomiao Ma, north china electric power university, China

Dr. Miaomiao Ma, born in February 1982, is a distinguished Chinese researcher specializing in model predictive control, optimal and robust control, and nonlinear control. Currently serving as an Associate Professor at the School of Control and Computer Engineering, North China Electric Power University, Beijing, he has made significant contributions to renewable power systems and mechatronic systems, particularly in automotive applications. With a strong foundation in control engineering, he has been actively involved in high-impact research and academic collaborations. Dr. Ma has held academic positions in China and Germany, including postdoctoral research at the University of Stuttgart under Prof. Frank Allgöwer. His research focuses on advanced control strategies for energy-efficient and resilient engineering systems. As an accomplished author, he has published extensively in leading journals and conferences, shaping the future of control theory applications in energy and automation. His expertise continues to influence both academia and industry.

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Suitability for the Research for Best Researcher Award – Miaomiao Ma

Dr. Miaomiao Ma is an accomplished researcher in control theory and engineering, particularly in model predictive control, optimal and robust control, and their applications in renewable power and mechatronic systems. His academic journey, from earning a Ph.D. from Jilin University to holding a prominent position as an Associate Professor at North China Electric Power University, highlights a strong foundation in both theoretical and applied research. His international exposure, including post-doctoral research at the University of Stuttgart under the supervision of Frank Allgöwer, further underscores his expertise in control engineering.

Dr. Ma has made significant contributions to the field, as evidenced by his extensive publication record in high-impact journals, including IEEE Transactions on Industrial Electronics, IET Renewable Power Generation, and ISA Transactions. His research primarily focuses on control strategies for micro-grids, wind energy systems, and power system stability, all of which are critical areas in modern energy and automation technologies. His innovative approaches, such as distributed moving horizon control and predictive load frequency control, have practical applications in optimizing energy efficiency and system stability. Additionally, his leadership in securing competitive research grants, including those from the Natural Science Foundation of China, further establishes his credibility as a leading researcher in his field.

🎓 Education 

Dr. Miaomiao Ma earned his Ph.D. in Control Theory and Engineering from Jilin University in 2009, where he developed a disturbance attenuation control scheme for constrained systems under the guidance of Prof. Hong Chen. Prior to that, he completed his Master of Science in Control Theory and Engineering at Jilin University in 2006, focusing on robust control of active suspensions using LMI optimization. His undergraduate studies in Automation, also at Jilin University, provided him with a strong technical foundation in control engineering. Throughout his academic journey, Dr. Ma has consistently demonstrated excellence in control systems, optimization techniques, and predictive control methodologies. His educational background has played a pivotal role in shaping his research trajectory, leading to innovative contributions in model predictive control, nonlinear control strategies, and their applications in renewable energy and automotive systems. His commitment to education and research continues to drive advancements in control engineering.

💼 Professional Experience

Dr. Miaomiao Ma has accumulated extensive academic and research experience, currently serving as an Associate Professor at the School of Control and Computer Engineering, North China Electric Power University (NCEPU), since January 2015. Prior to this, he was an Assistant Professor at NCEPU from 2009 to 2014. His international exposure includes a postdoctoral research tenure at the Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany, under Prof. Frank Allgöwer from 2012 to 2013. Additionally, he was a visiting scholar at the same institute in 2007 and 2006. His professional journey has been marked by cutting-edge research in predictive and robust control, contributing significantly to renewable energy integration, micro-grid systems, and automotive control applications. His collaborative efforts with international researchers have strengthened global advancements in power systems and control engineering, solidifying his reputation as a leading figure in his field.

🏅 Awards and Recognition 

Dr. Miaomiao Ma’s contributions to control engineering and renewable energy systems have earned him several prestigious recognitions. He has received multiple research excellence awards for his work in model predictive control and distributed optimization. His papers have been widely cited, earning accolades in high-impact journals such as IEEE Transactions on Industrial Electronics and IET Renewable Power Generation. He has also been an invited speaker at international conferences, sharing insights on predictive control applications. His research projects have been supported by national and international funding agencies, reinforcing his expertise in control systems. Furthermore, Dr. Ma has been recognized as a leading scholar in his field, contributing to advancements in renewable energy integration, micro-grid optimization, and robust control mechanisms. His outstanding research achievements continue to inspire innovation and development in engineering applications worldwide.

🌍 Research Skill On Engineering

Dr. Miaomiao Ma possesses extensive research expertise in model predictive control, nonlinear control, and robust control strategies, particularly in renewable energy and automotive systems. His work focuses on optimizing micro-grid performance through distributed predictive control, ensuring stability in multi-area power systems. He specializes in H-infinity control, disturbance attenuation, and constrained optimization techniques, enhancing control strategies in energy systems. Dr. Ma’s interdisciplinary approach integrates control theory with mechatronics, resulting in innovative solutions for energy efficiency. His research methodologies involve algorithm development, simulation modeling, and real-time control implementations. With a strong publication record in renowned journals and conferences, he has contributed to shaping advanced control strategies for sustainable engineering. His collaborative projects with international researchers and institutions further demonstrate his ability to drive impactful research in modern control engineering applications.

📖 Publication Top Notes

  • Title: Distributed model predictive load frequency control of the multi-area power system after deregulation
    Authors: M Ma, C Zhang, X Liu, H Chen
    Citations: 164
    Year: 2016
    Journal: IEEE Transactions on Industrial Electronics
  • Title: Distributed model predictive load frequency control of multi-area interconnected power system
    Authors: M Ma, H Chen, X Liu, F Allgöwer
    Citations: 134
    Year: 2014
    Journal: International Journal of Electrical Power & Energy Systems
  • Title: Moving Horizon Tracking Control of Wheeled Mobile Robots With Actuator Saturation
    Authors: H Chen, MM Ma, H Wang, ZY Liu, ZX Cai
    Citations: 99
    Year: 2009
    Journal: IEEE Transactions on Control Systems Technology
  • Title: LFC for multi‐area interconnected power system concerning wind turbines based on DMPC
    Authors: M Ma, X Liu, C Zhang
    Citations: 74
    Year: 2017
    Journal: IET Generation, Transmission & Distribution
  • Title: Disturbance attenuation control of active suspension with non-linear actuator dynamics
    Authors: MM Ma, H Chen
    Citations: 58
    Year: 2011
    Journal: IET Control Theory & Applications
  • Title: Power transfer characteristics in fluctuation partition algorithm for wind speed and its application to wind power forecasting
    Authors: M Yang, D Wang, C Xu, B Dai, M Ma, X Su
    Citations: 34
    Year: 2023
    Journal: Renewable Energy
  • Title: Maximum power point tracking and voltage regulation of two-stage grid-tied PV system based on model predictive control
    Authors: M Ma, X Liu, KY Lee
    Citations: 31
    Year: 2020
    Journal: Energies
  • Title: Constrained H₂ control of active suspensions using LMI optimization
    Authors: M Ma, H Chen
    Citations: 28
    Year: 2006
    Conference: Chinese Control Conference
  • Title: Robust MPC for the constrained system with polytopic uncertainty
    Authors: X Liu, S Feng, M Ma
    Citations: 23
    Year: 2012
    Journal: International Journal of Systems Science
  • Title: Moving horizon ℋ∞ control of variable speed wind turbines with actuator saturation
    Authors: M Ma, H Chen, X Liu, F Allgöwer
    Citations: 20
    Year: 2014
    Journal: IET Renewable Power Generation

Dr. Mlungisi Duma | Artificial Intelligence | Best Researcher Award

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Dr. Mlungisi Duma | Artificial Intelligence | Best Researcher Award

Dr. Mlungisi Duma, University of Johannesburg, South Africa

Dr. Mlungisi Duma is a Senior Researcher and Development Manager at the University of Johannesburg. With over 19 years of experience in the IT profession, he has a rich background in software development and management. Dr. Duma holds a PhD in Electronic and Electrical Engineering, specializing in Artificial Intelligence, from the University of Johannesburg. His research focuses on machine learning, evolutionary computation, and optimization algorithms. He has successfully led numerous projects, published in top-tier journals, and is an active reviewer for multiple prestigious journals. His expertise extends to consultancy, where he manages application development for First National Bank, overseeing code maintenance for ATM systems. Dr. Duma’s contributions to academia and industry showcase his dedication to innovation and leadership in AI research.

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Summary of Suitability for the Research for Best Researcher Award

Dr. Mlungisi Duma’s diverse contributions to the fields of artificial intelligence and evolutionary computation, along with his leadership in both academia and industry, make him highly suitable for the ‘Research for Best Researcher Award’. His ability to bridge the gap between theoretical research and real-world applications, coupled with his strong publication record and professional recognition, demonstrate his excellence as a researcher. He is well-positioned to receive this award, as his work contributes significantly to advancing the field of artificial intelligence.

🎓  Education 

Dr. Mlungisi Duma holds a Master’s degree in Computer Science and a PhD in Electronic and Electrical Engineering, both from the University of Johannesburg. His PhD specialization in Artificial Intelligence equipped him with expertise in machine learning, evolutionary computation, and optimization algorithms. Throughout his academic journey, Dr. Duma has actively engaged in cutting-edge research projects, collaborating with renowned academics and professionals. His commitment to education has been reflected in his role as a judge and reviewer at various academic institutions and scientific journals. As a Senior Member of IEEE and ACM, he continues to contribute to the advancement of AI technologies. Dr. Duma’s academic background is a testament to his passion for innovation, making significant contributions to the field of Artificial Intelligence.

 💼  Experience

With 19 years of experience in the IT industry, Dr. Mlungisi Duma has held various technical and leadership roles. For nine years, he worked as a software developer, honing his skills in coding, system architecture, and application design. Following this, he spent a decade as a Development Manager and Software Architect at First National Bank, where he led teams responsible for developing and maintaining ATM systems. Currently, he is a Senior Researcher and Development Manager at the University of Johannesburg, where he leads AI research initiatives. His extensive experience spans both academic and industry settings, bridging the gap between theoretical research and practical applications. Dr. Duma’s ability to manage multidisciplinary teams and deliver innovative solutions reflects his leadership and technical acumen.

🏅Awards and Honors 

Dr. Mlungisi Duma has received several prestigious awards and honors for his contributions to Artificial Intelligence and software development. He is a Senior Member of IEEE and ACM, recognizing his influence in the academic and professional communities. Dr. Duma’s work has also been recognized through his membership in the Golden Key International Honour Society, a distinction for top-performing academics globally. He has served as a judge at the University of Johannesburg’s Academy of Computer Science project day and has been a frequent reviewer for renowned journals, including IEEE Access, Applied Soft Computing, and the Journal of Mathematical Problems in Engineering. These honors highlight Dr. Duma’s commitment to academic excellence and his significant contributions to advancing AI technologies.

 🌍 Research Focus

Dr. Mlungisi Duma’s research focuses on Artificial Intelligence, particularly in the fields of machine learning, evolutionary computation, and optimization algorithms. He has contributed extensively to developing novel AI models for predictive modeling, control parameter optimization, and feature selection. His recent work includes optimizing ant colony algorithms and using artificial immune systems for collaborative filtering in recommender systems. Dr. Duma’s research is not only theoretical but also has practical applications, as demonstrated by his consultancy projects for First National Bank, where AI-driven solutions are implemented in ATM systems. He has published widely in top-tier journals, reflecting his thought leadership in AI and its applications in diverse sectors. His current projects aim to enhance AI’s role in automation and decision-making across industries.

 📖 Publication Top Notes

  • Sparseness reduction in collaborative filtering using a nearest neighbour artificial immune system with genetic algorithms
    • Citations: 22
  • Optimising latent features using artificial immune system in collaborative filtering for recommender systems
    • Citations: 20
  • Partial imputation of unseen records to improve classification using a hybrid multi-layered artificial immune system and genetic algorithm
    • Citations: 30
  • Classification with missing data using multi-layered artificial immune systems
    • Citations: 4
  • Partial imputation to improve predictive modelling in insurance risk classification using a hybrid positive selection algorithm and correlation-based feature selection
    • Citations: 2

Dr. Rômulo Carleial | Zoology | Best Researcher Award

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Dr. Rômulo Carleial | Zoology | Best Researcher Award

Dr. Rômulo Carleial, Royal Botanic Gardens, Kew, United Kingdom

Rômulo Carleial is an evolutionary biologist based at the Royal Botanic Gardens, Kew, UK. His research spans sexual selection, conservation genetics, and the evolutionary dynamics of phenotypic plasticity. He has a strong academic foundation, having studied in renowned institutions like the University of Oxford and Yale University. Rômulo’s work explores the interplay between genetics and adaptation, contributing to critical conservation efforts. His commitment to science education is evident through his teaching roles in the UK and Brazil. He is passionate about understanding the evolutionary mechanisms that shape biodiversity, aiming to solve ecological challenges.

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Summary of Suitability for the Research for Best Researcher Award:

Rômulo Carleial demonstrates an exceptional profile for the Research for Best Researcher Award. His research spans multiple critical areas, including evolutionary biology, conservation, and genetics, with a focus on sexual selection, genetic plasticity, and conservation biology. His reflective statement highlights a deep engagement with contemporary scientific questions, such as the philosophical implications of the Extended Evolutionary Synthesis, showing thought leadership in evolutionary theory.

🎓 Education

Rômulo Carleial has a rich educational background, beginning with his B.S. in Biology from the Federal University of Minas Gerais, Brazil. He further pursued his academic journey with an MSc in Ecology and Wildlife Management, where he developed his expertise in evolutionary biology. His DPhil in Zoology from the University of Oxford deepened his understanding of genetics and sexual selection. Additionally, Rômulo gained valuable experience as a visiting researcher at Yale University and Florida International University, honing his skills in evolutionary and conservation science, contributing to his global scientific perspective.

💼 Experience

Rômulo Carleial’s experience is diverse and impactful, with a PDRA position at the Royal Botanic Gardens, Kew, UK, focusing on conservation genetics. He has served as a tutor at Oxford University, delivering lectures and conducting practical demonstrations. His international teaching experiences include delivering courses in Brazil and the UK, alongside fieldwork supporting biodiversity conservation. Rômulo’s work extends to community outreach, organizing science events and talks to promote evolutionary biology education. His scientific collaborations have led to numerous international presentations, further cementing his reputation in evolutionary and conservation sciences.

🏅Awards and Honors

Rômulo Carleial has received numerous prestigious awards. In 2022, he co-authored a DEFRA grant that secured £438,704 to investigate the genetic basis of AOD. He was also a recipient of CNPq DPhil and MSc international scholarships, which funded his advanced research at Oxford University. These scholarships, along with CAPES Science Without Borders funding, supported his studies and international collaborations. His ability to secure competitive grants and scholarships highlights his research excellence and commitment to advancing evolutionary biology and conservation.

🌍 Research Focus

Rômulo Carleial’s research focuses on the intersection of evolutionary biology, conservation, and genetics. His earlier work examined sexual selection and sexual dichromatism, while his current interests lie in understanding how genetics and phenotypic plasticity contribute to adaptive traits in organisms. His research on the genetic basis of plant resistance to pathogens, particularly in oak trees, aims to protect ecosystems from climate change and disease. He is also exploring the philosophical implications of the Extended Evolutionary Synthesis, focusing on organismal agency in evolution and its conservation biology impact.

 📖 Publications Top Notes

Circadian patterns in male sexual behaviour and female resistance in a polygynandrous bird
A first draft genome of holm oak (Quercus ilex subsp. ballota), the most representative species of the Mediterranean forest and the Spanish agrosylvopastoral ecosystem “dehesa”
Disentangling the causes of temporal variation in the opportunity for sexual selection
Temporal dynamics of competitive fertilization in social groups of red junglefowl (Gallus gallus) shed new light on avian sperm competition
Dynamic phenotypic correlates of social status and mating effort in male and female red junglefowl, Gallus gallus

Dr. Roohollah Shirani Faradonbeh | Mining Engineering | Best Researcher Award

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Dr. Roohollah Shirani Faradonbeh | Mining Engineering | Best Researcher Award

Dr. Roohollah Shirani Faradonbeh, Curtin University, Australia

Dr. Roohollah Shirani Faradonbeh is an accomplished mining engineer with expertise in intelligent mining, mine electrification, and sustainable resource management. Currently, he serves as an Assistant Professor at Curtin University’s WA School of Mines, where he contributes to innovative research in digital mining technologies and advanced rock mechanics. With a PhD in Mining Engineering from the University of Adelaide, his research focuses on AI-driven predictive models for rockburst risk assessment in underground mines. Dr. Shirani has published extensively on topics like mine tailings recovery, blasting optimization, and sustainable mining practices.

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Summary of Suitability for the “Research for Best Researcher Award” – Roohollah Shirani Faradonbeh

Dr. Roohollah Shirani Faradonbeh has an outstanding academic background and extensive experience in the field of mining engineering, making him a highly suitable candidate for the Research for Best Researcher Award. His research focuses on critical areas such as rockburst phenomena in deep underground mining, which has significant implications for safety and operations in the mining industry. His development of AI-based models and novel testing methodologies, as demonstrated in his doctoral work, has opened new frontiers in intelligent mining, especially in predicting and mitigating rockburst risks.

 🎓Education

Dr. Shirani holds a PhD in Mining Engineering from the University of Adelaide, where his thesis explored AI-based models for predicting and controlling rockburst phenomena in deep underground mines. His MSc in Mining Engineering from Tarbiat Modares University focused on minimizing blast-induced ground vibrations using gene expression programming. During his BSc at the University of Kashan, he investigated methods for reducing the back-break phenomenon in Iran’s Sungun Copper Mine. His educational journey highlights his expertise in predictive modeling, experimental mechanics, and sustainable mining practices.

 💼 Experience

Dr. Shirani has held multiple academic and industry roles, including his current position as Assistant Professor at Curtin University’s WA School of Mines. He has served as an industry advisor for Fortescue Metals Group and was a research and teaching assistant at the University of Adelaide. His teaching portfolio covers advanced topics like rock excavation technology, mine automation, and slope engineering. In addition to academic contributions, Dr. Shirani has supervised numerous PhD and M.Phil. students in fields such as autonomous mining systems, rockburst early warning tools, and environmental impact assessments for deep-sea mining.

 🏅Awards and Honors

Throughout his career, Dr. Shirani has received recognition for his contributions to mining engineering and research excellence. He has been honored with multiple academic awards for his innovative work in intelligent mining systems and AI-driven rockburst models. His research on blasting operations and ground vibration prediction has garnered attention from industry and academia alike. Additionally, Dr. Shirani has played a key role in international mining conferences, where his contributions to sustainable mining and resource recovery have been highly regarded by peers and industry professionals.

🌍 Research Focus

Dr. Shirani’s research centers on cutting-edge mining technologies, focusing on areas like mine digitalization, autonomous systems, and AI-based predictive models. He is particularly interested in the electrification and decarbonization of mining operations, as well as sustainable mine rehabilitation and waste management. His work in the experimental analysis of rockburst behavior and mine tailings recovery has paved the way for advancements in mining safety and efficiency. He also explores alternative mining methods, such as deep-sea mining and asteroid mining, reflecting his forward-thinking approach to resource extraction.

 📖 Publications Top Notes

Forecasting blast-induced ground vibration developing a CART model
Cited by: 172
Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction
Cited by: 171
Prediction of the uniaxial compressive strength of sandstone using various modeling techniques
Cited by: 164
Combination of neural network and ant colony optimization algorithms for prediction and optimization of flyrock and back-break induced by blasting
Cited by: 153
Long-term prediction of rockburst hazard in deep underground openings using three robust data mining techniques
Cited by: 147

Dr. Gloria Grice | Pharmacy | Best Researcher Award

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Dr. Gloria Grice | Pharmacy | Best Researcher Award

Dr. Gloria Grice, University of Health Sciences and Pharmacy in St. Louis, United States

Gloria R. Grice, Pharm.D., is an accomplished academic leader and healthcare professional. She currently serves as the Associate Dean for Academic Affairs at the St. Louis College of Pharmacy, University of Health Sciences and Pharmacy in Saint Louis. With over two decades of experience in pharmacy education, Dr. Grice holds additional roles as a Professor (Non-Tenure Track) in the Department of Pharmacy Practice and a Courtesy Assistant Professor at Goldfarb School of Nursing. She earned her Doctor of Pharmacy degree from the University of Maryland, where she also completed pre-pharmacy coursework. Dr. Grice’s expertise spans pharmacotherapy, pharmacy practice, and interprofessional healthcare education. She has been recognized for her contributions to student-centered learning and ability-based education. Throughout her career, Dr. Grice has led innovative teaching and clinical practice initiatives, preparing future healthcare professionals to excel in diverse clinical settings.

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Evaluation for Research for Best Researcher Award: Gloria R. Grice

Summary of Suitability
Gloria R. Grice stands out as a highly accomplished academic and healthcare professional with extensive experience in both clinical practice and academic leadership. Her tenure as Associate Dean for Academic Affairs, coupled with her long-standing role as a Professor in Pharmacy Practice, highlights her capacity for leadership, mentorship, and innovation in pharmacy education. Her rich educational background, including a Doctor of Pharmacy degree from the University of Maryland, and her specialty residency in Family Medicine, establish her as an expert in her field.

  🎓 Education 

Gloria R. Grice completed her Doctor of Pharmacy (Pharm.D.) from the University of Maryland, Baltimore, in May 2002. Prior to her Pharm.D., she pursued Pre-Pharmacy studies at the University of Maryland, College Park, from 1996 to 1998. Her academic journey was marked by an emphasis on both foundational science and clinical pharmacy practice. Dr. Grice’s education has laid the groundwork for her extensive involvement in pharmacy practice and academic leadership. Her passion for advancing pharmacy education is reflected in her current role as Associate Dean for Academic Affairs and as a Professor (Non-Tenure Track) in the Department of Pharmacy Practice. Dr. Grice continues to contribute to educational advancements by developing innovative curricula that integrate pharmacotherapy, interprofessional education, and patient-centered care approaches.

 💼 Experience

Dr. Gloria R. Grice has over two decades of experience in pharmacy practice and academia. Since July 2021, she has been the Associate Dean for Academic Affairs at the St. Louis College of Pharmacy, University of Health Sciences and Pharmacy in Saint Louis. She has also held the role of Professor (Non-Tenure Track) in the Department of Pharmacy Practice since 2015. Dr. Grice’s teaching career includes serving as a course coordinator, lecturer, and preceptor for numerous pharmacy and interprofessional education courses. Her earlier roles include Clinical Instructor and Clerkship Preceptor, where she provided experiential education in primary care and geriatrics. Dr. Grice’s residency at St. John’s Mercy Family Medicine expanded her clinical practice in various specialties, including internal medicine and geriatrics. Her clinical and educational expertise continues to shape the next generation of pharmacists and healthcare professionals.

  🏅Awards and Honors 

Dr. Gloria R. Grice has received several recognitions for her contributions to pharmacy education and clinical practice. She holds certifications in Advanced Cardiac Life Support (ACLS) and Immunization from the American Pharmacists Association, demonstrating her clinical proficiency. Additionally, she has been a Board Certified Pharmacotherapy Specialist since 2003, further renewed in 2010 and 2017, underscoring her expertise in pharmacotherapy. Dr. Grice is also licensed to practice pharmacy in both Missouri and Maryland. Throughout her career, she has been honored for her commitment to student-centered, ability-based education, particularly in the areas of primary care and interprofessional healthcare education. Her role in shaping experiential learning and preceptorship has earned her significant respect among peers and students alike. Dr. Grice’s leadership in academic administration further exemplifies her dedication to advancing the field of pharmacy education.

  🌍 Research Focus 

Dr. Gloria R. Grice’s research focuses on interprofessional education, pharmacotherapy, and innovative approaches to healthcare education. She is particularly interested in how collaborative, patient-centered care can be enhanced through better integration of pharmacists into interprofessional healthcare teams. Her work explores the role of pharmacy in managing chronic conditions such as diabetes, hypertension, and heart failure, as well as the optimization of pharmacogenomics in primary care settings. Dr. Grice has contributed to research on educational strategies, including ability-based learning and assessment-driven methodologies. Her goal is to advance the quality of pharmacy education, preparing healthcare professionals to deliver comprehensive, team-based care. Dr. Grice’s research also highlights the importance of experiential learning and preceptorship in cultivating future leaders in pharmacy practice.

  📖 Publications Top Notes

Use of pharmacogenetic and clinical factors to predict the therapeutic dose of warfarin
  • Citations: 998
Integration of genetic, clinical, and INR data to refine warfarin dosing
  • Citations: 267
Genetic-based dosing in orthopedic patients beginning warfarin therapy
  • Citations: 225
A polymorphism in the VKORC1 regulator calumenin predicts higher warfarin dose
  • Citations: 126
Laboratory and clinical outcomes of pharmacogenetic vs. clinical protocols for warfarin initiation in orthopedic patients
  • Citations: 100