Tag: AI Innovation Award

Glen Liau, Medicine, AI Innovation Award

Posted on by scizentox scizentoxLeave a Comment on Glen Liau, Medicine, AI Innovation Award

Asst. Prof Glen Liau: Orthopaedic Surgeon at NUHS, Singapore

Dr. Liau Zi Qiang Glen is a Consultant Orthopaedic Surgeon specializing in Adult Reconstruction and Joint Replacement Surgery at the National University Hospital (NUH) and Alexandra Hospital in Singapore. With a commitment to advancing medical science, he is currently pursuing a fellowship in Orthopaedic Surgery at the renowned Stanford University School of Medicine. In addition to his clinical work, Dr. Liau is an Adjunct Assistant Professor at the Yong Loo Lin School of Medicine, National University of Singapore (NUS), where he teaches and mentors the next generation of healthcare professionals. He also holds the role of Deputy Chief Medical Informatics Officer at NUH, where he spearheads initiatives to integrate technology and informatics into patient care. His areas of expertise include robotic knee replacement, minimally invasive surgery, and the application of healthcare informatics to improve surgical precision and patient outcomes.

Online Profiles

Google Scholar Profile

Since 2020, Dr. Liau’s research has garnered significant attention, with a total of 186 citations across his publications. His work continues to influence the field of orthopaedics, as evidenced by his h-index of 8 and i10-index of 7, which reflect both the volume and impact of his contributions to scientific knowledge. These metrics demonstrate his ongoing commitment to advancing the field and providing valuable insights into surgical techniques, patient outcomes, and medical informatics.

Education

Dr. Liau’s educational background reflects a blend of medical excellence and strategic thinking. He graduated with a Bachelor of Medicine, Bachelor of Surgery (MBBS) from the National University of Singapore (NUS), where he developed a keen interest in orthopaedics. He further advanced his expertise with a Master of Medicine in Orthopaedic Surgery from NUS, earning recognition for his contributions to both clinical practice and academic research. Beyond his medical degree, Dr. Liau pursued an MBA at NUS, which helped him hone his leadership and management skills within the healthcare sector. His qualifications are further bolstered by his Fellowship with the Royal College of Surgeons of Edinburgh (FRCSEd), and he continues to pursue further certifications in robotic surgery and medical informatics to stay at the forefront of his field.

Research Focus

Dr. Liau’s research focuses on improving the precision, safety, and outcomes of orthopaedic surgery, particularly through the integration of robotic technology and advanced imaging. His research interest spans a wide array of topics, including the biomechanics of joint replacements, surgical robotics, and healthcare data analytics. He has been at the forefront of studies investigating robotic-assisted total knee replacement surgery, evaluating how such technologies can reduce complications, shorten recovery times, and enhance overall surgical outcomes. In addition, Dr. Liau’s research looks into how predictive modeling and machine learning can be applied in pre-operative planning to customize treatments for patients based on their individual needs, such as predicting the likelihood of surgical success or recovery speed.

Experience

Dr. Liau’s extensive clinical experience includes treating patients with complex joint issues, such as osteoarthritis, fractures, and degenerative diseases. As a Consultant Orthopaedic Surgeon, he has performed hundreds of joint replacement surgeries, including both traditional and robotic-assisted procedures. At the National University Hospital, Dr. Liau also serves as the Deputy Chief Medical Informatics Officer, where he plays a crucial role in developing and implementing digital solutions for improving patient care. His clinical expertise is further complemented by his academic responsibilities, where he leads research initiatives and provides guidance to medical students, residents, and fellow surgeons. He is also actively involved in clinical trials focused on testing new treatments and technologies in orthopaedics, collaborating with both local and international research teams.

Research Timeline

Dr. Liau’s research timeline includes several key milestones, such as his role as Principal Investigator in a groundbreaking study exploring the use of artificial intelligence in predicting post-operative outcomes for patients undergoing knee replacement surgery. He has also contributed to the development of a decision support system (PRECEDE-KOA) that helps guide clinicians in the treatment of knee osteoarthritis, based on patient-specific data. Over the past few years, Dr. Liau has expanded his research into the use of 3D printing and patient-specific instrumentation in joint replacement surgery. His studies on robotic surgery have been published in top-tier journals, and he continues to build upon this work with ongoing investigations into the efficacy of real-time surgical navigation systems. His research projects have been consistently funded by both national and international agencies, underscoring his influence in the field of orthopaedic surgery.

Awards & Honors

Dr. Liau’s exceptional contributions to the medical field have been recognized with numerous prestigious awards. He was the recipient of the P. Balasubramaniam Young Orthopaedic Investigator’s Award at the Singapore Orthopaedic Association Conference, an honor given to outstanding young surgeons in the field. His innovation in robotic knee replacements earned him the Silver Medal at the Singapore Orthopaedic Association Awards. He has also been recognized with the Gold Singapore Health Quality Service Award for excellence in clinical care. In addition, Dr. Liau was awarded a National Research Foundation (NRF) Fellowship for his work in orthopaedic surgery and healthcare informatics. His work has also been featured in numerous international conferences, earning accolades for advancing surgical techniques and improving patient outcomes through the use of technology.

Recent Publications

Dr. Liau’s recent publications reflect his cutting-edge research in orthopaedics and healthcare technology. His study on the use of AI to predict post-operative outcomes in total knee replacement surgeries was published in The Journal of Arthroplasty, where he served as the lead author. He has also co-authored a paper in Knee Surgery & Related Research, which explored a novel technique for enhancing the accuracy of pre-operative planning in robotic-assisted surgeries. In Orthopaedic Journal of Sports Medicine, Dr. Liau published a study on the effectiveness of a hybrid approach combining robotic-assisted surgery and traditional methods in ACL reconstruction. Additionally, his research on the use of machine learning to optimize surgical workflow was featured in JMIR Formative Research. These publications highlight his commitment to improving surgical outcomes and patient care through the integration of technology in clinical practice.

  • Outcomes of an Advanced Epic Personalization Course on Clinician Efficiency through Use of Electronic Medical Records: Retrospective Study
    JG Chen, HX Lai, SM Wong, TLT Pan, EL Lim, ZQG Liau
    Journal: JMIR Formative Research (2025) | 9, e68491

  • Outcomes of ACL Reconstruction with Concomitant Meniscal Surgery: A Retrospective Cohort Study
    ZQG Liau, K Thirukumaran, KZG Yeo, YR Mok, YHD Lee
    Journal: Orthopaedic Journal of Sports Medicine (2025) | 13 (6), 23259671251327600

  • Surgical Fixation of Hip Fractures–A Novel Technique for Pre-Operative Planning
    ZQG Liau, K Thirukumaran, SI Sim, ASR Pang
    Journal: Journal of Orthopaedic Surgery and Research (2025) | 20 (1), 391

  • Predictive Factors of Short Inpatient Stay Following Total Knee Replacement
    ZQG Liau, JZK Toh, L Sathappan, YH Ng
    Journal: Musculoskeletal Care (2024) | 22 (4), e70022

  • Systemic Diclofenac Sodium Reduces Postoperative rhBMP-2 Induced Neuroinflammation: A Rodent Model Study
    GLZ Qiang, SL Jiani, WMR Lam, J Weng, LHK Hua, L Kok, SF Husain, …
    Journal: Spine (2023) | 48 (18), 1326-1334

Strength for the AI Innovation Award

Here’s a concise and organized breakdown of 5 key topics that reflect Dr. Liau’s achievements and contributions, ideal for an AI Innovation Award nomination:

1. AI in Predictive Modeling for Post-Operative Outcomes

Dr. Liau has made significant strides in the integration of AI into orthopaedic surgery, particularly through his artificial intelligence models aimed at predicting post-operative outcomes. His lead authorship on a study published in The Journal of Arthroplasty demonstrated how AI can enhance clinical decision-making and improve patient care by predicting recovery patterns for total knee replacement surgeries. This work not only showcases the promise of AI but also its practical application in personalized medicine.

2. Development of AI-Enhanced Decision Support Systems

Dr. Liau has co-developed PRECEDE-KOA, a decision support system powered by AI, to guide clinicians in treating knee osteoarthritis. This innovative tool leverages machine learning to analyze patient-specific data, such as medical history, imaging, and biomechanics, to suggest optimal treatment pathways. By integrating AI into clinical workflows, the system aims to reduce human error and improve treatment efficacy, ultimately leading to better patient outcomes.

3. Robotic-Assisted Surgery and AI Integration

Dr. Liau’s research into robotic-assisted surgeries, particularly robotic knee replacement, has significantly advanced with the application of AI-driven technologies. His work in blending robotic techniques with AI-enhanced surgical navigation systems helps improve surgical precision, reduce complications, and shorten recovery times. His published work on combining AI with robotic systems in joint surgeries has received attention for its potential to revolutionize orthopaedic practices.

4. Machine Learning for Surgical Workflow Optimization

In his efforts to improve surgical efficiency, Dr. Liau has conducted studies that explore the integration of machine learning algorithms to optimize surgical workflows. By analyzing data from surgeries, including patient profiles and real-time surgical metrics, his research in JMIR Formative Research demonstrated how AI can streamline operations, reduce delays, and enhance surgical outcomes through predictive analytics and automated task management.

5. AI for Personalized Pre-Operative Planning

Dr. Liau’s work in personalized pre-operative planning leverages AI to create individualized treatment plans for patients undergoing orthopaedic surgery. His research on using 3D printing and AI for patient-specific instrumentation is groundbreaking, allowing for better alignment, reduced implant failure rates, and faster recoveries. This work reflects a clear vision for the future of orthopaedic surgery, where AI and technology work hand-in-hand to deliver tailored, precise, and effective treatments.

Fatma Akalın, Computer Science, AI Innovation Award

Posted on by scizentox scizentoxLeave a Comment on Fatma Akalın, Computer Science, AI Innovation Award

Asst. Prof Fatma Akalın: Assistant Professor at Sakarya University, Turkey

Fatma Akalın is an accomplished Assistant Professor in the Department of Computer Engineering at Sakarya University, specializing in the intersection of artificial intelligence, machine learning, and biomedical engineering. Her research is driven by a deep interest in applying AI algorithms to solve complex challenges in healthcare, particularly for disease diagnosis and personalized medicine. With expertise in data science, bioinformatics, and medical imaging, she has made significant strides in automating processes such as genomic sequence classification, anomaly detection in blood cell images, and the development of AI-driven decision support systems. Dr. Akalın’s commitment to advancing research in healthcare technology positions her as a thought leader in both academic and applied AI communities.

Online Profiles

Google Scholar Profile

Citations, h-index, i10-index

  • Citations: Dr. Akalın’s research has accumulated a total of 66 citations across various academic publications, with 61 citations in the last 5 years, reflecting the growing influence and relevance of her work in the field.

  • h-index: With an h-index of 5, Dr. Akalın has made significant contributions, with at least 5 of her publications being cited at least 5 times each. This indicates a solid body of impactful research in her areas of expertise.

  • i10-index: Dr. Akalın holds an i10-index of 1, meaning she has one publication that has been cited 10 times or more, further highlighting the recognition her work has received in the academic community

Dr. Akalın maintains an active and influential presence across multiple online academic platforms. Her publications are widely cited in leading international journals, and she regularly contributes to conferences in fields such as AI, bioinformatics, and computational biology. As an Assistant Editor for Sakarya University Journal of Computer and Information Sciences (SAUCIS), she has an integral role in shaping the research landscape at the university. Her collaborative projects include contributions to national research initiatives that address pressing public health concerns through the use of AI technologies. She has also developed various web-based applications aimed at enhancing healthcare outcomes, integrating both AI and clinical expertise to create innovative solutions for real-world health issues.

Education

Dr. Akalın completed her Doctoral Degree in Computer Engineering at Sakarya University in 2023, where she focused on leveraging AI algorithms for the classification of leukemia subtypes using digital mapping of DNA sequences. Her thesis, titled “Classification of Leukemia Types Using AI-Based Algorithms on DNA Sequences via Digital Mapping Techniques,” reflected her strong commitment to applying cutting-edge computational methods to solve biomedical challenges. She earned her Master’s Degree in 2020, with a thesis on the application of heuristic algorithms for detecting polyps in small intestine images. This work demonstrated her early engagement with AI in medical imaging. Her Bachelor’s Degree was also completed at Sakarya University in 2018, marking the beginning of her academic journey into computer engineering and AI.

Research Focus

Dr. Akalın’s research is deeply rooted in artificial intelligence, machine learning, and bioinformatics. Her primary focus is the integration of AI into healthcare systems, specifically in disease detection and diagnostic applications. She has worked extensively on the classification of genetic sequences, including the use of AI algorithms for identifying and predicting leukemia and other cancers. Additionally, her work includes the development of advanced diagnostic systems based on digital imaging, such as detecting anomalies in medical images like blood cell smears and endoscopic images. In recent years, she has also delved into synthetic data generation for model training, optimizing machine learning algorithms for better clinical decision-making, and exploring data-driven AI models that can adapt to the complexities of real-world clinical environments.

Experience

Dr. Akalın has held the position of Assistant Professor in the Department of Computer Engineering at Sakarya University since September 2023, where she teaches courses in artificial intelligence, web technologies, and data structures. Prior to this role, she served as a Research Assistant at the same department from 2020 to 2023, contributing to numerous research projects, guiding graduate students, and publishing in top-tier journals. During her academic career, she has mentored students on master’s theses and helped develop cutting-edge research in fields such as medical diagnostics, deep learning, and artificial intelligence. Her diverse experience spans both academic and research settings, where she has also collaborated on national-level projects related to AI-based healthcare solutions.

Research Timeline

  • 2025: Dr. Akalın is currently leading a project on the development of an AI-powered decision support chatbot aimed at optimizing sales processes within ERP systems. Additionally, she is working on a real-time system for detecting and counting blast cells in leukemia diagnosis using advanced deep learning methods.

  • 2024: She is working on the development of a web-based AI system that utilizes hybrid data sets to aid in the diagnosis of monkeypox. Additionally, she is exploring the use of AI to assess cardiac risks in adolescents based on EKG images as part of a national TUBITAK-funded project.

  • 2023: Dr. Akalın has initiated a project focused on developing AI-enhanced virtual reality simulations for secondary education, along with another project to build a web-based system to promote sustainable production and consumption in Turkey.

Awards & Honors

Dr. Akalın has been recognized for her outstanding contributions to scientific research, particularly in the application of artificial intelligence to healthcare. She was awarded the 10th İksad Scientific Award in 2019, a prestigious recognition in the field of applied science. She continues to receive recognition for her innovative research on medical diagnostics, and her work has been acknowledged by leading research institutes and journals. Her ability to bridge the gap between AI theory and practical healthcare applications has made her a sought-after researcher and collaborator in both academic and industrial circles.

Top-Noted Publication

  • “Deep Learning-Based Community Classifier Approach for Gastrointestinal Anomaly Detection,” published in Pamukkale University Engineering Journal, 2024, discusses the application of deep learning methods for gastrointestinal anomaly detection, contributing to the growing body of knowledge on AI in medical diagnostics.

  • “Classification of Exon and Intron Regions on DNA Sequences Using SBERT and ANFIS,” published in Journal of Polytechnic, 2024, presents a hybrid approach combining SBERT and ANFIS for DNA sequence classification, a significant advancement in genomic data analysis.

  • “Neural Network-Based Survival Classification in Heart Failure Patients,” published in Arabian Journal for Science and Engineering, 2024, focuses on using neural networks for predicting the survival outcomes of heart failure patients, applying AI to improve personalized treatment strategies.

  • “DNA Genomic Sequence Classification with Digital Signal Processing and EfficientNetB7,” published in Gazi University Journal, 2022, investigates the classification of DNA sequences using deep learning models, contributing to advancements in genomic medicine.

Dr. Akalın’s work continues to push the boundaries of AI in healthcare, and her publications are widely regarded as some of the most significant contributions to the field in recent years.

Strengths for the AI Innovation Award

  1. Pioneering AI Applications in Healthcare: Dr. Akalın’s work in automating disease diagnostics, such as leukemia classification from genomic data and gastrointestinal anomaly detection, showcases her groundbreaking contributions to healthcare through AI. These innovations can significantly improve patient outcomes and revolutionize diagnostic processes.

  2. Cross-Disciplinary Expertise: Dr. Akalın effectively merges AI, machine learning, bioinformatics, and medical imaging to develop advanced diagnostic systems, demonstrating her versatility and expertise in multiple disciplines, and advancing both AI and biomedical engineering.

  3. Leadership in AI-Driven Healthcare Projects: She is leading multiple impactful AI projects, including real-time leukemia detection systems and AI-enhanced decision support tools for healthcare, positioning her as a leader in AI’s practical application in medicine.

  4. Synthetic Data Innovation: Dr. Akalın is pioneering research in synthetic data generation for training AI models, addressing critical challenges in healthcare data scarcity and privacy concerns, and making AI more adaptable for clinical use.

  5. Award-Winning Research: Her contributions have earned recognition, including the 10th İksad Scientific Award, cementing her position as a leading innovator in AI for healthcare, and highlighting the significant impact of her research on both academic and real-world levels.