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Scientist | Physiotherapist | Educator | Meta-analyst | Reiki Master & Teacher (Top-Level)

85.7%

Q1 Publications

206

Google Scholar Citations in just over 4 years

€500k+

International Funding

10+

Global Collaborations

Assoc. Prof. Dr. Gokhan YAGIZ

Scientist | Physiotherapist | Educator | Meta-analyst | Reiki Master-Teacher

Assoc. Prof. Dr Gokhan YAGIZ is a physiotherapist, academician, and researcher specialising in sports physiotherapy, musculoskeletal rehabilitation, sports medicine, medical imaging, and rehabilitation science. His interdisciplinary research integrates musculoskeletal ultrasound and magnetic resonance imaging, shear wave elastography, artificial intelligence, robotics, biomechanics, and evidence synthesis to advance precision diagnosis, injury prevention, rehabilitation, and human performance. His work focuses on elite athlete performance optimisation, muscle architecture and morphology, hamstring injury mechanisms, sarcopenia, healthy ageing, medical imaging technologies, rehabilitation robotics and exoskeletons, and the development of innovative diagnostic and rehabilitation solutions through systematic reviews, meta-analyses, and translational research.

Research Interests

Sports Medicine & Human Performance

  • Elite athlete performance optimization

  • Sports injury prevention and risk reduction

  • Mechanisms of Sports Injuries and Rehabilitation Procedures

  • Return-to-sport assessment and decision-making

  • Human performance in athletic and military populations

  • Exercise rehabilitation and performance enhancement

Medical Imaging & Rehabilitation Technology

  • Musculoskeletal ultrasound imaging

  • Magnetic resonance imaging (MRI)

  • Shear wave elastography

  • Quantitative muscle imaging

  • Muscle architecture, morphology, and biomechanics

  • Sarcopenia and healthy ageing

  • Robotic exoskeletons and rehabilitation robotics

  • Functional electrical stimulation (FES)

  • Exergames and digital rehabilitation technologies

  • Artificial intelligence and machine learning in healthcare

  • Medical image analysis and diagnostic innovation

Research Methodology & Data Science

  • Systematic reviews and meta-analyses

  • Evidence synthesis and evidence-based practice

  • Research methods in health sciences

  • Structural equation modelling (SEM)

  • Advanced statistical analysis

  • Clinical and epidemiological research

  • Data science using Python, R, JASP, SPSS, and Stata

Current Focus

My current research aims to integrate Rehabilitation science, medical imaging, and artificial intelligence to improve the diagnosis, prevention, and treatment of musculoskeletal disorders. It also seeks to enhance human performance across athletic, military, and clinical groups.

Skills

Imaging & assessment

  • Musculoskeletal Ultrasound

  • Shear Wave Elastography

  • MRI

  • ImageJ

  • OsiriX MD

Technical Expertise

Clinical & rehabilitation

  • Orthopaedic and Sports Physiotherapy

  • Robotic Exoskeletons

  • Exergames

  • EMG

  • Eye-tracking

  • FES

  • Telerehabilitation

Statistics & data science

  • Python (Pandas)

  • R

  • SPSS

  • Stata

  • JASP

  • RevMan

  • Comprehensive Meta-Analysis

  • Structural Equation Modelling

Research methods

  • Evidence Synthesis

  • Prospective, cross-sectional and Retrospective studies

  • Sports Injury Prediction

  • Diagnostic Biomarkers

  • RegressionAnalyses

  • Machine Learning

  • Mediation-Moderation Analyses

A Recent Flagship Project

3D Muscle and Tendon Texture Analysis

Our ongoing research pioneers using 3D ultrasound texture analysis to identify early diagnostic markers for various diseases. By combining quantitative imaging with machine learning algorithms, we turn laboratory discoveries into real-world clinical diagnostic tools.

This global framework combines clinical sports physiotherapy with cutting-edge computational diagnostics to provide objective, non-invasive muscle quality assessments.

Collaborate on Translational Science

We welcome inquiries from international research peers, grant funding bodies, and prospective PhD candidates interested in quantitative imaging and sports rehabilitation.