Prague Brains Group

Statistical Analyses

We perform various levels of statistical analyses in the extent of individual needs, using many statistical software packages to suit specific properties of your research:

  • Descriptive statistics
  • Parametric and non-parametric inferential methods
  • Predictive statistical correlation models
  • Predictive statistical regression models

Types of software we work with, including graphical softwares:

  • R (R Foundation)
  • Python (Python Software Foundation)
  • STATISTICA (StatSoft)
  • MATLAB (MathWorks)
  • OriginPro (OriginLab Corporation)
  • Excel (Microsoft Corporation)
  • MetaXL (EpiGear)

Machine Learning & Artificial Intelligence


We actively employ a range of machine learning (ML) and artificial intelligence (AI) methods to analyze complex medical data. By integrating these ML and AI techniques into our research workflow, we improve data interpretation and the overall accuracy of predictions, contributing to advancements in scientific and clinical applications.

Methods we utilize include:

  • Supervised Learning - We work with labeled datasets to train models that can predict outcomes based on input features. This is extensively used in tasks such as classification and regression.
  • Unsupervised Learning - By applying unsupervised learning techniques, we explore hidden structures within unlabeled data, particularly for clustering, anomaly detection, and dimensionality reduction.
  • Deep Learning & Neural Networks - For complex data types, we use deep learning models to extract intricate features and uncover deeper relationships within the data.

ML and AI tools we use include:

  • Python (Python Software Foundation)
  • Scikit-learn (Open Source)
  • Keras (Open Source)
  • MATLAB (MathWorks)

 

Methodology of Systematic Reviews and Meta-Analyses

We provide guidance through the process of systematic review/meta-analysis construction based on many years of experience. Our work is based on extended cooperation for creating high-quality systematic reviews via efficient and evidence-based solutions.

Our work for you includes assistance during the construction of PICO statement, establishing inclusion and exclusion criteria, literature search, literature selection, data extraction, and we perform final both qualitative and quantitative data synthesis with all kinds of graphical illustrations. Final assistance during the manuscript preparation is included as well.

Guidelines, risk of bias assessments and software we work with:

Guidelines:

  • Working with the latest versions of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), as a globally accepted evidence-based minimum set of items for reporting in systematic reviews and meta-analyses.
  • Working with the latest versions of Meta-analysis of Observational Studies in Epidemiology (MOOSE) statements (less frequently used).
  • Performing advisable preregistration of your systematic review/meta-analysis at the International Prospective Register of Systematic Reviews (PROSPERO; https://www.crd.york.ac.uk/Prospero).

Risk of Bias Assessment:

  • Newcastle-Ottawa Scale for nonrandomized studies
  • Jadad Scale for randomized clinical trials
  • Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2)
  • Cochrane Risk of Bias Assessments (Rob 2, ROBINS-I, ROB-ME)

Assessments of heterogeneity and statistical analysis:

  • Modelling of forest-plots via MetaXL (EpiGear) Software or within stand-alone packages, such as Cochrane RevMan:

Stand-alone packages:

We routinely used software packages used for statistical analyses, more in detail introduced in an individual page.

We create adequate modifications of abovementioned scales in order to provide bias assessment of the best fit for individual needs.

MRI data analyses

 

Education and Supervision

Prague Brains Group is driven by a commitment to advancing neurosurgical research through a comprehensive approach that emphasizes innovation, education, and collaboration. By enhancing the skills and knowledge of students, clinicians, and researchers, we foster an environment of continuous learning and discovery. Through rigorous education and active involvement in groundbreaking projects, we equip future leaders with the tools needed to contribute to the evolving field of neurosurgery. Collaboration with academic institutions, industry partners, and experts ensures that  research opts for the scientific and medical progress.

Literature Review Conduction:  

  • Techniques for identifying relevant research papers  
  • Systematic literature review methods
  • Efficient use of databases and reference management software

Supervision and Control of Scientific Literature Work:  

  • Guidance in evaluating the quality of research papers  
  • Organizing and summarizing scientific literature  
  • Critical appraisal skills (bias detection, statistical significance)

 Data Analysis and Interpretation:

  • Understanding basic and advanced statistical methods  Data visualization techniques (graphs, charts, etc.)
  • Interpretation of data in the context of scientific hypotheses

Explanation of Methods Used in Research:  

  • Detailed breakdown of methodologies used in neurosurgical studies  
  • Understanding clinical trials, imaging techniques, and lab protocols 
  • Training on ethical considerations in research methodology

Manuscript Writing:  

  • Structure of scientific papers (Introduction, Methods, Results, Discussion)  
  • Clear and concise scientific writing  
  • Referencing and avoiding plagiarism  
  • Responding to peer reviews and revisions

Topic Selection for Research:     -

  • How to assess the novelty and feasibility of a research question  
  • Matching personal interests with research trends in neurosurgery  
  • Techniques for narrowing down broad topics into focused research questions

Involvement in Ongoing Projects: 

  • Opportunities to contribute to existing research studies  
  • Participation in different phases of research (data collection, analysis, manuscript preparation)  
  • Learning about multidisciplinary collaboration in neurosurgical research

Administrative Assistance: 

  • Understanding research project administration (grant applications, ethical approvals)  
  • Paperwork management and research documentation  
  • Knowledge of legal and institutional guidelines for research

Presentation Skills:     

  • Crafting effective presentations of scientific data  
  • Public speaking and delivery techniques  
  • Use of PowerPoint, charts, and visual aids for scientific communication

Attending Scientific Conferences:

  • Help with preparing abstracts and posters for presentation
  • Networking skills with other researchers and experts 
  • Learning from cutting-edge research presentations

Grant Proposal Writing:

  • Identifying funding sources for neurosurgical research 
  • Writing compelling grant proposals
  • Budgeting and timeline planning for research projects