01
RETROBREAST
Real-world programme exploring presentation, management and outcomes of breast cancer in routine clinical practice.
View project ↗Mohamed Aimene Melzi
Cancer care,
clinical research
& data.
Medical oncologist and clinical researcher working at the intersection of oncology, real-world evidence and applied data science.
M
oncology · evidence · data
RWE
Python
Clinical research
ONCOLOGY
REAL-WORLD EVIDENCE
CLINICAL RESEARCH
BIOSTATISTICS
DATA SCIENCE
ONCOLOGY
REAL-WORLD EVIDENCE
CLINICAL RESEARCH
About
Physician, researcher and data scientist working in oncology.
My work combines clinical oncology, prospective and real-world research, and reproducible statistical analysis. I am particularly interested in generating clinically useful evidence from routine-care data and multicentre oncology studies.
I design research protocols, structure clinical data, develop analytical workflows and translate complex datasets into interpretable scientific results.
01
Medical oncology
Clinical practice and cancer care.
02
Clinical research
Prospective, observational and real-world studies.
03
Data science
Biostatistics, Python, R and reproducible workflows.
Selected research
Clinical questions. Real-world data. Actionable evidence.
Selected programmes and studies spanning breast cancer, lung cancer and real-world oncology research in Algeria.
02
SAFRO
National real-world oncology research designed to characterise routine practice, access to care and clinical outcomes.
View project ↗03
NEOTRAPSCAL
Multicentre real-world evaluation of pathological complete response after neoadjuvant subcutaneous pertuzumab–trastuzumab plus chemotherapy.
View project ↗Publications
Selected scientific output.
This section is ready to connect to your ORCID, PubMed or a manually curated publication list.
Clinical research
From clinical question to research-grade evidence.
Study design, eCRF architecture, data management and methodological support for observational and multicentre oncology studies.
- Study design & protocols
- Real-world evidence
- eCRF & data structure
- Data management
- Scientific reporting
Data science
Reproducible analysis for clinical research.
Statistical programming and analytical workflows designed for transparent, reproducible and publication-ready biomedical research.
# survival analysis
kmf.fit(time, event)
cph.fit(dataset)
# model diagnostics
check_assumptions()
bootstrap_validation()Teaching & academic work
Teaching clinical oncology, research methodology and applied biostatistics.
01
Medical Oncology
Clinical reasoning, cancer management and evidence-based oncology.
02
Clinical Research
Study design, methodology, scientific writing and critical appraisal.
03
Statistics & Data Science
Applied biostatistics, Python, R and reproducible analysis.
Statistical research support
Mel StatLab
Methodological and statistical support for academic and biomedical research: data management, statistical analysis, publication-ready figures and analytical reports.
Discover Mel StatLabCurrently
What I am working on.
Research
Real-world oncology in Algeria
Focus
Breast · Lung · Bone metastases
Methods
Survival · Regression · RWE
Tools
Python · R · Jupyter
Contact
Let's connect.
For scientific collaboration, research projects, academic enquiries or methodological work.
Social links can be configured in script.js.