Healthcare Data Portfolio

Medicine × Data × Informatics

Dr. Nather Yunis
Suliaman, MD

Healthcare Data Analyst · Clinical Analytics · Health Informatics

Medical Doctor combining clinical reasoning with Python, SQL, healthcare analytics, interoperability standards, and responsible predictive modeling to turn healthcare data into reproducible, decision-ready insights.

MDClinical Background
5Healthcare Projects
Python + SQLAnalytics Stack

01 · About

Clinical reasoning applied to healthcare data.

I am a Medical Doctor building a professional path across healthcare data analytics, clinical analytics, health informatics, and responsible healthcare AI.

My work starts with the healthcare question and unit of analysis, then moves through data quality, reproducible methods, interpretation, and communication. I am particularly interested in hospital quality, clinical data, interoperability, public health data, and decision-support analytics.

02 · Capabilities

Core skills

A clinical + analytical toolkit for healthcare data work.

01

Healthcare Analytics

Clinical data analysis, hospital quality, readmissions, public health data, data quality and clinical interpretation.

02

Data & Statistics

Python, Pandas, NumPy, SQL, exploratory analysis, hypothesis testing, effect sizes and multiple-testing correction.

03

Visualization & BI

Power BI, Matplotlib, Seaborn, KPI design, dashboards and decision-oriented communication.

04

Health Informatics & ML

FHIR, HL7 v2, ICD-10-CM, LOINC, UCUM, Scikit-learn, classification and model evaluation.

PythonSQLPower BIPandasScikit-learnFHIRHL7 v2ICD-10-CMLOINCGitHub Actions

03 · Selected Work

Healthcare data portfolio

Projects selected for analytical rigor, clinical context, reproducibility, and transparent limitations.

03Informatics

FHIR · HL7 · Clinical Terminologies

FHIR Clinical Data Pipeline

A fully synthetic interoperability portfolio demonstrating Patient, Condition, Observation, MedicationRequest, Encounter and Bundle resources, plus HL7 v2 mapping and terminology use with ICD-10-CM, LOINC and UCUM.

FHIRHL7 v2LOINCUCUM
View repository ↗
04Analytics

Clinical Data Quality · Statistics

Diabetes Medical Data Analysis

Reproducible data cleaning, EDA, statistical testing, effect-size analysis and multiple-testing correction. Dataset provenance uncertainty is explicitly documented as a data-governance limitation rather than assumed.

PandasSciPyStatisticsGitHub Actions
View repository ↗
05Artifact Audit

Responsible Healthcare AI · Governance

Stroke Prediction Model — Artifact Audit

A transparent audit of published model artifacts. Integrity checks are reproducible, while performance claims are intentionally withheld because the original training dataset and complete training workflow are not available in the repository.

JoblibValidationModel CardGovernance
View repository ↗

04 · Working Principles

Responsible healthcare analytics

Performance numbers are only useful when the evidence behind them is clear.

01

Clinical Question First

Define the healthcare question, population, outcome and unit of analysis before choosing methods.

02

Data Quality

Document missingness, provenance, implausible values, coding assumptions and analytical limitations.

03

Reproducibility

Use documented workflows, version control, automated checks and transparent decision trails.

04

Clinical Governance

Predictive models require validation, calibration, subgroup assessment and governance before real-world clinical use.

05 · Career Direction

Open to healthcare data opportunities.

Focused on the UAE, Gulf region, remote and international healthcare organizations.

Healthcare Data AnalystClinical Data AnalystHealth InformaticsPublic Health DataHealthcare BI AnalystClinical Analytics

06 · Contact

Healthcare data, clinical analytics, informatics, or responsible AI.