You will get a patient readmission prediction model
Project details
The Problem
Unplanned hospital readmissions drain resources, cause heavy penalties, and signal preventable gaps in patient care. The warning signs are hidden deep within your raw EHR data, but traditional tools only track data after a patient returns. By then, it’s too late.
The Solution
I build production-ready readmission prediction models that analyze patient data before discharge. Using machine learning, the system flags high-risk individuals in real time, giving clinical teams a clear window to intervene and implement targeted transitional care.
Why My Work is Different
Kaggle Grandmaster Expertise: Built by a top 1% global data scientist specialized in maximizing machine learning performance (XGBoost) on complex, real-world datasets. No generic templates.
Explainable AI (SHAP): Black-box models fail in healthcare. I integrate SHAP values so clinicians can see the exact, transparent risk drivers behind every single prediction.
HIPAA-Aware & Agile: Engineered with strict privacy guardrails and sharp clinical utility, delivering a validated, deployment-ready model structure in just 5–7 days.
Unplanned hospital readmissions drain resources, cause heavy penalties, and signal preventable gaps in patient care. The warning signs are hidden deep within your raw EHR data, but traditional tools only track data after a patient returns. By then, it’s too late.
The Solution
I build production-ready readmission prediction models that analyze patient data before discharge. Using machine learning, the system flags high-risk individuals in real time, giving clinical teams a clear window to intervene and implement targeted transitional care.
Why My Work is Different
Kaggle Grandmaster Expertise: Built by a top 1% global data scientist specialized in maximizing machine learning performance (XGBoost) on complex, real-world datasets. No generic templates.
Explainable AI (SHAP): Black-box models fail in healthcare. I integrate SHAP values so clinicians can see the exact, transparent risk drivers behind every single prediction.
HIPAA-Aware & Agile: Engineered with strict privacy guardrails and sharp clinical utility, delivering a validated, deployment-ready model structure in just 5–7 days.
AI Development Type
Deep Learning, Knowledge Representation, Model Tuning, Recommendation System, Software MaintenanceAI Tools
Azure Machine Learning, Chainer, deeplearn.js, Google AutoML, MATLAB, MLflow, NVIDIA AI Platform, OpenCV, PyTorch, TensorFlowAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$149
|
Standard
$349
|
Advanced
$649
|
|---|---|---|---|
| Delivery Time | 5 days | 6 days | 7 days |
Number of Revisions | 3 | 5 | 9 |
AI Model Integration | |||
Detailed Code Comments | - | ||
Knowledge Graph | - | ||
Model Documentation | |||
Ontology | - | - | |
Source Code | |||
Taxonomy | - | - | - |
Frequently asked questions
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PD
Paula D.
Oct 1, 2025
Meditation/visualization Experiment Participant
About Nudrat
Healthcare Data Analyst | EHR Integration & Power BI Automation
Lahore, Pakistan - 10:33 am local time
What I do:
✔ Connect and clean EHR, billing, and operational data into one reliable dataset
✔ Build automated pipelines so reports update themselves, not manually
✔ Design Power BI dashboards for patient flow, readmissions, denials, and revenue
✔ Build predictive models for patient retention and readmission risk
✔ Handle all of this with HIPAA aware data practices
About me:
I'm a Computer Science student and Kaggle Datasets Grandmaster, ranked number ranked 18 of over 10,100+ contributors globally, top 0.2% worldwide. I focus specifically on healthcare data because most analysts know Python, but very few understand how clinics actually operate or what HIPAA means for a data pipeline.
I'm newer to Upwork, which means you get personalized attention and competitive rates while I build my track record here, not a junior who's guessing. My published Kaggle work and certifications below back that up.
Tech stack: Python, SQL, Power BI, Power Query, DAX, Power Automate, XGBoost, Scikit Learn, Streamlit, ETL pipelines, HIPAA compliant workflows
If you have healthcare data that isn't working for you yet, message me. I'll tell you honestly what's possible with it.
Steps for completing your project
After purchasing the project, send requirements so Nudrat can start the project.
Delivery time starts when Nudrat receives requirements from you.
Nudrat works on your project following the steps below.
Revisions may occur after the delivery date.
Clinical Data Alignment & Baseline Modeling
We map out your EHR/patient data fields to identify key readmission risk drivers (e.g., demographics, comorbidities, prior visits).
Advanced Feature Engineering & Optimization
Using XGBoost, I engineer advanced predictive features to capture complex patient risk patterns. I fine-tune the model for high precision to minimize false positives, ensuring your clinical team targets the right high-risk patients.