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Case Study

AI Cancer Care System— Healthcare Platform

An AI-powered platform designed to assist medical professionals in generating personalized cancer treatment plans.

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AI Cancer Care System
Industry

Healthcare

Project Type

AI Decision Support

Timeline

4 months

Role

Full-Stack Developer

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Project Overview

Overview

The AI Cancer Care System is a healthcare platform built to help medical professionals solve the challenge of creating personalized treatment plans for cancer patients using AI-driven analysis. The goal was to create a decision-support tool that is accurate, secure, and clinically relevant.

Category

AI SystemsWeb Apps

Type

Healthcare Platform

Tech Stack

ReactTypeScriptTailwind CSSNode.jsAI APIsMedical Data APIs
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Problem & Solution

The Problem

The Problem

Before this system, oncology teams faced significant challenges in creating individualized treatment plans efficiently.

Treatment planning relied heavily on manual review of extensive patient histories
Inconsistent recommendations due to varying levels of specialist availability
Lack of a centralized system for tracking patient data and treatment outcomes

Impact — These challenges resulted in slower decision-making, increased workload for medical staff, and suboptimal patient outcomes.

The Solution

The Solution

To address these challenges, I designed and built an AI-powered healthcare platform that focuses on:

AI-generated personalized treatment plan recommendations based on patient data
Secure and compliant patient data management system
Integration with external medical APIs for up-to-date clinical information

The system was structured to ensure performance, scalability, and ease of use.

Key Features

Key Features

01

Patient Data Management

Secure intake and storage of patient medical histories and profiles

02

AI Treatment Plans

AI-generated, personalized cancer treatment recommendations

03

Secure Data Handling

Encrypted data storage and access controls for patient privacy

04

API Integrations

Connected to external medical data sources for clinical accuracy

Tech Stack

Technologies Used

Frontend

ReactTypeScriptTailwind CSS

Backend

Node.js

Integrations

AI APIsMedical Data APIs

Results & Impact

Results & Impact

The system delivered measurable improvements across key areas.

Enhanced clinical decision-making with AI-backed recommendations
Reduced time required to generate initial treatment plan drafts
Improved consistency in treatment planning across cases
Streamlined patient data management in a single secure platform

Challenges

Challenges & How I Solved Them

ChallengeEnsuring data privacy and security for sensitive patient records

SolutionImplemented encryption at rest, strict access controls, and secure API communication protocols

ChallengeMaintaining AI output reliability for clinical use cases

SolutionAdded validation layers and clear UI indicators to ensure recommendations are used as support tools, not final decisions

Key Insights

Key Insights

This project reinforced important principles that shape how I approach every build.

01

Security and compliance must be designed into the architecture from day one — not bolted on later

02

AI in healthcare must be positioned as decision support, not decision replacement

03

Clear data models and access control structures are foundational for sensitive applications

Visual Showcase

Interface & Screens

AI Cancer Care System — Treatment Overview — Desktop
Treatment Overview — Desktop
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