HEALTHCARE.AI
AI-Powered Diagnostic System
Created on 13th August 2023
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HEALTHCARE.AI
AI-Powered Diagnostic System
The problem HEALTHCARE.AI solves
Problem Statement
The Diagnostic Dilemma in Healthcare
● Challenge: Current medical diagnostic processes suffer from a substantial error rate, leading to misdiagnoses
and suboptimal patient outcomes.
● Stats: According to a study by Johns Hopkins Medicine1, diagnostic errors contribute to around 10% of patient
deaths in the U.S. annually.
The Time Factor: Delays in Diagnosis
● Challenge: Traditional diagnostic methods are time-consuming, causing delays in initiating crucial treatments.
● Stats: The National Academy of Medicine2 highlights that it takes an average of 17 years for a medical discovery
to be fully integrated into clinical practice.
Inaccurate Diagnoses: Hidden Costs
● Challenge: Misdiagnoses result in prolonged treatments, increased healthcare expenses, and avoidable
hospitalizations.
● Stats: A report by BMJ Quality & Safety3 estimates that diagnostic errors cost the U.S. healthcare system over
$700 billion annually
Challenges we ran into
Dependencies installation during deployment, silly errors while backend integration using flask
Ensuring the dataset is accurate: The dataset might contain errors or inconsistencies that need to be identified and corrected.
Handling missing values: Dealing with missing data requires decisions on imputation or removal, which can affect the model's performance.
Tracks Applied (5)
Most Creative Use of GitHub
Major League Hacking
Best Use of Streamlit
Major League Hacking