Memora

About Memora Project

An advanced artificial intelligence system aimed at improving patient outcomes through early detection and risk assessment of Alzheimer's disease

Current Challenges

Alzheimer's disease represents one of the most significant healthcare challenges globally, with millions affected. Early detection and intervention can significantly improve quality of life and treatment outcomes.

Late Diagnosis Challenges

Most cases are diagnosed at advanced stages when treatment options are limited

Complex Cognitive Assessment

Difficulty in processing multiple risk factors and cognitive indicators effectively

Need for Early Intervention

Critical need for timely identification to enable early treatment and care planning

Memora's Innovative Solution

Memora analyzes neurological reports and cognitive health data using artificial intelligence to provide advanced and accurate Alzheimer's risk assessment:

1

Comprehensive Neurological Analysis

Advanced processing of neurological reports, cognitive assessments, and 34 risk factors using machine learning algorithms

2

Early Risk Detection

XGBoost-powered analysis with 94% accuracy providing color-coded risk levels and clear cognitive status interpretation

3

Clinical Action Plans

Evidence-based recommendations for neurological assessment, monitoring, and early intervention strategies

System Features

The Memora system features a set of advanced characteristics that make it the optimal solution for cognitive health and Alzheimer's risk assessment

High Accuracy

Advanced artificial intelligence models achieving high accuracy in health risk prediction

Advanced Algorithms

Precise Data Analysis

Easy to Use

Simple and clear interface designed specifically for medical staff and healthcare practitioners

Intuitive Design

Quick Training

Full Integration

Fully integrable with existing hospital systems and medical records

Seamless Connection

Comprehensive Compatibility

Our Team

Our team consists of two AI Engineers and Master's students in Artificial Intelligence at King Fahd University of Petroleum and Minerals (KFUPM). We specialize in building predictive models and developing AI solutions.

Reema AlQuwaie

AI Master's Student

Raghad Bayones

AI Master's Student

Demo

Try the Memora system yourself - two ways to interact with and test the system

Upload Medical Reports

Upload a medical report image to get intelligent risk analysis

Sample Reports for Testing

Negative Case (Normal) Positive Case (Risk Detected)

Upload Your Medical Report

Drag the report file here or click to choose
Supported formats: PNG, JPG, JPEG - Max size: 10 MB

Analyzing medical report...

Analysis Results

Age

Blood Pressure

Memory Score

BMI

Diagnosis Result

confidence

Age

Gender

Family History

MMSE Score

Memory Complaints

Confusion

Forgetfulness

Blood Pressure

Medical Report

Conversation with Cognitive Health Assistant

Ask any question about the cognitive assessment

Or try one of the suggested questions:

The system can be easily integrated with any other system

Use the Application Programming Interface (API) for seamless integration with your existing systems

Description:

Get cognitive health and Alzheimer's risk predictions using the extracted patient data

Request Example:

curl -X GET "https://api.memora.health/api/predict" \
  -H "Accept: application/json"

Response Example:

{
"prediction": {
    "value": 0,
    "label": "No Alzheimer's Disease",
    "confidence": 0.9944846630096436
},
"probabilities": {
    "no_alzheimers": 0.9944846630096436,
    "alzheimers": 0.005515359342098236,
    "risk_level": "Very Low"
},
"data_quality": {
    "all_features_present": true,
    "feature_count": 34,
    "preprocessing_applied": true
}
}

Open Swagger UI Open ReDoc

Security & Privacy

Protecting Patient Data

We invest in advanced technologies to protect patient privacy by automatically redacting and encrypting all personal and sensitive data

Before Encryption

Exposed Data

Patient Medical Record

Basic Patient Information:

Full Name: أحمد محمد عبد الرحمن السيد

National ID Number: ١٢٣٤٥٦٧٨٩٠١٢٣

Date of Birth: ١٥/٠٣/١٩٨٥

Address: شارع الملك فهد رقم ٤٥، حي النخيل، الرياض ١١٤٣٣

Phone Number: +٩٦٦ ٥٥ ١٢٣٤ ٥٦٧٨

Email Address: ahmed.alsayed@example.com

Insurance Information:

Insurance Company: شركة التعاونية للتأمين الصحي

Policy Number: POL-456789123

Current Diagnosis:

Patient diagnosed with Type 2 Diabetes (ICD-10: E11.9)

Blood Pressure المرتفع (ICD-10: I10)

Current Medications:

١. ميتفورمين ٥٠٠ ملغ - مرتين يومياً

٢. جليميبيرايد ٢ ملغ - مرة واحدة صباحاً

٣. ليزينوبريل ١٠ ملغ - مرة واحدة مساءً

ملاحظات الطبيب المعالج:

د. فاطمة علي الحسن - أخصائية الغدد الصماء

معلومات الاتصال في حالات الطوارئ:

الاسم: مريم عبد الله السيد (الزوجة)

Phone Number: +٩٦٦ ٥٠ ٩٨٧٦ ٥٤٣٢

رقم الحساب البنكي: SA١٢٣٤٥٦٧٨٩٠١٢٣٤٥٦٧٨٩٠

البنك: البنك الأهلي السعودي

توقيع المريض: أحمد السيد

After Encryption

Protected Data