Neuro
AI Detect
Innovative Strategies in Epilepsy Detection Using AI Revolutionizing
Discover AI possibilities
About us
According to World Health Organization more than 50 million individuals around the world in 2023 are suffering from epilepsy. With the increasing availability of EEG studies, the number of diagnosed patients with epilepsy will increase several times.

EEG, non-invasive and safe, is the preferred method for diagnosing epilepsy and differentiating it from similar conditions like cognitive or behavioral disorders.
NeuroAI Detect leverages AI to streamline EEG analysis, reducing time and costs, with the goal of improving global access to epilepsy diagnostics."
Main challeges
Prompt identification of seizures before they occur is crucial. It can enable patients to take early action to prevent serious accidents and injuries, yet remains a challenge.
Doctors must review full EEGs, a lengthy process that increases the cost and limits access to diagnostics.
Time-Intensive Analysis:
Routine EEGs cost between $200-$700, putting a financial strain on patients.
High Costs:
Predictal Stage Detection:
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Our Solution
NeuroAI Detect - the innovative system based on Artificial Intelligence for early epilepsy detection through extensive automated EEG analysis. Deep learning algorithms analyzes EEG signals, identifying patterns associated with epileptic, improve accuracy, reducing diagnositics time and costs.
Main focus
Generally AI research includes predicting seizure onset, identifying photoparoxysmal responses, classifying EEG components, and synthesizing conclusions from full EEG records.
Clinically, pinpointing the 'spike-and-wave' complex is vital. This key EEG feature occurs during and between seizures, serving as a definitive marker of epilepsy."
Time-Intensive Analysis:
Predictal Stage Detection:
How it works?
1. Pattern Identification: Our AI system identifies the key pathological EEG pattern, the spike-and-wave complex, which signifies an epileptic seizure when repeated at high amplitude.

2. Interictal Analysis: For interictal EEGs, the AI recognizes single, local spike-and-wave patterns. In children aged 4-14, these may indicate a risk of developing epilepsy or developmental disorders like BFEDC.

3. AI Assistance: The artificial intelligence highlights all detected patterns, streamlining the diagnostic process by presenting only pertinent data to the physician.

4. Efficiency Boost: This method reduces the doctor's EEG review time from hours to minutes, accelerating analysis by a factor of 10-20."
Strategic Partnerships
Engage in partnerships with EEG manufacturers to enhance device compatibility and functionality.
Work closely with epilepsy clinics and research facilities to refine our algorithms and validate technology.
Clinical Alliances
Collaborate with governmental health agencies to expand reach and support public health initiatives.
Public Sector Engagement
Industry Collaborations
Licensing Policy
Providing licenses to medical institutions and companies.
For healthcare providers and institutions
Clinical Alliances
Subscription model for access to the cloud platform and updates.
Public Sector Engagement
Industry Collaborations
Our approach
Mimicking human-like observation, our system employs computer vision to detect subtle trends and minute fluctuations in EEG data that may elude doctors.
Computer Vision
The Time Series Transformer and YOLOv5 Classification algorithms synergize to process long time series data, extract features, and pinpoint anomalies in EEG patterns.
Innovative Integration
Leveraging YOLOv5's precision and the 'Attention' mechanism of Time Series Transformers, our system accurately locates and highlights pathological EEG segments.
Precision Identification
Enhanced efficiency in data analysis is achieved through smooth integration with cloud computing platforms.
Cloud Compatibility
Key advantages
Enables detection of epilepsy at initial stages, significantly improving treatment outcomes.
Through continuous data expansion and advanced machine learning techniques, our algorithms aim to exceed manual diagnostic accuracy, targeting a 99.9% success rate.
Data-Driven Accuracy
By cutting down EEG analysis time and costs, we enhance the accessibility of epilepsy diagnostics for a broader patient base
Efficiency and Accessibility
Early Diagnosis
Collaboration and Technology Advancement Opportunities:
Seeking partnerships with top clinics to enrich our machine learning algorithm with annotated data.
Offering our AI platform at no cost for clinical trials to enhance research and development.
Complimentary AI Platform
Welcoming joint ventures to broaden the application of AI technologies in diagnosing a variety of diseases."
Open Collaboration
Clinical Data Partnership:
Our team
  • Vladimir Roitblat
    CEO
    25 years experience in high-tech companies. Implemented projects in healthcare, energy efficiency, education and artificial intelligence at the national and international levels

  • Daniel de Liever
    Policy consultant
    Experience in clinical psychology, digital health solutions, research and entrepreneurship. Implementation of healthcare & social domain policy
  • Bekhruz Azam
    ML Engeneer
    ML engeneer experience at Yandex, Nebius, Huawai
Contact us
+1 123 4567890
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Pineapple Loft, 22 Pink Street,
New York