ADANA TECHNOLOGIES
Healthcare AI Services
Advancing healthcare through AI, our innovative solutions are designed to meet the complex needs of providers, payers, and patient advocacy groups. We enable a more connected, efficient, and patient-centered healthcare system by integrating cutting-edge technologies such as Gen AI, Large Language Models (LLMs), and intelligent agents. Our AI services enhance diagnostic precision, tailor treatments to individual patient needs, and streamline clinical and administrative processes. From automating intricate data analysis to facilitating seamless communication across the healthcare spectrum, our tools empower healthcare stakeholders to improve outcomes, reduce operational burdens, and advocate more effectively for patient needs.
Compliance and Regulatory Challenges
Our AI Solution:
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- Automated Reporting: We build automated compliance reports using data analytics to ensure accurate, real-time submissions to regulators.
- Data Security Protocols: We implement encryption and multi-factor authentication, which are essential to protect sensitive customer data and comply with data protection laws like GDPR.
- Policy Updates: We track regulatory changes through alerts and update policies accordingly, keeping compliance strategies dynamic and current.
Risk Management
Our AI Solution:
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- Credit Scoring Models: We use Gen AI to more accurately assess borrower risk by considering a wide range of non-traditional data points, including online behavior and transaction history.
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- Predictive Risk Analytics: We implement predictive analytics to foresee market changes and potential risks, allowing for proactive risk management strategies.
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- Operational Risk Management: We deploy Gen AI models to monitor and analyze internal processes and transactions in real-time, identifying operational risks before they lead to financial losses or reputational damage.
Operational Efficiency
Our AI Solution:
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- Process Automation: We apply AI to automate routine banking operations such as account reconciliation, credit checks, and customer onboarding.
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- Optimized Resource Allocation: We use AI to optimize the allocation of human and capital resources, enhancing overall operational efficiency.
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- Intelligent Document Processing (IDP): We implement Gen AI models to automate the processing of complex documents like loan applications, KYC forms, and legal paperwork.
Fraud Detection and Prevention
Our AI Solution:
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- Machine Learning Models: We use ML algorithms to analyze transaction patterns and detect unusual or high-risk behavior indicative of fraud.
- Real-Time Alerts: We set up real-time alerts for suspicious transactions to enable rapid responses.
- User Authentication: We implement biometric verification and behavioral analytics to enhance identity authentication.
Customer Experience and Personalization
Our AI Solution:
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- Personalized Financial Advice: We employ AI to analyze individual customer data and provide personalized financial advice and product recommendations.
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- Chatbots and Virtual Assistants: We use Gen AI-driven chatbots to provide 24/7 customer service, handling inquiries and transactions with ease.
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- Dynamic Pricing Models: We utilize Gen AI to dynamically adjust pricing and service offerings based on customer behavior, market conditions, and individual financial profiles.
Data Security and Privacy
Our AI Solution:
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- Differential Privacy: We implement differential privacy techniques in AI algorithms to ensure that the data used for training AI systems cannot be reverse-engineered to compromise individual privacy.
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- Advanced Biometrics: We employ AI-powered biometric authentication methods, such as facial recognition, voice recognition, and fingerprint scanning, to provide robust security measures that are difficult to breach.
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- Anomaly Detection Systems: We implement Gen AI models to continuously monitor network traffic and user activities, quickly identifying and responding to unusual patterns that could indicate a security breach.
Our Use Case
Telemedicine, voice-to-text, mapping to dictionaries
01
Data Collection and Preprocessing
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Data Preprocessing: We apply audio processing techniques like noise reduction, spectral filtering, and echo cancellation to enhance clarity and ensure accurate transcription.
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LLM Entity Extraction and Classification
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LLM Training/Integration: We deploy pre-trained or fine-tuned large language models capable of extracting key entities like symptoms, test procedures, medications, and diagnoses from the transcriptions.
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We highlight extracted entities with color-coded labels for easy visual identification.
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PII Identification: We integrate an additional layer of entity recognition to detect and flag PII for privacy compliance.
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Quality Assurance and Continuous Improvement
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Testing and Validation: We validate the entity extraction and mapping process against known ground truth datasets, and ensure compliance with privacy standards.
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Feedback Loop and Optimization: We regularly gather user feedback to refine and optimize extraction, mapping, and the final PDF generation.
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We finally ensure a seamless workflow for doctors and staff.
02
Voice-to-Text and Transcription Implementation
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ASR Model Selection and Fine-Tuning: We choose an Automatic Speech Recognition (ASR) model with a solid medical vocabulary. Fine-tune it with curated audio data to better handle telemedicine-specific terminologies and nuances.
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PDF Creation and Formatting: We automate the conversion of transcriptions into well-formatted, standardized PDF documents. Include time-stamped sections and speaker differentiation for readability.
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Medical Entity Mapping to Standard Dictionaries
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Mapping Algorithms: We develop mapping algorithms that align recognized medical entities with standardized classifications like MEDDRA, RxNorm, ICD, and SNOMED.
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We use a hybrid approach, combining machine learning with rule-based systems for precise matching.
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Verification and Normalization: We verify mappings against known standards to maintain consistency.
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Integration with EMR and Scalability
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EMR Integration: We will implement an API or interface for seamless data transfer from the generated PDF into the Electronic Medical Record (EMR) system (Cerner or Epic), maintaining security and data integrity.