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AI in Healthcare

Humanizing the Future with AI

Imagine a healthcare journey where AI acts as a supportive partner, enhancing the capabilities of healthcare professionals and providing personalized insights for patients. We’re not just advancing medical technology; we’re humanizing healthcare. We believe in a future where healthcare is not just about diagnoses and treatments but about genuine human connection. Our AI-powered solutions are designed to seamlessly integrate with the warmth and compassion of human care, creating an experience that is not only technologically advanced but deeply personal.
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our services

Advanced & powerful services

Group 8899 (4)
Diagnostic AI Solutions

We implement AI algorithms for accurate and efficient medical diagnostics.
We provide image recognition and analysis for radiology and pathology images.
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Group 8899 (5)
Telehealth Integration

We implement AI features for virtual consultations, symptom analysis, and medication management.
Enhance the overall telehealth experience for patients and healthcare providers.
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Group 8899 (6)
Remote Patient Monitoring

Implement AI solutions for continuous remote monitoring of patients.
Utilize wearables and IoT devices to collect and analyze health data.
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Group 8899 (7)
Clinical Decision Support Systems

Design AI-powered tools to assist healthcare professionals in making informed clinical decisions.
Integrate real-time data to enhance decision-making during patient care.
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A Better Healthcare

Inspiring Health and Hope Through the Power of AI

Our mission is to bridge the gap between cutting-edge AI and compassionate care, ensuring that every individual receives the attention and understanding they deserve. Through innovative solutions, we are paving the way for a healthcare landscape where technology empowers, but humanity prevails. Join us in embracing a new era of healthcare – one that combines the precision of artificial intelligence with the empathy that defines human touch. At Predict Vision, we are shaping a future where health is not just a science, but a deeply caring and interconnected experience.”
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Our Process

how we work

Throughout our process, collaboration with healthcare professionals, data scientists, and IT specialists is crucial to ensure our AI system meets the needs of the healthcare industry while adhering to ethical and regulatory standards.

01

Objectives and Scope
  • Outline the goals of the AI system.
  • Identify specific healthcare tasks or problems it will address.
  • Scope definition, considering the target audience and healthcare domains.

02

Data Collection and Preparation
  • Gather relevant and high-quality healthcare data.
  • Ensure data privacy and compliance with regulations.
  • Clean, preprocess, and structure the data for training.

03

Algorithm Selection
  • Choose the right machine learning or deep learning algorithms.
  • We consider the complexity of the healthcare task and available data.

04

Model Training
  • Train the chosen model using the prepared healthcare data.
  • Implement validation techniques to ensure robustness.
  • Fine-tune parameters to optimize performance.

05

Validation and Evaluation
  • Validate the model using separate datasets.
  • Evaluate performance metrics, considering accuracy, sensitivity, specificity, etc.
  • Iteratively refine the model based on results.

06

Interpretability and Explainability
  • Ensure the AI model’s decisions are interpretable.
  • Provide explanations for its predictions to gain trust from healthcare professionals.

07

Integration with Healthcare Systems
  • Integrate the AI system into existing healthcare infrastructure.
  • Collaborate with IT teams to ensure compatibility and security.

08

Regulatory Compliance
  • Adhere to healthcare regulations and standards.
  • Prepare necessary documentation for compliance.

09

User Interface and Experience
  • Design an intuitive and user-friendly interface for healthcare professionals.
  • Ensure seamless integration into the workflow.

10

Testing and Quality Assurance
  • Conduct rigorous testing to identify and fix potential issues.
  • Implement quality assurance measures to guarantee reliability.

11

Deployment
  • Gradually deploy the AI system in real healthcare settings.
  • Monitor performance in real-world scenarios and gather feedback.

12

Continuous Improvement
  • Implement mechanisms for continuous learning and improvement.
  • Regularly update the model based on new data and feedback.
team members

Meet Our Team

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Rene B.Cruz

business analysis
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Lili Albert

creative expert
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Kushi Agrawal

Business Analysis
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Tom B. Cruz

Career Analysis
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Mark Harui

Product Manager
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Adisa Gouse

Web Developer
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Thomson John

Marketing Manager
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Erika Petit

Devoleper
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Bela Alexander

designation
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