Udemy - AI in Decentralized Observational Clinical Trial

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Udemy - AI in Decentralized Observational Clinical Trial (Size: 315 MB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
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  1 - Introduction
  1. Introduction to Decentralised observational Clinical trials (DCTs) (Description).html 3.1 KB
  1. Introduction to Decentralised observational Clinical trials (DCTs).en_US.srt 2 KB
  1. Introduction to Decentralised observational Clinical trials (DCTs).mp4 18.3 MB
  10 - AI in Decentralised trial logistics, Regulatory compliance and data privacy
  11 - AI in virtual clinical trial platform, adaptive trial design & Real time data
  12 - AI for outcome measures, literature review and biomarker discovery
  2 - Clinical Trial types and Decentralised clinical trial
  3 - Types ,Key features, advantages and limitation of Observational clinical trial
  4 - Ethical consideration, Applications and Future of observational clinical trial
  10. Ethical consideration (Description).html 4.1 KB
  10. Ethical consideration.en_US.srt 1 KB
  10. Ethical consideration.mp4 3.3 MB
  11. Applications of observational clinical trial (Description).html 4.6 KB
  11. Applications of observational clinical trial.en_US.srt 1.4 KB
  11. Applications of observational clinical trial.mp4 24.6 MB
  12. Future of observational clinical trial (Description).html 5.8 KB
  12. Future of observational clinical trial.en_US.srt 3.7 KB
  12. Future of observational clinical trial.mp4 15 MB
  5 - AI in Decentralised observatioal clinical trial and patient recruitment
  13. Artificial Intelligence in Decentralised Observational Clinical Tria (Description).html 5.5 KB
  13. Artificial Intelligence in Decentralised Observational Clinical Tria.en_US.srt 2.7 KB
  13. Artificial Intelligence in Decentralised Observational Clinical Tria.mp4 10.1 MB
  14. AI powered patient recruitment and screening (Description).html 8.8 KB
  14. AI powered patient recruitment and screening.en_US.srt 2.5 KB
  14. AI powered patient recruitment and screening.mp4 10.5 MB
  6 - Remote Data collection and Data analysis
  15. Remote Data collection and wearable devices (Description).html 4.2 KB
  15. Remote Data collection and wearable devices.en_US.srt 2.3 KB
  15. Remote Data collection and wearable devices.mp4 8.9 MB
  16. AI-Driven data analysis and pattern recognition (Description).html 4.1 KB
  16. AI-Driven data analysis and pattern recognition.en_US.srt 2.8 KB
  16. AI-Driven data analysis and pattern recognition.mp4 16.5 MB
  7 - AI for patient communication and protocol adherence and monitoring
  17. Natural Language processing for patient communication (Description).html 4 KB
  17. Natural Language processing for patient communication.en_US.srt 2 KB
  17. Natural Language processing for patient communication.mp4 34.1 MB
  18. AI for protocol adherence and monitoring.en_US.srt 4.6 KB
  18. AI for protocol adherence and monitoring.mp4 19.5 MB
  8 - AI in virtual site monitoring and predictive modelling
  19. AI in virtual site monitoring and quality control (Description).html 3.7 KB
  19. AI in virtual site monitoring and quality control.en_US.srt 2.7 KB
  19. AI in virtual site monitoring and quality control.mp4 11.8 MB
  20. AI-Driven predictive modelling for patient outcome (Description).html 4.4 KB
  20. AI-Driven predictive modelling for patient outcome.en_US.srt 2 KB
  20. AI-Driven predictive modelling for patient outcome.mp4 8.9 MB
  9 - AI for real world evidence generation and patient engagement
  21. AI for Real world evidence generation (Description).html 3.6 KB
  21. AI for Real world evidence generation.en_US.srt 1.8 KB
  21. AI for Real world evidence generation.mp4 8.4 MB
  22. AI Enabled patient engagement and retention strategies (Description).html 4 KB
  22. AI Enabled patient engagement and retention strategies.en_US.srt 1.4 KB
  22. AI Enabled patient engagement and retention strategies.mp4 6.2 MB
  6. Types of Observational clinical trial (Description).html 4.2 KB
  6. Types of Observational clinical trial.en_US.srt 4.2 KB
  6. Types of Observational clinical trial.mp4 13.1 MB
  7. Key features of observation clinical trials (Description).html 3.7 KB
  7. Key features of observation clinical trials.en_US.srt 1.4 KB
  7. Key features of observation clinical trials.mp4 4 MB
  8. Advantages of Observational clinical trial (Description).html 3.3 KB
  8. Advantages of Observational clinical trial.en_US.srt 1.2 KB
  8. Advantages of Observational clinical trial.mp4 5.2 MB
  9. Limitations of observational clinical trial (Description).html 3.8 KB
  9. Limitations of observational clinical trial.en_US.srt 819.2 B
  9. Limitations of observational clinical trial.mp4 3.4 MB
  3. Types of clinical trial (Description).html 3 KB
  3. Types of clinical trial.en_US.srt 2.7 KB
  3. Types of clinical trial.mp4 11.6 MB
  4. What is Decentralised Clinical trial (Description).html 3.6 KB
  4. What is Decentralised Clinical trial.en_US.srt 1.6 KB
  4. What is Decentralised Clinical trial.mp4 5.6 MB
  5. Enhanced patient recruitment and participation (Description).html 5 KB
  5. Enhanced patient recruitment and participation.en_US.srt 1.6 KB
  5. Enhanced patient recruitment and participation.mp4 6.2 MB
  29. AI in Patient reported outcome measures.en_US.srt 1.9 KB
  29. AI in Patient reported outcome measures.mp4 9 MB
  30. AI for automated literature review and evidence synthesis.en_US.srt 614.4 B
  30. AI for automated literature review and evidence synthesis.mp4 2.7 MB
  31. AI in Biomarker discovery and validation.en_US.srt 2 KB
  31. AI in Biomarker discovery and validation.mp4 8.7 MB
  26. AI in virtual clinical trial platform (Description).html 4.7 KB
  26. AI in virtual clinical trial platform.en_US.srt 1.2 KB
  26. AI in virtual clinical trial platform.mp4 5.6 MB
  27. AI for adaptive trial design for observational studies.en_US.srt 1.5 KB
  27. AI for adaptive trial design for observational studies.mp4 6.8 MB
  28. AI enabled real time data quality monitoring (Description).html 6.2 KB
  28. AI enabled real time data quality monitoring.en_US.srt 921.6 B
  28. AI enabled real time data quality monitoring.mp4 5.6 MB
  23. AI in decentralised trial logistics and supply chain management.en_US.srt 2.3 KB
  23. AI in decentralised trial logistics and supply chain management.mp4 10.1 MB
  24. AI for regulatory compliance and Reporting (Description).html 4.5 KB
  24. AI for regulatory compliance and Reporting.en_US.srt 1.4 KB
  24. AI for regulatory compliance and Reporting.mp4 6.7 MB
  25. AI powered data Privacy and security measures (Description).html 4.7 KB
  25. AI powered data Privacy and security measures.en_US.srt 1.6 KB
  25. AI powered data Privacy and security measures.mp4 7.7 MB
  2. Course overview.en_US.srt 2.1 KB
  2. Course overview.mp4 7 MB

Description


AI in Decentralized Observational Clinical Trial

https://WebToolTip.com

Last updated 12/2024
Created by Dr Pravin Badhe
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English + subtitle | Duration: 31 Lectures ( 53m ) | Size: 315 MB

AI in clinical trials, Virtual clinical trial, observational clinical trial, Recent advances in clinical trial

What you'll learn
✓ Foundations of Decentralized Clinical Trials (DCTs)
✓ AI-Powered Patient Recruitment and Screening: Discover how AI revolutionizes patient engagement and participation.
✓ Wearable Technology and Remote Data Collection: Learn how AI integrates data from wearable devices for real-time monitoring.
✓ Predictive Modeling and Pattern Recognition: Explore AI-driven analytics for patient outcomes and data-driven insights.
✓ Ethical and Regulatory Considerations: Dive into privacy, compliance, and the ethical challenges in AI-enabled trials.
✓ Advanced AI Applications: Study case studies of AI in adaptive trial design, biomarker discovery, and automated literature reviews.

Requirements
● Undergraduate or postgraduate students in life sciences, biotechnology, computer science, or related fields seeking to understand AI's application in healthcare.
● Clinical researchers, trial managers, and healthcare providers interested in modernizing trial methodologies.
● Data scientists and AI developers aiming to apply their skills in the healthcare domain.
● Professors and instructors seeking to integrate cutting-edge technology into their teaching.
● Biotech and pharmaceutical professionals exploring AI's potential in decentralized clinical trials.

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