Jindal Healthcare’s Post

AI's impact for bad or good | Healthcare Finance NewsArtificial intelligence makes efficient use of a massive amount of data, but it can also create deep fake technology, says Dr. Benoit Desjardins, ...https://lnkd.in/eg-TpzKu

AI is helping to streamline workforce challenges

AI's impact for bad or good

AI is moving from concept to solving real world problems

Workers' comp professionals no longer have to spend hours manually searching multiple sources of data, to find the right treatment for injured workers. Claim Clarity automates the process with AI, guiding users to a single source of all state and evidence-based guidelines, updated in real time - saving hours in #claimsmanagement for better business and medical outcomes. #workerscompensationclaims #utilizationmanagement

Lifecycle management provides an effective approach toward delivering safe, effective AI-enabled Health Care. FDA welcomes your feedback on our latest blog addressing this topic. https://lnkd.in/d2cpH2aM

Check out the latest blog post from CDRH’s Digital Health Center of Excellence on the potential lifecycle management (LCM) holds for addressing the unique challenges of AI in health care. LCM considerations can help AI meet real-world needs while managing inherent risks across the software lifecycle. https://lnkd.in/dNMensDy

The evolving and dynamic nature of AI/ML applications requires a fully integrated total product lifecycle management system.

A new blog post from the US FDA related to artificial intelligence (AI) used in healthcare applications. In this blog, they discuss how to map the AI software development life cycle (SDLC) process with existing standards and define the term AI lifecycle (AILC). AILC includes the following iterated phases: - Planning and Designing -- Problem definition -- Interpretability and Explainability -- and more - Data Collection and Management -- Data Governance and Documentation -- Data Versioning and Traceability -- and more - Model Building and Tuning -- Model Selection -- Model Interpretability and Explainability -- Hyperparameter tuning -- and more - Verification and Validation -- Evaluation Metric -- Documentation and Reporting -- Model comparison -- and more - Model Deployment -- Monitoring and logging -- Documentation and Training -- and more - Operation and Monitoring -- Continuous Improvement -- Alerting and notifications -- and more - Real-world Performance Evaluation -- Drift detection -- Documentation and Reporting -- and more Last but not least, Risk management and Cybersecurity should be incorporated across all phases of the lifecycle like the existing SDLC framework for either the medical device or software industry. The input can be utilized to establish/update a checklist to assess and define activities in each phase as applicable and incorporated into existing SDLC SOP/WIs in the Quality Management System (QMS) to meet the state-of-the-art practice. For more details, refer to https://lnkd.in/g7tHxT9v. #biomedicalengineering #precisionmedicine #digitalhealth #medicaldevices #qualitymanagementsystem #bioinformatics #healthcareinnovation #cybersecurity #healthcaretechnology #pointofcare #POC #healthtech #invitrodiagnostics #samd #simd #regulatoryaffairs #standards #internationalstandards #industrystandards #biotech #medtech #IVD #RiskManagement #AI #MachineLearning #IEC62304 #IEC82304 #QMS #SDLC #SOP #WI #QualityManagementSystem

Check out the latest blog post from CDRH’s Digital Health Center of Excellence on the potential lifecycle management (LCM) holds for addressing the unique challenges of AI in health care. LCM considerations can help AI meet real-world needs while managing inherent risks across the software lifecycle. https://lnkd.in/dNMensDy