Background Improvement science has supported the methodological foundations for the application of quality improvement (QI) ...

Software engineers developing artificial intelligence (AI) models using standard frameworks such as Keras, PyTorch, and TensorFlow are usually not well-equipped to translate those models into ...

The shift toward AI-driven decision frameworks is not simply a technological trend but a fundamental necessity for life ...

This workshop will provide an introduction to the types of theories, models, and frameworks (TMFs) commonly used in dissemination and implementation science, including pros and cons and application of ...

Effective pre-implementation planning is critical for successful adoption of intelligent process automation (IPA). The comprehensive IPA pre-implementation framework outlined in this document provides ...

New technologies are often so brimming with potential that they're difficult to define. In turn, that makes them harder to implement as part of an overarching digital transformation strategy. Many ...

Similar to how we synthesized a framework for value-based payment (VBP)-specific design considerations in previous Health Affairs Forefront work, we present here a brief framework for categorizing the ...

Investors are reassessing fragmented implementation models as portfolio complexity, liquidity demands, and market risks grow. Read more ...

The toolkits are designed to help researchers and learners more easily digest the literature on D&I science and to generate ideas for applying it to their work. Each includes a compilation of relevant ...

The African Centre for Leadership, Strategy and Development (Centre LSD), alongside political economists and development specialists, has commended President Bola Ahmed Tinubu for proposing the ...