TL;DR
This paper traces the development of GenAI, with a focus on its application in mobile AI assistants integrated into smartphones and edge computing platforms.
How Generative AI is evolving beyond ChatGPT is discussed and its potential to support human creativity and problem-solving is explored and the need for reliable, transparent, secure, and responsible AI systems for future applications is emphasized.
It is shown that merely adding auxiliary modalities does not guarantee improvement on ICU mortality prediction over an EHR-only baseline, and implies that careful design of the fusion architecture and an appropriate evaluation in the clinical context are required.
This survey serves as a foundational reference for advancing generative AI techniques across the audio domain, and is the first work to jointly cover all three audio domains and all generative model families, while also providing dedicated evaluation-metric analysis and cross-domain comparative assessments.
The impact of balancing real and SD is examined and some recommendations that researchers can further utilise to improve the ML model’s training process are provided and which approaches to adopt are considered.
It is concluded that AI is best positioned, in the near term, as an assistive layer rather than an autonomous agent, and the rationale for developing vertically oriented, laboratory-specific foundation models that can integrate structured results, longitudinal patient data, quality-control metadata, instrument informat...
It is argued that the next phase of AI in MCH must shift from static prediction toward longitudinal, mechanism-aware, and clinically actionable systems, supported by robust validation and multidisciplinary collaboration.
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