Summary A predictive maintenance model that processes data at high speed supports faster decision-making and real-time ...
There are golf developments that introduce a course. Then there are places that introduce a feeling long before the first tee ...
In many public healthcare systems, particularly in resource-constrained environments, time-series forecasting models offer a practical, interpretable, and evidence-based alternative (Stacey et al., ...
Indian pharma finds conventional analytics insufficient, turns to AI for actionable insights: Nandita Vijayasimha, Bengaluru Friday, July 10, 2026, 12:15 Hrs [IST] India's pharmac ...
It will use an AI model trained on clinical notes to help staff decide whether children may need emergency care.
AI tools are proliferating across pulmonary medicine and critical care, with promising early results in diagnostics and ...
We need more synthetic data in some areas, wearables and medical imaging cannot be substitutes, anonymisation is crucial but not simple – AI's challenges ...
Drs Ursula A. Matulonis and Marisa R. Nucci discuss the future of AI and pathology and how genetics and genomics play a role ...
Operational autonomy is quickly becoming one of the defining capabilities of a modern enterprise. As digital estates become ...
Pediatric hospital medicine is rapidly advancing with new research focusing on clinical management, quality improvement, health equity, and technology. This summary highlights the top articles from ...
Background Adult-onset Still’s disease (AOSD) is a systemic autoinflammatory disorder lacking a gold-standard diagnostic ...
Multiomics data integration with machine learning has become the standard approach for combining genomic, transcriptomic, proteomic, and metabolomic measurements collected from the same biological ...
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