arXiv:2606. 29889v1 Announce Type: new Abstract: Timely intensive care dictates survival, yet emergency infrastructure remains unevenly distributed across Sri Lanka.
arXiv:2606. 19975v1 Announce Type: cross Abstract: This paper examines the impact of artificial intelligence and digital technologies on the blue-collar gig economy in India, focusing on algorithmic management.
Google DeepMind brings National Partnerships for AI initiative to India, scaling AI for science and education
OpenAI for India expands AI access across the country—building local infrastructure, powering enterprises, and advancing workforce skills.
arXiv:2609.09356v1 Announce Type: new Abstract: At Noora Health, our nurses answer more than 50,000 medical queries per month on our WhatsApp-based service that provides caregivers with on-demand sup...
arXiv:2602. 13241v3 Announce Type: replace-cross Abstract: Emergency call-takers form the first operational link in public safety response, handling over 240 million calls annually while facing a sustained training crisis: staffing shortages exceed 25\% in many centers, and preparing a single new hire can require up to 720 hours of one-on-one instruction that removes experienced personnel from active duty.
arXiv:2608. 12863v1 Announce Type: new Abstract: As AI systems proliferate in consumer facing applications, questions about liability for AI related harms remain unresolved.
Oscar brings AI to health insurance, reducing costs and improving patient care.
arXiv:2606. 12423v1 Announce Type: cross Abstract: The rapid integration of artificial intelligence (AI) into critical infrastructure including healthcare, finance, energy, and defense, offers transformative benefits but also conflicts with evolving regulatory and governance frameworks.
The scoping review examines how artificial intelligence (AI) is applied across all stages of medication management in rural healthcare settings, from prescribing to post-administration monitoring. It identifies four main themes: the types of AI used, the medication phases impacted, the effectiveness in reducing errors, and rural-specific challenges such as infrastructure and alert fatigue. Studies show machine‑learning surveillance can cut prescribing and transcription errors by 34% to 80%, yet barriers like governance gaps, funding limits, and clinician resistance remain.
arXiv:2607. 19075v1 Announce Type: cross Abstract: The rapid growth of the global aging population presents severe challenges to healthcare systems, necessitating efficient, equitable, and patient-centered care models.
AI for Disaster Response in Asia: OpenAI Workshop with Gates Foundation
