The convergence of gamification and AI heralds a transformative era in mental health care, offering a blend of engagement and precision previously unattainable.
Recent developments, specifically artificial intelligence and the ubiquity of smart devices, enable us to monitor cough unobtrusively and continuously for periods of time. Objective cough quantification can be combined with patients’ perceptions to better determine diagnosis, treatment response and prognosis.
This week Huma Therapeutics received FDA Class II 510(k) clearance for its Software as a Medical Device (SaMD) platform, potentially speeding approval of a variety of AI and machine-learning (ML)-powered digital health devices. We spoke with Kaushik Gune, U.S. Head of Healthcare at Huma, about the current state of digital health technologies, the value of partnerships to enhance the use of real world data and how digital health is likely to advance in the coming years.
“The innovation, security and reliability of AWS helps us accelerate the delivery of high-quality clinical documentation. Our overarching goal is to create a better, more sustainable solution and to continue to be a trusted partner that our clients can rely on to reduce administrative tasks and prioritize patient engagement.”
Rama Chellappa, PhD, John Hopkins University Bloomberg Distinguished Professor in electrical, computer, and biomedical engineering, and co-author of “Can We Trust AI?” looks at the promise of AI in health care and how we can best utilize this extraordinary tool to save lives and improve health equity.
A global pandemic is still upon us, but that certainly does not mean that healthcare technology innovation is standing still. To help the medical device industry look to the future and prepare, experts from regulation and academia alike are bringing attention to the acceleration and pitfalls of innovation.
AI’s arrival in the cardiovascular profession brings a plethora of new opportunities for providing innovative, tailored treatment.
Opportunities for intelligent computer systems span widely, including extensive use in medical science. Artificial intelligence enhances cognition analysis of complex health issues and improves the diagnoses. However, there are still some challenges in terms of data quality, regulations, market penetration and adaptation.