Health equity can provide equal opportunity for patients to achieve the best care possible. Medtech leaders from Boston Scientific, Sequel Med Tech, and ZEISS Medical Technology share how healthcare delivery, data transparency, and industry collaboration can provide more value to patients.
A new survey from the Center for Connected Medicine at UPMC Sheds light on how healthcare systems are navigating both the promise and the possible risk of AI and generative AI.
A review paper from the Agency for Healthcare Research and Quality supports the benefits of computerized clinical decision support systems (CDSS) in reducing medication errors and adverse drug events, but also uncovered risks and unintended consequences that must be addressed to improve patient safety and implementation of next generation systems.
Emerging technologies, integrated vendor ecosystems and enhanced regulatory compliance will redefine care delivery and shape the needs of healthcare stakeholders. Following are six healthcare technology trends that will shape care delivery and the MedTech market in 2024.
While AI is already making significant contributions to pre-operative planning and post-operative analysis, its utilization intra-operatively remains a key area for further development. Collecting and utilizing comprehensive intra-operative surgical data, as facilitated by innovative applications of existing technologies such as light field, will pave the way for advanced AI applications in spine surgery.
The integration of artificial intelligence (AI) into breast cancer detection and treatment is already making a profound impact. AI-powered algorithms enhance early detection by analyzing vast amounts of data and identifying subtle abnormalities often invisible to the human eye. These technologies empower healthcare professionals to make informed decisions, improving the accuracy of diagnoses and tailoring treatment plans to the specific genetic makeup and health conditions of individual patients. This integration represents a paradigm shift in the cancer care continuum.
“The V-CHAMPS Challenge showed us that artificial intelligence (AI) models that performed well on the synthetic patient data in Phase 1 also performed well on the RWD during Phase 2, highlighting the potential value of using synthetic data in AI model development.”
Even AI models trained on general medical literature will have difficulty making sense of the nuances specific to primary care, which is full of unique jargon, abbreviations and other idiosyncrasies. As always, the proverbial devil is in the details. Any AI solution worth its salt must be fluent in the specific idioms of the field and empower clinicians to deliver the best care that they can.
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.
