AI is employed in healthcare for various applications, including medical image analysis, disease diagnosis, personalized treatment planning, and patient monitoring. It utilizes machine learning, natural language processing, and data analytics to improve diagnostic accuracy, optimize treatment outcomes, and enhance healthcare delivery, leading to more efficient and effective patient care.
AI systems in high-stakes industries often fail to provide clear explanations for their decisions, leaving users vulnerable. Researchers from the University of Surrey propose the SAGE framework to ensure AI-generated explanations are transparent, user-friendly, and ethically sound.
A new study finds that people trust AI for low-stakes decisions like music recommendations but are skeptical in high-stakes areas like healthcare—especially those with strong statistical literacy.
A national survey found that 65.8% of adults distrust their healthcare systems to use AI responsibly, highlighting concerns about safety and transparency in AI adoption.
Researchers developed a smart AI-powered heating jacket with color-changing yarns to prevent overheating, enhancing safety for users, particularly the elderly.
edars-Sinai is testing the Aiva Nurse Assistant, an AI-powered mobile app that allows nurses to document patient information through voice dictation, reducing administrative workload and improving efficiency. The pilot aims to enhance patient care by freeing up nurses’ time for meaningful interactions.
Researchers found that people distrust artificial moral advisors (AMAs), particularly when they offer utilitarian advice, even if the advice is identical to that of human advisors.
As a network of websites with a truly global audience, AZoNetwork is joining the global effort to close the gender gap. Since the first AZoNetwork website, AZoM, was launched in 2000, we have seen increased representation and recognition, with more women winning Nobel Prizes.
Researchers from NJIT, Rutgers, and Temple University are developing AI security education programs to address adversarial machine learning threats, aiming to equip future engineers with robust defense strategies.
Flinders University researchers used PROLIFERATE_AI to evaluate the RAPIDx AI tool’s effectiveness in diagnosing cardiac conditions in emergency departments, revealing both its benefits and challenges for clinicians of varying experience levels.
A new study highlights the growing risks of bias in large language models (LLMs) as they become cheaper and widely used, calling for ethical AI policies to ensure fairness and transparency.
Researchers at NTU Singapore have developed an AI-powered screening tool, ReCOGnAIze, that detects mild cognitive impairment (MCI) with nearly 90% accuracy using neuroscientific games in just 15 minutes. This partnership with Osler Group makes early dementia detection more accessible and cost-effective.
AI safety experts warn that rapid advancements in general-purpose AI pose increasing risks, from cyber threats to systemic economic impacts, urging better safeguards and international oversight.
Researchers at Binghamton University and the University at Buffalo are using AI and computational modeling to refine electrospray deposition, a technique for producing ultra-thin polymer films with applications in electronics and healthcare.
Researchers at EPFL's WiRE Lab have integrated explainable AI (XAI) into wind power forecasting models, improving transparency and reliability in predicting wind energy generation. Their study shows that XAI can identify key input variables, reducing uncertainty and making wind power more competitive in the energy market.
Researchers at KAIST have developed a highly reliable, selector-less memristor-based computing system that enables real-time, self-learning AI processing on edge devices, achieving accuracy comparable to ideal simulations in tasks like video foreground-background separation.
Researchers benchmarked AI models using the Seshat Global History Databank and found significant gaps in their ability to understand and analyze expert-level historical knowledge.
Research introduces an explainable AI model that predicts ICU length of stay with 90% accuracy while providing evidence-based insights for informed decision-making. This innovative approach aims to optimize resource allocation, reduce overcrowding, and improve patient outcomes.
Research explores how Natural Language Processing (NLP) models like ChatGPT revolutionize understanding and generating human language. It delves into their mechanics, training processes, potential applications, and ethical considerations in AI's rapid evolution.
The UK government launches a bold AI Opportunities Action Plan, aiming to drive economic growth, revolutionize public services, and position Britain as a global leader in artificial intelligence.
AI-powered solutions revolutionize cervical cancer screening by enhancing diagnostic accuracy, automating processes, and expanding access to underserved regions, offering a new frontier in prevention and early detection.
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