If the last two years were defined by the breathless hype of experimentation, 2026 marks the healthcare industry’s decisive transition from “flashy, one-off experiments” to “top-down programs designed for measurable impact”. Across the digital…
Continue Reading
Primary eye care providers refer glaucoma patients using their clinical experience and context. Specialized Artificial Intelligence (AI) excels in referrals trained on clinical data but relies on assumptions that may not hold in practice….
Continue Reading
Accurately predicting surgical and transfusion needs in traumatic brain injury (TBI) patients remains challenging in emergency settings. We developed multiomics data fusion (MDF) models integrating clinical biomarkers, neural radiological imaging, and clinical text mining…
Continue Reading
While chronological age is a universal risk predictor across most populations and diseases, distinguishing between biologically older from younger individuals may identify individuals with accelerated or delayed cardiovascular aging. This study presents a deep…
Continue Reading
Explainable Artificial Intelligence (XAI) is proposed as essential for high-risk applications like healthcare, where it aims to enhance user trust. However, studies often rely on automated metrics rather than user evaluation. We adapt a…
Continue Reading
CDW Healthcare Strategist David Anderson said that he has found discussions around artificial intelligence to be more rooted in reality.
“I think people are really having more in-depth conversations about their AI strategy,” he said….
Artificial intelligence (AI) tools for radiology are commonly unmonitored once deployed. The lack of real-time case-by-case assessments of AI prediction confidence requires users to independently distinguish between trustworthy and unreliable AI predictions, which increases…
Continue Reading
To address the diversity of skin conditions and the low prevalence of skin cancers, we curated a large hospital dataset (National Information Society Agency, Seoul, Korea [NIA] dataset; 70 diseases, 152,443 images) and collected…
Continue Reading
Dynamic response to therapy is strongly associated with cancer outcomes. We aim to develop the response-adapted individualized risk index (RAIRI) as an individual prognostic approach and predictive biomarker for adjuvant chemotherapy (AC) benefit in…
Continue Reading
Identification of cohorts at higher risk of cancer can enable earlier diagnosis of the disease, which significantly improves patient outcomes. In this study, we select nine cancer sites with high incidence of late-stage diagnosis…
Continue Reading
