The 12-lead ECG hasn't changed in a century. The algorithms reading it have. Three CEOs and one educator on whether doctors should trust the model ...
Researchers developed a hybrid UMAP-HDBSCAN-SVM machine learning workflow to rapidly classify low-loss STEM-EELS spectrum ...
It is a common misperception that electrocardiograms (ECGs) simply contain data about heart activity. However, modern ECGs ...
The use of AI in health care is challenging because sensitive patient data is scattered across different systems, and its use ...
AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...
A machine learning model developed by researchers at the Johns Hopkins Kimmel Cancer Center filters out the biological noise in liquid biopsy samples, helping clinicians better match therapies to ...
We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...
In the late 2000s, “mobile-first” emerged as a design discipline. The argument was a single sentence: don’t design for the big screen and squeeze it down. Start with the small screen, the harder ...
Machine learning has emerged as a transformative force in the field of neurosurgery, offering innovative tools to predict surgical outcomes with greater ...
BACKGROUND: Hypertension induces structural and functional damage in multiple organs. Evidence of subclinical damage ...
It’s been three-and-a-half years since generative AI exploded onto the scene. In this past year, progress has continued its relentless pace: Vibe coding took off, companies embraced agentic workflows, ...
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