Chest CT Scans Could Secretly Reveal Your Heart Attack Risk Years Early
Researchers show that routine chest CT scans, combined with machine learning analysis of body composition and clinical data, can opportunistically ...
Researchers show that routine chest CT scans, combined with machine learning analysis of body composition and clinical data, can opportunistically ...
A new cloud-edge AI framework called SMWPF combines a lightweight edge predictor with a Qwen-based cloud model to cut wind ...
An adaptive porosity-based segmentation method called Smart Threshold replaces fixed thresholds in apple CT imaging, revealing cultivar-specific tissue architecture and ...
Researchers in China have developed an internally validated machine learning model that predicts long-term post-stroke disability from routine admission blood ...
A machine learning framework classifies patients across three diabetes stages with 98.7% accuracy while explaining exactly which clinical variables drove ...
A new systematic review of 150 studies argues that AI-driven cybersecurity for the Industrial Internet of Things has reached impressive ...
When a new monitoring device disagrees with the clinical assessment it is supposed to improve, standard diagnostic accuracy analyses cannot ...
A deep learning model that fuses PET imaging features with clinical data predicted breast cancer molecular subtypes non-invasively, reaching an ...
A multicenter Chinese study shows that a machine-learning radiomics model built from routine non-contrast CT scans, combined with clinical features, ...
A new analysis argues that solid-state batteries could transform robotics, revealing that a single commercial robot consumes an EV-equivalent 60 ...
A new review maps how artificial intelligence is transforming RNA-targeted drug discovery across both small molecules and oligonucleotide therapeutics.
A new study tests whether trade, governance and environmental tax indicators can classify national CO2 emission levels, and finds that ...
Interpretable machine learning models predict 7-, 14-, and 28-day mortality in sepsis-associated liver injury, outperforming modified SOFA and MELD-Na in ...
Argonne researchers built Phy-ChemNODE, a physics-constrained autoencoder-NeuralODE framework that emulates stiff methane combustion kinetics with 6x to 860x speedups while ...
A sentinel hospital study in Guangzhou tested a reporting-lag-aware machine learning framework for seven-day-ahead forecasting of influenza, COVID-19 and Mycoplasma ...
A French research team has combined time-domain reflectometry with temporal convolutional networks to detect, locate, and characterize wiring faults, achieving ...
A comparative study finds that a fine-tuned DistilBERT pipeline reliably detects deceptive hotel reviews while a Perceiver-based pipeline collapses toward ...
KAIST researchers developed a technology called SHIRBT-MMF that identifies daily stress from repeated smartphone behaviors such as messenger chatting, web ...
A global machine learning study of 163 countries finds that national wealth and diagnostic intensity, not diet, explain most of ...
Artificial intelligence is quietly transforming two of the most intimate fields of medicine: neuroscience and psychology. A new editorial published ...
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