Latest AI and machine learning research in intensivists for healthcare professionals.
Background: Klebsiella pneumoniae is a global pathogen with significant rates of antimicrobial resis...
Scaling laws suggest that increasing model size, training data, and compute generally yields monoton...
Offline sepsis treatment aims to learn treatment policies from retrospective ICU trajectories. Decis...
Patients admitted to pediatric ICU and cardiac ICU often require intensive perioperative support and...
Advances in electronic health records (EHR) and large-scale critical care databases have enabled the...
Population health stratification frameworks, such as the Italian DM77, organize patients by clinical...
Background: Patients with intracerebral hemorrhage (ICH) in intensive care units (ICUs) frequently r...
Embodied coding agents construct robot policies from natural-language instructions by generating exe...
Retrieval-augmented generation (RAG) is a widely used approach for grounding large language models (...
Time-series data are often sampled irregularly at high frequencies and exhibit long-range dependenci...
Medical vision-language model (VLM) evaluation is sensitive to workflow design, prompting strategy, ...
Accurate prediction of adverse events in the intensive care unit (ICU) following cardiothoracic surg...
Sepsis causes approximately 11 million deaths globally each year. Whole-genome sequencing (WGS) of f...
Although recent 3D generative models produce increasingly realistic assets, controllable 3D asset ed...
Multi-agent systems (MAS) are increasingly used to automate enterprise workflows involving multiple ...
Quantitative characterization of lymph node morphology is important for assessing axillary lymph nod...
Continuous-time sensing and monitoring with timely and accurate decision-making are critical for man...
Visual grounding in remote sensing images aims to locate objects described by referring expressions....
Hi-OPD addresses a failure mode left uncontrolled by flat open-prompt training: descendant retrieval...
Clinical multimodal models must often predict before all chest X-ray (CXR) and electronic health rec...
Machine learning can be crucial to help scale complex signal processing applications in scenarios su...