Hospital-Based Medicine

Intensivists

Latest AI and machine learning research in intensivists for healthcare professionals.

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Showing 379-399 of 6,135 articles
Scalable Multi-FPGA HPC Architecture for Associative Memory System.

Associative memory is a cornerstone of cognitive intelligence within the human brain. The Bayesian c...

A comprehensive review and trends in lubrication modelling.

Lubrication plays a pivotal role in modern society, given its significant economic and environmental...

M4: Multi-proxy multi-gate mixture of experts network for multiple instance learning in histopathology image analysis.

Multiple instance learning (MIL) has been successfully applied for whole slide images (WSIs) analysi...

MRI-based risk factors for intensive care unit admissions in acute neck infections.

OBJECTIVES: We assessed risk factors and developed a score to predict intensive care unit (ICU) admi...

DiffMC-Gen: A Dual Denoising Diffusion Model for Multi-Conditional Molecular Generation.

The precise and efficient design of potential drug molecules with diverse physicochemical properties...

DconnLoop: a deep learning model for predicting chromatin loops based on multi-source data integration.

BACKGROUND: Chromatin loops are critical for the three-dimensional organization of the genome and ge...

LMFE: A Novel Method for Predicting Plant LncRNA Based on Multi-Feature Fusion and Ensemble Learning.

: Long non-coding RNAs (lncRNAs) play a crucial regulatory role in plant trait expression and diseas...

Harness machine learning for multiple prognoses prediction in sepsis patients: evidence from the MIMIC-IV database.

BACKGROUND: Sepsis, a severe systemic response to infection, frequently results in adverse outcomes,...

Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.

Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. W...

Shared autonomy between human electroencephalography and TD3 deep reinforcement learning: A multi-agent copilot approach.

Deep reinforcement learning (RL) algorithms enable the development of fully autonomous agents that c...

Multi-head ensemble of smoothed classifiers for certified robustness.

Randomized Smoothing (RS) is a promising technique for certified robustness, and recently in RS the ...

Prognostic value of SAPS II score for 28-day mortality in ICU patients with acute pulmonary embolism.

BACKGROUND: Acute pulmonary embolism (APE) is a common and life-threatening emergency in intensive c...

Developing a high-performance AI model for spontaneous intracerebral hemorrhage mortality prediction using machine learning in ICU settings.

BACKGROUND: Spontaneous intracerebral hemorrhage (SICH) is a devastating condition that significantl...

Amogel: a multi-omics classification framework using associative graph neural networks with prior knowledge for biomarker identification.

The advent of high-throughput sequencing technologies, such as DNA microarray and DNA sequencing, ha...

Adaptive bigraph-based multi-view unsupervised dimensionality reduction.

As a crucial machine learning technology, graph-based multi-view unsupervised dimensionality reducti...

Constructing an early warning model for elderly sepsis patients based on machine learning.

Sepsis is a serious threat to human life. Early prediction of high-risk populations for sepsis is ne...

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