Hospital-Based Medicine

Intensivists

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

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Showing 484-504 of 6,147 articles
Precise multi-factor immediate implant placement decision models based on machine learning.

This study aims to explore the effect of implant apex design, osteotomy preparation, intraosseous de...

Diffusion-driven multi-modality medical image fusion.

Multi-modality medical image fusion (MMIF) technology utilizes the complementarity of different moda...

Hierarchical task network-enhanced multi-agent reinforcement learning: Toward efficient cooperative strategies.

Navigating multi-agent reinforcement learning (MARL) environments with sparse rewards is notoriously...

EMBANet: A flexible efficient multi-branch attention network.

Recent advances in the design of convolutional neural networks have shown that performance can be en...

Multi-modality medical image classification with ResoMergeNet for cataract, lung cancer, and breast cancer diagnosis.

The variability in image modalities presents significant challenges in medical image classification,...

Deep attention model for arrhythmia signal classification based on multi-objective crayfish optimization algorithmic variational mode decomposition.

The detection and classification of arrhythmia play a vital role in the diagnosis and management of ...

MorphBungee: A 65-nm 7.2-mm 27-µJ/Image Digital Edge Neuromorphic Chip With on-Chip 802-Frame/s Multi-Layer Spiking Neural Network Learning.

This paper presents a digital edge neuromorphic spiking neural network (SNN) processor chip for a va...

Exploring hyperelastic material model discovery for human brain cortex: Multivariate analysis vs. artificial neural network approaches.

The human brain, characterized by its intricate architecture, exhibits complex mechanical properties...

An Enhanced Protocol to Expand Human Exposome and Machine Learning-Based Prediction for Methodology Application.

The human exposome remains limited due to the challenging analytical strategies used to reveal low-l...

Resilience of hierarchical actuators highlighted by a myosin-to-muscle mock-up.

Skeletal muscle is the main actuator of various families of vertebrates (mammals, fish, reptiles). I...

Enhancing machine learning performance in cardiac surgery ICU: Hyperparameter optimization with metaheuristic algorithm.

The healthcare industry is generating a massive volume of data, promising a potential goldmine of in...

Learning robust medical image segmentation from multi-source annotations.

Collecting annotations from multiple independent sources could mitigate the impact of potential nois...

Class-aware multi-level attention learning for semi-supervised breast cancer diagnosis under imbalanced label distribution.

Breast cancer affects a significant number of patients worldwide, and early diagnosis is critical fo...

A multi-domain feature fusion epilepsy seizure detection method based on spike matching and PLV functional networks.

The identification of spikes, as a typical characteristic wave of epilepsy, is crucial for diagnosin...

Multi-source sparse broad transfer learning for parkinson's disease diagnosis via speech.

Diagnosing Parkinson's disease (PD) via speech is crucial for its non-invasive and convenient data c...

Fast finite-time quantized control of multi-layer networks and its applications in secure communication.

This paper introduces a quantized controller to address the challenge of fast finite-time synchroniz...

Multimodal convolutional neural networks for the prediction of acute kidney injury in the intensive care.

Increased monitoring of health-related data for ICU patients holds great potential for the early pre...

Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR.

The revolutionary CRISPR-Cas9 system leverages a programmable guide RNA (gRNA) and Cas9 proteins to ...

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