Hospital-Based Medicine

Intensivists

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

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Showing 421-441 of 6,135 articles
Advancing sepsis diagnosis and immunotherapy machine learning-driven identification of stable molecular biomarkers and therapeutic targets.

Sepsis represents a significant global health challenge, necessitating early detection and effective...

An intelligent multi-attribute decision-making system for clinical assessment of spinal cord disorder using fuzzy hypersoft rough approximations.

The data for diagnosing spinal cord disorder (SCD) are complex and often confusing, making it diffic...

Development and validation of an interpretable machine learning model for predicting in-hospital mortality for ischemic stroke patients in ICU.

BACKGROUND: Timely and accurate outcome prediction is essential for clinical decision-making for isc...

Integrated fusion approach for multi-class heart disease classification through ECG and PCG signals with deep hybrid neural networks.

Detection and classification of cardiovascular diseases are crucial for early diagnosis and predicti...

Automatic cerebral microbleeds detection from MR images via multi-channel and multi-scale CNNs.

BACKGROUND: Computer-aided detection (CAD) systems have been widely used to assist medical professio...

Dynamic Prediction and Intervention of Serum Sodium in Patients with Stroke Based on Attention Mechanism Model.

Abnormal serum sodium levels are a common and severe complication in stroke patients, significantly ...

Deep reinforcement learning for multi-targets propofol dosing.

The administration of propofol for sedation or general anesthesia presents challenges due to the com...

Leveraging Artificial Intelligence to Reduce Neuroscience ICU Length of Stay.

GOAL: Efficient patient flow is critical at Tampa General Hospital (TGH), a large academic tertiary ...

A multi-stage fusion deep learning framework merging local patterns with attention-driven contextual dependencies for cancer detection.

Cancer is a severe threat to public health. Early diagnosis of disease is critical, but the lack of ...

UGS-M3F: unified gated swin transformer with multi-feature fully fusion for retinal blood vessel segmentation.

Automated segmentation of retinal blood vessels in fundus images plays a key role in providing ophth...

OMS-CNN: Optimized Multi-Scale CNN for Lung Nodule Detection Based on Faster R-CNN.

The global increase in lung cancer cases, often marked by pulmonary nodules, underscores the critica...

Drug Repositioning via Multi-View Representation Learning With Heterogeneous Graph Neural Network.

Exploring simple and efficient computational methods for drug repositioning has emerged as a popular...

A damage identification method for aviation structure integrating Lamb wave and deep learning with multi-dimensional feature fusion.

With the development of aerospace industry, a more suitable structural health monitoring (SHM) metho...

Multi-task interaction learning for accurate segmentation and classification of breast tumors in ultrasound images.

In breast diagnostic imaging, the morphological variability of breast tumors and the inherent ambigu...

Canine EEG helps human: cross-species and cross-modality epileptic seizure detection via multi-space alignment.

Epilepsy significantly impacts global health, affecting about 65 million people worldwide, along wit...

Opportunistic access control scheme for enhancing IoT-enabled healthcare security using blockchain and machine learning.

The healthcare industry, aided by technology, leverages the Internet of Things (IoT) paradigm to off...

An AI-Based Clinical Decision Support System for Antibiotic Therapy in Sepsis (KINBIOTICS): Use Case Analysis.

BACKGROUND: Antimicrobial resistances pose significant challenges in health care systems. Clinical d...

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