Hospital-Based Medicine

Intensivists

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

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Renal Dysfunction Across the Spectrum of Cardiogenic Shock: Mechanisms, Clinical Implications, and Therapeutic Strategies.

PURPOSE OF REVIEW: This review aims to elucidate the complex interplay between cardiogenic shock (CS...

PoseNet++: A multi-scale and optimized feature extraction network for high-precision human pose estimation.

Human pose estimation (HPE) has made significant progress with deep learning; however, it still face...

Multimodal Depression Recognition via Mutual Information Maximization Joint with Multi-task Learning.

Depression is a serious mental health disorder with a potential hazard for individuals and society c...

MVT-Net: A novel cervical tumour segmentation using multi-view feature transfer learning.

Cervical cancer is one of the most aggressive malignant tumours of the reproductive system, posing a...

Evidence-based Multi-Feature Fusion for Adversarial Robustness.

The accumulation of adversarial perturbations in the feature space makes it impossible for Deep Neur...

High-precision deformation monitoring and intelligent early warning for wellbore based on BDS/GNSS.

To address the complex deformation of wellbores influenced by surrounding coal mining operations, th...

Disease entity impacts muscle wasting in the ICU with COVID-19 patients losing muscle nearly twice as fast.

Muscle loss in critically ill patients, particularly during prolonged ICU stays, poses significant c...

Automatic Multi-Task Segmentation and Vulnerability Assessment of Carotid Plaque on Contrast-Enhanced Ultrasound Images and Videos via Deep Learning.

Intraplaque neovascularization (IPN) within carotid plaque is a crucial indicator of plaque vulnerab...

DynSeizureGAT: Multi-band Dynamic Graph Attention Network for Interpretable Seizure Detection and Analysis of Drug-Resistant Epilepsy Using SEEG.

The dynamic propagation of epileptic discharges complicates Drug-Resistant Epilepsy (DRE) seizure de...

MVKD-Trans: A Multi-View Knowledge Distillation Vision Transformer Architecture for Breast Cancer Classification Based on Ultrasound Images.

Breast cancer is the leading cancer threatening women's health. In recent years, deep neural network...

Dysregulated neural coding in the vagus nerve during long sepsis.

Sepsis is a life-threatening condition characterized by organ dysfunction resulting from the body's ...

Multi-omics approaches: transforming the landscape of natural product isolation.

The field of natural product (NPs) discovery has significantly evolved with the advent of multi-omic...

Development of a Machine Learning-Based Predictive Model for Postoperative Delirium in Older Adult Intensive Care Unit Patients: Retrospective Study.

BACKGROUND: Delirium is a prevalent phenomenon among patients admitted to the geriatric intensive ca...

Machine learning model for daily prediction of pediatric sepsis using Phoenix criteria.

BACKGROUND: Early sepsis diagnosis is essential for initiating prompt treatment, preventing the prog...

Prediction of Sepsis after Endourologic Kidney Stone Surgery: A Machine Learning Approach.

Sepsis secondary to urinary tract infection after kidney stone surgery is associated with considera...

Automated Multi-grade Brain Tumor Classification Using Adaptive Hierarchical Optimized Horse Herd BiLSTM Fusion Network in MRI Images.

Brain tumor classification using Magnetic Resonance Imaging (MRI) images is an important and emergin...

Applying a multi-task and multi-instance framework to predict axillary lymph node metastases in breast cancer.

Deep learning (DL) models have shown promise in predicting axillary lymph node (ALN) status. However...

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