Hospital-Based Medicine

Intensivists

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

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A Multi-model Deep Learning Architecture for Diagnosing Multi-class Skin Diseases.

Skin diseases are a significant global public health concern, affecting 21-85% of the world's popula...

Coronary Artery Disease Detection Based on a Novel Multi-Modal Deep-Coding Method Using ECG and PCG Signals.

Coronary artery disease (CAD) is an irreversible and fatal disease. It necessitates timely and preci...

Multi-Activity Step Counting Algorithm Using Deep Learning Foot Flat Detection with an IMU Inside the Sole of a Shoe.

Step counting devices were previously shown to be efficient in a variety of applications such as ath...

Multi-Class Segmentation Network Based on Tumor Tissue in Endometrial Cancer Pathology Images: ECMTrans-net.

Endometrial cancer has the second highest incidence of malignant tumors in the female reproductive s...

LTMSegnet: Lightweight multi-scale medical image segmentation combining Transformer and MLP.

Medical image segmentation is currently of a priori guiding significance in medical research and cli...

A Multi-level ensemble approach for skin lesion classification using Customized Transfer Learning with Triple Attention.

Skin lesions encompass a variety of skin abnormalities, including skin diseases that affect structur...

Personalized multi-head self-attention network for news recommendation.

With the rapid explosion of online news and user population, personalized news recommender systems h...

Integrative multi-omic and machine learning approach for prognostic stratification and therapeutic targeting in lung squamous cell carcinoma.

The proliferation, metastasis, and drug resistance of cancer cells pose significant challenges to th...

A multi-class fundus disease classification system based on an adaptive scale discriminator and hybrid loss.

Fundus images are crucial in the observation and detection of ophthalmic diseases. However, detectin...

InstructNet: A novel approach for multi-label instruction classification through advanced deep learning.

People use search engines for various topics and items, from daily essentials to more aspirational a...

Is artificial intelligence prepared for the 24-h shifts in the ICU?

Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient...

Self-adaptive label discovery and multi-view fusion for complementary label learning.

Unlike traditional supervised classification, complementary label learning (CLL) operates under a we...

Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study.

BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital ...

MobileNet-V2: An Enhanced Skin Disease Classification by Attention and Multi-Scale Features.

The increasing prevalence of skin diseases necessitates accurate and efficient diagnostic tools. Thi...

PViT-AIR: Puzzling vision transformer-based affine image registration for multi histopathology and faxitron images of breast tissue.

Breast cancer is a significant global public health concern, with various treatment options availabl...

Research of multi-label text classification based on label attention and correlation networks.

Multi-Label Text Classification (MLTC) is a crucial task in natural language processing. Compared to...

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