Hospital-Based Medicine

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

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The Health Gym: synthetic health-related datasets for the development of reinforcement learning algorithms.

In recent years, the machine learning research community has benefited tremendously from the availab...

Electromyography-driven model-based estimation of ankle torque and stiffness during dynamic joint rotations in perturbed and unperturbed conditions.

The simultaneous modulation of joint torque and stiffness enables humans to perform large repertoire...

Multi-stage classification of Alzheimer's disease from F-FDG-PET images using deep learning techniques.

The study aims to implement a convolutional neural network framework that uses the 18F-FDG PET modal...

MFL-Net: An Efficient Lightweight Multi-Scale Feature Learning CNN for COVID-19 Diagnosis From CT Images.

Timely and accurate diagnosis of coronavirus disease 2019 (COVID-19) is crucial in curbing its sprea...

Self-Supervised Multi-Modal Hybrid Fusion Network for Brain Tumor Segmentation.

Accurate medical image segmentation of brain tumors is necessary for the diagnosing, monitoring, and...

Multi-label classification of Alzheimer's disease stages from resting-state fMRI-based correlation connectivity data and deep learning.

Alzheimer's disease is a neurodegenerative condition that gradually impairs cognitive abilities. Rec...

Natural Language Processing Model for Identifying Critical Findings-A Multi-Institutional Study.

Improving detection and follow-up of recommendations made in radiology reports is a critical unmet n...

MODENN: A Shallow Broad Neural Network Model Based on Multi-Order Descartes Expansion.

Deep neural networks have achieved great success in almost every field of artificial intelligence. H...

MSFF-Net: Multi-Stream Feature Fusion Network for surface electromyography gesture recognition.

In the field of surface electromyography (sEMG) gesture recognition, how to improve recognition accu...

Unraveling the complexities of urban fluvial flood hydraulics through AI.

As urbanization increases across the globe, urban flooding is an ever-pressing concern. Urban fluvia...

Emergence of MXene and MXene-Polymer Hybrid Membranes as Future- Environmental Remediation Strategies.

The continuous deterioration of the environment due to extensive industrialization and urbanization ...

Prediction of drug-target interactions through multi-task learning.

Identifying the binding between the target proteins and molecules is essential in drug discovery. Th...

In-sensor neural network for high energy efficiency analog-to-information conversion.

This work presents an on-chip analog-to-information conversion technique that utilizes analog hyper-...

Predicting risk of sepsis, comparison between machine learning methods: a case study of a Virginia hospital.

Sepsis is an inflammation caused by the body's systemic response to an infection. The infection coul...

Segmentation for Multi-Rock Types on Digital Outcrop Photographs Using Deep Learning Techniques.

The basic identification and classification of sedimentary rocks into sandstone and mudstone are imp...

3D multi-physics uncertainty quantification using physics-based machine learning.

Quantitative predictions of the physical state of the Earth's subsurface are routinely based on nume...

Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification.

Identification of novel non-invasive biomarkers is critical for the early diagnosis of lung adenocar...

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