Hospital-Based Medicine

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

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Showing 1849-1869 of 6,177 articles
Assessment of acute kidney injury risk using a machine-learning guided generalized structural equation model: a cohort study.

BACKGROUND: Acute kidney injury is common in the surgical intensive care unit (ICU). It is associate...

A Deep Learning-Based Camera Approach for Vital Sign Monitoring Using Thermography Images for ICU Patients.

Infrared thermography for camera-based skin temperature measurement is increasingly used in medical ...

Machining learning predicts the need for escalated care and mortality in COVID-19 patients from clinical variables.

This study aimed to develop a machine learning algorithm to identify key clinical measures to triag...

HeMA: A hierarchically enriched machine learning approach for managing false alarms in real time: A sepsis prediction case study.

Early detection of sepsis can be life-saving. Machine learning models have shown great promise in ea...

From predictions to prescriptions: A data-driven response to COVID-19.

The COVID-19 pandemic has created unprecedented challenges worldwide. Strained healthcare providers ...

GHS-NET a generic hybridized shallow neural network for multi-label biomedical text classification.

Exponential growth of biomedical literature and clinical data demands more robust yet precise comput...

SAM-GAN: Self-Attention supporting Multi-stage Generative Adversarial Networks for text-to-image synthesis.

Synthesizing photo-realistic images based on text descriptions is a challenging task in the field of...

Radiomic Machine Learning Classifiers in Spine Bone Tumors: A Multi-Software, Multi-Scanner Study.

PURPOSE: Spinal lesion differential diagnosis remains challenging even in MRI. Radiomics and machine...

A multipurpose machine learning approach to predict COVID-19 negative prognosis in São Paulo, Brazil.

The new coronavirus disease (COVID-19) is a challenge for clinical decision-making and the effective...

An in silico deep learning approach to multi-epitope vaccine design: a SARS-CoV-2 case study.

The rampant spread of COVID-19, an infectious disease caused by SARS-CoV-2, all over the world has l...

Machine Learning-Based Early Warning Systems for Clinical Deterioration: Systematic Scoping Review.

BACKGROUND: Timely identification of patients at a high risk of clinical deterioration is key to pri...

Risk factors analysis of COVID-19 patients with ARDS and prediction based on machine learning.

COVID-19 is a newly emerging infectious disease, which is generally susceptible to human beings and ...

A Deep Segmentation Network of Multi-Scale Feature Fusion Based on Attention Mechanism for IVOCT Lumen Contour.

Recently, coronary heart disease has attracted more and more attention, where segmentation and analy...

CrystalM: A Multi-View Fusion Approach for Protein Crystallization Prediction.

Improving the accuracy of predicting protein crystallization is very important for protein crystalli...

Combined Spiral Transformation and Model-Driven Multi-Modal Deep Learning Scheme for Automatic Prediction of TP53 Mutation in Pancreatic Cancer.

Pancreatic cancer is a malignant form of cancer with one of the worst prognoses. The poor prognosis ...

Spherical-Patches Extraction for Deep-Learning-Based Critical Points Detection in 3D Neuron Microscopy Images.

Digital reconstruction of neuronal structures is very important to neuroscience research. Many exist...

Machine learning model for predicting severity prognosis in patients infected with COVID-19: Study protocol from COVID-AI Brasil.

The new coronavirus, which began to be called SARS-CoV-2, is a single-stranded RNA beta coronavirus,...

A Machine Learning Multi-Class Approach for Fall Detection Systems Based on Wearable Sensors with a Study on Sampling Rates Selection.

Falls are dangerous for the elderly, often causing serious injuries especially when the fallen perso...

Artificial intelligence in sepsis early prediction and diagnosis using unstructured data in healthcare.

Sepsis is a leading cause of death in hospitals. Early prediction and diagnosis of sepsis, which is ...

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