Hospital-Based Medicine

Intensivists

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

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Showing 2836-2856 of 6,181 articles
Modeling multi-species RNA modification through multi-task curriculum learning.

N6-methyladenosine (m6A) is the most pervasive modification in eukaryotic mRNAs. Numerous biological...

Secondary structure prediction of protein based on multi scale convolutional attention neural networks.

To fully extract the local and long-range information of amino acid sequences and enhance the effect...

Merged Affinity Network Association Clustering: Joint multi-omic/clinical clustering to identify disease endotypes.

Although clinical and laboratory data have long been used to guide medical practice, this informatio...

[A Case of Descending Colon and Rectal Cancer with Acute Myeloid Leukemia Performed Robot‒Assisted Hartmann's Procedure].

The case is a 68‒year‒old male, who had been diagnosed with acute myeloid leukemia(AML)prior to rect...

Avoidable Serum Potassium Testing in the Cardiac ICU: Development and Testing of a Machine-Learning Model.

OBJECTIVES: To create a machine-learning model identifying potentially avoidable blood draws for ser...

Gene Classification Based on Multi-Class SVMs with Systematic Sampling and Hierarchical Clustering (SSHC) Algorithm.

The support vector machines (SVMs) is one of the machine learning algorithms with high classificatio...

A new multi-scale backbone network for object detection based on asymmetric convolutions.

Real-time object detection on mobile platforms is a crucial but challenging computer vision task. Ho...

Deep learning supported disease detection with multi-modality image fusion.

Multi-modal image fusion techniques aid the medical experts in better disease diagnosis by providing...

Artificial intelligence-based prediction of transfusion in the intensive care unit in patients with gastrointestinal bleeding.

OBJECTIVE: Gastrointestinal (GI) bleeding commonly requires intensive care unit (ICU) in cases of po...

Machine Learning for Biomedical Time Series Classification: From Shapelets to Deep Learning.

With the biomedical field generating large quantities of time series data, there has been a growing ...

A Case of Dapsone-induced Mild Methemoglobinemia with Dyspnea and Cyanosis.

Dear Editor, Dapsone is a dual-function drug with antimicrobial and antiprotozoal effects and anti-i...

Early Prediction of Sepsis From Clinical Data Using Ratio and Power-Based Features.

OBJECTIVES: Early prediction of sepsis is of utmost importance to provide optimal care at an early s...

Early Sepsis Prediction Using Ensemble Learning With Deep Features and Artificial Features Extracted From Clinical Electronic Health Records.

OBJECTIVES: Sepsis is caused by infection and subsequent overreaction of immune system and will seve...

Artificial intelligence to guide management of acute kidney injury in the ICU: a narrative review.

PURPOSE OF REVIEW: Acute kidney injury (AKI) frequently complicates hospital admission, especially i...

Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission.

OBJECTIVE: To compare the performance of machine learning models against the traditionally derived C...

An Explainable Artificial Intelligence Predictor for Early Detection of Sepsis.

OBJECTIVES: Early detection of sepsis is critical in clinical practice since each hour of delayed tr...

A Time-Phased Machine Learning Model for Real-Time Prediction of Sepsis in Critical Care.

OBJECTIVES: As a life-threatening condition, sepsis is one of the major public health issues worldwi...

Multi-Stroke handwriting character recognition based on sEMG using convolutional-recurrent neural networks.

Despite the increasing use of technology, handwriting has remained to date as an efficient means of ...

Dataset-aware multi-task learning approaches for biomedical named entity recognition.

MOTIVATION: Named entity recognition is a critical and fundamental task for biomedical text mining. ...

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