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Early prognosis prediction for non-variceal upper gastrointestinal bleeding in the intensive care unit: based on interpretable machine learning.

European journal of medical research
INTRODUCTION: This study aims to construct a mortality prediction model for patients with non-variceal upper gastrointestinal bleeding (NVUGIB) in the intensive care unit (ICU), employing advanced machine learning algorithms. The goal is to identify ...

Deep learning approach for dysphagia detection by syllable-based speech analysis with daily conversations.

Scientific reports
Dysphagia, a disorder affecting the ability to swallow, has a high prevalence among the older adults and can lead to serious health complications. Therefore, early detection of dysphagia is important. This study evaluated the effectiveness of a newly...

Assessing GPT-4 multimodal performance in radiological image analysis.

European radiology
OBJECTIVES: This study aims to assess the performance of a multimodal artificial intelligence (AI) model capable of analyzing both images and textual data (GPT-4V), in interpreting radiological images. It focuses on a range of modalities, anatomical ...

Can deep learning classify cerebral ultrasound images for the detection of brain injury in very preterm infants?

European radiology
OBJECTIVES: Cerebral ultrasound (CUS) is the main imaging screening tool in preterm infants. The aim of this work is to develop deep learning (DL) models that classify normal vs abnormal CUS to serve as a computer-aided detection tool providing timel...

Development and validation of a prediction model for malignant sinonasal tumors based on MR radiomics and machine learning.

European radiology
OBJECTIVES: This study aimed to utilize MR radiomics-based machine learning classifiers on a large-sample, multicenter dataset to develop an optimal model for predicting malignant sinonasal tumors and tumor-like lesions.

Development and External Validation of a Motor Intention-Integrated Prediction Model for Upper Extremity Motor Recovery After Intention-Driven Robotic Hand Training for Chronic Stroke.

Archives of physical medicine and rehabilitation
OBJECTIVE: To derive and validate a prediction model for minimal clinically important differences (MCIDs) in upper extremity (UE) motor function after intention-driven robotic hand training using residual voluntary electromyography (EMG) signals from...

Deep learning for efficient reconstruction of highly accelerated 3D FLAIR MRI in neurological deficits.

Magma (New York, N.Y.)
OBJECTIVE: To compare compressed sensing (CS) and the Cascades of Independently Recurrent Inference Machines (CIRIM) with respect to image quality and reconstruction times when 12-fold accelerated scans of patients with neurological deficits are reco...

An Integrated Radiopathomics Machine Learning Model to Predict Pathological Response to Preoperative Chemotherapy in Gastric Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: Accurately predicting the pathological response to chemotherapy before treatment is important for selecting the appropriate treatment groups, formulating individualized treatment plans, and improving the survival rates of pa...

Construction and verification of a machine learning-based prediction model of deep vein thrombosis formation after spinal surgery.

International journal of medical informatics
BACKGROUND: Deep vein thromboembolism (DVT) is a common postoperative complication with high morbidity and mortality rates. However, the safety and effectiveness of using prophylactic anticoagulants for preventing DVT after spinal surgery remain cont...