AIMC Topic: Prospective Studies
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Utility of an Echocardiographic Machine Learning Model to Predict Outcomes in Intensive Cardiac Care Unit Patients.
Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
Dec 14, 2024
INTRODUCTION: The risk stratification at admission to the intensive cardiac care unit (ICCU) is crucial and remains challenging.
Feasibility of Sub-milliSievert Low-dose Computed Tomography with Deep Learning Image Reconstruction in Evaluating Pulmonary Subsolid Nodules: A Prospective Intra-individual Comparison Study.
Academic radiology
Dec 13, 2024
RATIONALE AND OBJECTIVES: To comprehensively assess the feasibility of low-dose computed tomography (LDCT) using deep learning image reconstruction (DLIR) for evaluating pulmonary subsolid nodules, which are challenging due to their susceptibility to...
Deep learning for segmentation of colorectal carcinomas on endoscopic ultrasound.
Techniques in coloproctology
Dec 13, 2024
BACKGROUND: Bowel-preserving local resection of early rectal cancer is less successful if the tumor infiltrates the muscularis propria as opposed to submucosal infiltration only. Magnetic resonance imaging currently lacks the spatial resolution to pr...
A clinical practical model for preoperative prediction of visual outcome for pituitary adenoma patients in a retrospective and prospective study.
Frontiers in endocrinology
Dec 13, 2024
OBJECTIVE: Preoperative prediction of visual recovery after pituitary adenoma resection surgery remains challenging. This study aimed to investigate the value of clinical and radiological features in preoperatively predicting visual outcomes after su...
Performance of image processing analysis and a deep convolutional neural network for the classification of oral cancer in fluorescence visualization.
International journal of oral and maxillofacial surgery
Dec 12, 2024
The aim of this prospective study was to determine the effectiveness of screening using image processing analysis and a deep convolutional neural network (DCNN) to classify oral cancers using non-invasive fluorescence visualization. The study include...
Prospective Evaluation of Real-Time Artificial Intelligence for the Hill Classification of the Gastroesophageal Junction.
United European gastroenterology journal
Dec 12, 2024
BACKGROUND: Assessment of the gastroesophageal junction (GEJ) is an integral part of gastroscopy; however, the absence of standardized reporting hinders consistency of examination documentation. The Hill classification offers a standardized approach ...
Employing artificial intelligence for optimising antibiotic dosages in sepsis on intensive care unit: a study protocol for a prospective observational study (KI.SEP).
BMJ open
Dec 12, 2024
INTRODUCTION: In sepsis treatment, achieving and maintaining effective antibiotic therapy is crucial. However, optimal antibiotic dosing faces challenges due to significant variability among patients with sepsis. Therapeutic drug monitoring (TDM), th...
Wound imaging software and digital platform to assist review of surgical wounds using patient smartphones: The development and evaluation of artificial intelligence (WISDOM AI study).
PloS one
Dec 9, 2024
INTRODUCTION: Surgical patients frequently experience post-operative complications at home. Digital remote monitoring of surgical wounds via image-based systems has emerged as a promising solution for early detection and intervention. However, the in...
RADHawk-an AI-based knowledge recommender to support precision education, improve reporting productivity, and reduce cognitive load.
Pediatric radiology
Dec 7, 2024
BACKGROUND: Using artificial intelligence (AI) to augment knowledge is key to establishing precision education in modern radiology training. Our department has developed a novel AI-derived knowledge recommender, the first reported precision education...
A multimodal machine learning model for the stratification of breast cancer risk.
Nature biomedical engineering
Dec 4, 2024
Machine learning models for the diagnosis of breast cancer can facilitate the prediction of cancer risk and subsequent patient management among other clinical tasks. For the models to impact clinical practice, they ought to follow standard workflows,...
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