AIMC Topic: Prospective Studies
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Machine Learning-Guided Fluid Resuscitation for Acute Pancreatitis Improves Outcomes.
Clinical and translational gastroenterology
Apr 1, 2025
INTRODUCTION: Ariel Dynamic Acute Pancreatitis Tracker (ADAPT) is an artificial intelligence tool using mathematical algorithms to predict severity and manage fluid resuscitation needs based on the physiologic parameters of individual patients. Our a...
Control of dental calculus Prevents severe Radiation-Induced oral mucositis in patients undergoing radiotherapy for nasopharyngeal carcinoma.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Mar 27, 2025
PURPOSE: This study aims to develop an artificial intelligence model to predict severe radiation-induced oral mucositis (RIOM) in patients with locally advanced nasopharyngeal carcinoma (LA-NPC) and verify the risk factors associated with severe RIOM...
Machine Learning Models predicting Decompensation in Cirrhosis.
Journal of gastrointestinal and liver diseases : JGLD
Mar 27, 2025
BACKGROUND AND AIMS: Decompensation of cirrhosis significantly decreases survival, thus, prevention of complications is paramount. We used machine learning techniques to identify parameters predicting decompensation.
Deep learning-based reconstruction for three-dimensional volumetric brain MRI: a qualitative and quantitative assessment.
BMC medical imaging
Mar 27, 2025
BACKGROUND: To evaluate the performance of a deep learning reconstruction (DLR) based on Adaptive-Compressed sensing (CS)-Network for brain MRI and validate it in a clinical setting.
A prospective study for the examination of peripheral blood smear samples in pediatric population using artificial intelligence.
Turkish journal of medical sciences
Mar 27, 2025
BACKGROUND/AIM: Peripheral blood smear (PBS) and bone marrow aspiration are gold standards of manual microscopy diagnostics for blood cell disorders. Nowadays, data-driven artificial intelligence (AI) techniques open new perspectives in digital hemat...
Predicting quality of life of patients after treatment for spinal metastatic disease: development and internal evaluation.
The spine journal : official journal of the North American Spine Society
Mar 26, 2025
BACKGROUND CONTEXT: When treating spinal metastases in a palliative setting, maintaining or enhancing quality of life (QoL) is the primary therapeutic objective. Clinicians tailor their treatment strategy by weighing the QoL benefits against expected...
Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score.
Critical care explorations
Mar 26, 2025
BACKGROUND: Early detection of clinical deterioration using machine-learning early warning scores may improve outcomes. However, most implemented scores were developed using logistic regression, only underwent retrospective validation, and were not t...
Artificial intelligence in dysphagia assessment: evaluating lingual muscle composition in head and neck cancer.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Mar 25, 2025
PURPOSE: Oropharyngeal dysphagia is a common and debilitating condition in head and neck cancer (HNC) patients. This study aimed to evaluate the relationship between tongue muscle composition (quantity and quality) and the risk of dysphagia in non-su...
Application of an AI-Based Model for Non-Invasive Sonographic Assessment for Injection Laryngoplasty.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Mar 21, 2025
OBJECTIVE: Hyaluronic acid (HA) can be degraded over time. However, the persistence of the effects after injection laryngoplasty (IL) for unilateral vocal fold paralysis (UVFP) has been observed. The relation between HA residue and clinical voice out...
Deep learning reconstruction for accelerated 3-D magnetic resonance cholangiopancreatography.
La Radiologia medica
Mar 18, 2025
PURPOSE: This study aimed to compare a conventional three-dimensional (3-D) magnetic resonance cholangiopancreatography (MRCP) sequence with a deep learning (DL)-accelerated MRCP sequence (hereafter, MRCP) regarding acquisition time and image quality...
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