AIMC Topic: Prospective Studies
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A digital phenotyping dataset for impending panic symptoms: a prospective longitudinal study.
Scientific data
Nov 21, 2024
This study investigated the utilization of digital phenotypes and machine learning algorithms to predict impending panic symptoms in patients with mood and anxiety disorders. A cohort of 43 patients was monitored over a two-year period, with data col...
An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study.
European radiology experimental
Nov 20, 2024
BACKGROUND: To retrospectively assess the added value of an artificial intelligence (AI) algorithm for detecting pulmonary nodules on ultra-low-dose computed tomography (ULDCT) performed at the emergency department (ED).
Deep learning reconstruction for accelerated high-resolution upper abdominal MRI improves lesion detection without time penalty.
Diagnostic and interventional imaging
Nov 19, 2024
PURPOSE: The purpose of this study was to compare a conventional T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence with a DL-reconstructed accelerated high-resolution VIBE sequence (HR-VIBE) in terms of image quality, lesion...
Prediction of esophageal fistula in radiotherapy/chemoradiotherapy for patients with advanced esophageal cancer by a clinical-deep learning radiomics model : Prediction of esophageal fistula in radiotherapy/chemoradiotherapy patients.
BMC medical imaging
Nov 18, 2024
BACKGROUND: Esophageal fistula (EF), a rare and potentially fatal complication, can be better managed with predictive models for personalized treatment plans in esophageal cancers. We aim to develop a clinical-deep learning radiomics model for effect...
Non-invasive multiple cancer screening using trained detection canines and artificial intelligence: a prospective double-blind study.
Scientific reports
Nov 15, 2024
The specificity and sensitivity of a simple non-invasive multi-cancer screening method in detecting breast, lung, prostate, and colorectal cancer in breath samples were evaluated in a double-blind study. Breath samples of 1386 participants (59.7% mal...
Repeatability of Microperimetry in Areas of Retinal Pigment Epithelium and Photoreceptor Loss in Geographic Atrophy Supported by Artificial Intelligence-Based Optical Coherence Tomography Biomarker Quantification.
American journal of ophthalmology
Nov 14, 2024
PURPOSE: Growing interest in microperimetry (MP) or fundus-controlled perimetry as a targeted psychometric testing method in geographic atrophy (GA) is warranted because of the disease subclinical/extrafoveal appearance or preexisting foveal loss wit...
A machine learning approach to stratify patients with hypermobile Ehlers-Danlos syndrome/hypermobility spectrum disorders according to disorders of gut brain interaction, comorbidities and quality of life.
Neurogastroenterology and motility
Nov 14, 2024
BACKGROUND: A high prevalence of disorders of gut-brain interaction (DGBI) exist in patients with hypermobile Ehlers-Danlos Syndrome (hEDS) and hypermobility spectrum disorders (HSD). However, it is unknown if clusters of hEDS/HSD patients exist whic...
Deep learning based ultra-low dose fan-beam computed tomography image enhancement algorithm: Feasibility study in image quality for radiotherapy.
Journal of applied clinical medical physics
Nov 14, 2024
OBJECTIVE: We investigated the feasibility of deep learning-based ultra-low dose kV-fan-beam computed tomography (kV-FBCT) image enhancement algorithm for clinical application in abdominal and pelvic tumor radiotherapy.
Phantoms, Imaging
Prospective Studies
Image Processing, Computer-Assisted
Abdominal Neoplasms
Tomography, X-Ray Computed
Radiographic Image Interpretation, Computer-Assisted
Radiation Dosage
Humans
Radiotherapy, Image-Guided
Female
Feasibility Studies
Signal-To-Noise Ratio
Algorithms
Radiographic Image Enhancement
Male
Organs at Risk
Pelvic Neoplasms
Deep Learning
Radiotherapy Planning, Computer-Assisted
Radiotherapy Dosage
Radiotherapy, Intensity-Modulated
Understanding and modeling human-AI interaction of artificial intelligence tool in radiation oncology clinic using deep neural network: a feasibility study using three year prospective data.
Physics in medicine and biology
Nov 14, 2024
Artificial intelligence (AI) based treatment planning tools are being implemented in clinic. However, human interactions with such AI tools are rarely analyzed. This study aims to comprehend human planner's interaction with the AI planning tool and i...
Feasibility of Ultra-low Radiation and Contrast Medium Dosage in Aortic CTA Using Deep Learning Reconstruction at 60 kVp: An Image Quality Assessment.
Academic radiology
Nov 13, 2024
OBJECTIVE: To assess the viability of using ultra-low radiation and contrast medium (CM) dosage in aortic computed tomography angiography (CTA) through the application of low tube voltage (60kVp) and a novel deep learning image reconstruction algorit...
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