AIMC Topic: Prospective Studies

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Machine Learning-Based Prediction of Hospitalization During Chemoradiotherapy With Daily Step Counts.

JAMA oncology
IMPORTANCE: Toxic effects of concurrent chemoradiotherapy (CRT) can cause treatment interruptions and hospitalizations, reducing treatment efficacy and increasing health care costs. Physical activity monitoring may enable early identification of pati...

Develop and Validate a Prognostic Index With Laboratory Tests to Predict Mortality in Middle-Aged and Older Adults Using Machine Learning Models: A Prospective Cohort Study.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Prognostic indices can enhance personalized predictions of health burdens. However, a simple, practical, and reproducible tool is lacking for clinical use. This study aimed to develop a machine learning-based prognostic index for predicti...

Machine Learning-Based Prediction of Malnutrition in Surgical In-Patients: A Validation Pilot Study.

Studies in health technology and informatics
BACKGROUND: Malnutrition in hospitalised patients can lead to serious complications, worse patient outcomes and longer hospital stays. State-of-the-art screening methods rely on scores, which need additional manual assessments causing higher workload...

Dark-Blood Computed Tomography Angiography Combined With Deep Learning Reconstruction for Cervical Artery Wall Imaging in Takayasu Arteritis.

Korean journal of radiology
OBJECTIVE: To evaluate the image quality of novel dark-blood computed tomography angiography (CTA) imaging combined with deep learning reconstruction (DLR) compared to delayed-phase CTA images with hybrid iterative reconstruction (HIR), to visualize ...

A deep-learning model for intracranial aneurysm detection on CT angiography images in China: a stepwise, multicentre, early-stage clinical validation study.

The Lancet. Digital health
BACKGROUND: Artificial intelligence (AI) models in real-world implementation are scarce. Our study aimed to develop a CT angiography (CTA)-based AI model for intracranial aneurysm detection, assess how it helps clinicians improve diagnostic performan...

Panoramic imaging errors in machine learning model development: a systematic review.

Dento maxillo facial radiology
OBJECTIVES: To investigate the management of imaging errors from panoramic radiography (PAN) datasets used in the development of machine learning (ML) models.

Image Quality and Diagnostic Performance of Low-Dose Liver CT with Deep Learning Reconstruction versus Standard-Dose CT.

Radiology. Artificial intelligence
Purpose To compare the image quality and diagnostic capability in detecting malignant liver tumors of low-dose CT (LDCT, 33% dose) with deep learning-based denoising (DLD) and standard-dose CT (SDCT, 100% dose) with model-based iterative reconstructi...

ASSOCIATION OF TESSELLATION DENSITY WITH PROGRESSION OF AXIAL LENGTH AND REFRACTION IN CHILDREN: An Artificial Intelligence-Assisted 4-Year Study.

Retina (Philadelphia, Pa.)
PURPOSE: To investigate fundus tessellation density (TD) and its association with axial length (AL) elongation and spherical equivalent (SE) progression in children.

Ultrafast Brain MRI with Deep Learning Reconstruction for Suspected Acute Ischemic Stroke.

Radiology
Background Deep learning (DL)-accelerated MRI can substantially reduce examination times. However, studies prospectively evaluating the diagnostic performance of DL-accelerated MRI reconstructions in acute suspected stroke are lacking. Purpose To inv...

Proctoring System Enables Safe Induction of Robotic Gastrectomy: Short-term Outcomes of the First 10 Cases.

Anticancer research
BACKGROUND/AIM: The Japan Society of Endoscopic Surgery (JSES) proctoring system was established to prevent serious pancreatic pressure injuries in Japan in 2019. To safely perform robotic gastrectomy (RG) in our hospital, which has no experience in ...