AIMC Topic: Middle Aged

Clear Filters Showing 7131 to 7140 of 17155 articles

A Deep Learning Model for Automatically Quantifying the Anterior Segment in Ultrasound Biomicroscopy Images of Implantable Collamer Lens Candidates.

Ultrasound in medicine & biology
OBJECTIVE: This study aimed to develop and evaluate a deep learning-based model that could automatically measure anterior segment (AS) parameters on preoperative ultrasound biomicroscopy (UBM) images of implantable Collamer lens (ICL) surgery candida...

Development and Validation of Artificial Intelligence-Based Algorithms for Predicting the Segments Debulked by Rotational Atherectomy Using Intravascular Ultrasound Images.

The American journal of cardiology
We develop and evaluate an artificial intelligence (AI)-based algorithm that uses pre-rotation atherectomy (RA) intravascular ultrasound (IVUS) images to automatically predict regions debulked by RA. A total of 2106 IVUS cross-sections from 60 patien...

A Nordic survey on artificial intelligence in the radiography profession - Is the profession ready for a culture change?

Radiography (London, England : 1995)
INTRODUCTION: The impact of artificial intelligence (AI) on the radiography profession remains uncertain. Although AI has been increasingly used in clinical radiography, the perspectives of the radiography professionals in Nordic countries have yet t...

Machine learning-based preoperative analytics for the prediction of anastomotic leakage in colorectal surgery: a swiss pilot study.

Surgical endoscopy
BACKGROUND: Anastomotic leakage (AL), a severe complication following colorectal surgery, arises from defects at the anastomosis site. This study evaluates the feasibility of predicting AL using machine learning (ML) algorithms based on preoperative ...

Person-specific and pooled prediction models for binge eating, alcohol use and binge drinking in bulimia nervosa and alcohol use disorder.

Psychological medicine
BACKGROUND: Machine learning could predict binge behavior and help develop treatments for bulimia nervosa (BN) and alcohol use disorder (AUD). Therefore, this study evaluates person-specific and pooled prediction models for binge eating (BE), alcohol...

Telephone follow-up based on artificial intelligence technology among hypertension patients: Reliability study.

Journal of clinical hypertension (Greenwich, Conn.)
Artificial intelligence (AI) telephone is reliable for the follow-up and management of hypertensives. It takes less time and is equivalent to manual follow-up to a high degree. We conducted a reliability study to evaluate the efficiency of AI telepho...

Machine learning models for predicting early hemorrhage progression in traumatic brain injury.

Scientific reports
This study explores the progression of intracerebral hemorrhage (ICH) in patients with mild to moderate traumatic brain injury (TBI). It aims to predict the risk of ICH progression using initial CT scans and identify clinical factors associated with ...

A deep learning model for brain segmentation across pediatric and adult populations.

Scientific reports
Automated quantification of brain tissues on MR images has greatly contributed to the diagnosis and follow-up of neurological pathologies across various life stages. However, existing solutions are specifically designed for certain age ranges, limiti...

Artificial intelligence enables precision diagnosis of cervical cytology grades and cervical cancer.

Nature communications
Cervical cancer is a significant global health issue, its prevalence and prognosis highlighting the importance of early screening for effective prevention. This research aimed to create and validate an artificial intelligence cervical cancer screenin...