AIMC Topic: Feasibility Studies

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Is deep learning-enabled real-time personalized CT dosimetry feasible using only patient images as input?

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To propose a novel deep-learning based dosimetry method that allows quick and accurate estimation of organ doses for individual patients, using only their computed tomography (CT) images as input.

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 ...

A machine learning-based approach to predict energy layer for each field in spot-scanning proton arc therapy for lung cancer: A feasibility study.

Medical physics
BACKGROUND: Determining the optimal energy layer (EL) for each field, under considering both dose constraints and delivery efficiency, is crucial to promoting the development of proton arc therapy (PAT) technology.

Feasibility and acceptance of artificial intelligence-based diabetic retinopathy screening in Rwanda.

The British journal of ophthalmology
BACKGROUND: Evidence on the practical application of artificial intelligence (AI)-based diabetic retinopathy (DR) screening is needed.

Deploying Robot-Led Activities for People with Dementia at Aged Care Facilities: A Feasibility Study.

Journal of the American Medical Directors Association
OBJECTIVES: To explore the feasibility of deploying robot-led activities for people with dementia living in aged care facilities.

Deep learning-based super-resolution of structural brain MRI at 1.5 T: application to quantitative volume measurement.

Magma (New York, N.Y.)
OBJECTIVE: This study investigated the feasibility of using deep learning-based super-resolution (DL-SR) technique on low-resolution (LR) images to generate high-resolution (HR) MR images with the aim of scan time reduction. The efficacy of DL-SR was...

Deep learning-based detection of irreversible pulpitis in primary molars.

International journal of paediatric dentistry
BACKGROUND: Changes in healthy and inflamed pulp on periapical radiographs are traditionally so subtle that they may be imperceptible to human experts, limiting its potential use as an adjunct clinical diagnostic feature.

Artificial intelligence-based, semi-automated segmentation for the extraction of ultrasound-derived radiomics features in breast cancer: a prospective multicenter study.

La Radiologia medica
PURPOSE: To investigate the feasibility of an artificial intelligence (AI)-based semi-automated segmentation for the extraction of ultrasound (US)-derived radiomics features in the characterization of focal breast lesions (FBLs).