AIMC Topic: Feasibility Studies

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Assessing the risk of problem gambling among lottery loyalty program members: A machine learning approach.

Addictive behaviors
BACKGROUND AND AIMS: Lottery gambling is a relatively benign form of gambling. Nonetheless, individuals with gambling problems may engage in lottery play and/or play the lottery exclusively. Lottery loyalty programs have data that could be used to sc...

Feasibility of human ethomic biomarkers for the diagnosis and monitoring of hip osteoarthritis.

Journal of biomechanics
Radiographic imaging is typically used to diagnose osteoarthritis (OA). However, patients would typically be sent for imaging after they present to a physician because of joint pain. By this time, the condition is likely irreversible. This study aims...

A machine learning toolkit assisted approach for IMRT fluence map optimization: feasibility and advantages.

Biomedical physics & engineering express
. Traditional machine learning (ML) and deep learning (DL) applications in treatment planning rely on complex model architectures and large, high-quality training datasets. However, they cannot fully replace the conventional optimization process. Thi...

Breaking down data silos across companies to train genome-wide predictions: A feasibility study in wheat.

Plant biotechnology journal
Big data, combined with artificial intelligence (AI) techniques, holds the potential to significantly enhance the accuracy of genome-wide predictions. Motivated by the success reported for wheat hybrids, we extended the scope to inbred lines by integ...

Fully Automated Online Adaptive Radiation Therapy Decision-Making for Cervical Cancer Using Artificial Intelligence.

International journal of radiation oncology, biology, physics
BACKGROUND: Interfraction variations during radiation therapy pose a challenge for patients with cervical cancer, highlighting the benefits of online adaptive radiation therapy (oART). However, adaptation decisions rely on subjective image reviews by...

Generating Artificial Patients With Reliable Clinical Characteristics Using a Geometry-Based Variational Autoencoder: Proof-of-Concept Feasibility Study.

Journal of medical Internet research
BACKGROUND: Artificial patient technology could transform health care by accelerating diagnosis, treatment, and mapping clinical pathways. Deep learning methods for generating artificial data in health care include data augmentation by variational au...

Use of Open-Source Large Language Models for Automatic Synthesis of the Entire Imaging Medical Records of Patients: A Feasibility Study.

Tomography (Ann Arbor, Mich.)
BACKGROUND/OBJECTIVES: Reviewing the entire history of imaging exams of a single patient's records is an essential step in clinical practice, but it is time and resource consuming, with potential negative effects on workflow and on the quality of med...

Prospective multicenter external validation of the rib fracture frailty index.

The journal of trauma and acute care surgery
BACKGROUND: The Rib Fracture Frailty (RFF) Index is an internally validated machine learning-based risk assessment tool for adult patients with rib fractures that requires minimal provider entry. Existing frailty risk scores have yet to undergo head-...

Oxidative Stress Markers and Prediction of Severity With a Machine Learning Approach in Hospitalized Patients With COVID-19 and Severe Lung Disease: Observational, Retrospective, Single-Center Feasibility Study.

JMIR formative research
BACKGROUND: Serious pulmonary pathologies of infectious, viral, or bacterial origin are accompanied by inflammation and an increase in oxidative stress (OS). In these situations, biological measurements of OS are technically difficult to obtain, and ...