AIMC Topic: Prospective Studies
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Artificial intelligence solution to accelerate the acquisition of MRI images: Impact on the therapeutic care in oncology in radiology and radiotherapy departments.
Cancer radiotherapie : journal de la Societe francaise de radiotherapie oncologique
Jun 11, 2024
PURPOSE: MRI is essential in the management of brain tumours. However, long waiting times reduce patient accessibility. Reducing acquisition time could improve access but at the cost of spatial resolution and diagnostic quality. A commercially availa...
Prediction model of preeclampsia using machine learning based methods: a population based cohort study in China.
Frontiers in endocrinology
Jun 11, 2024
INTRODUCTION: Preeclampsia is a disease with an unknown pathogenesis and is one of the leading causes of maternal and perinatal morbidity. At present, early identification of high-risk groups for preeclampsia and timely intervention with aspirin is a...
Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.
Journal of magnetic resonance imaging : JMRI
Jun 10, 2024
BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative.
Predicting the onset of overweight in Chinese high school students: a machine-learning approach in a one-year prospective cohort study.
Endocrine
Jun 10, 2024
OBJECTIVE: This study aimed to develop and evaluate machine-learning models for predicting the onset of overweight in adolescents aged 14‒17, utilizing easily collectible personal information.
Re-evaluation of the prospective risk analysis for artificial-intelligence driven cone beam computed tomography-based online adaptive radiotherapy after one year of clinical experience.
Zeitschrift fur medizinische Physik
Jun 8, 2024
Cone-beam computed tomography (CBCT)-based online adaptation is increasingly being introduced into many clinics. Upon implementation of a new treatment technique, a prospective risk analysis is required and enhances workflow safety. We conducted a ri...
Development and external validation of a logistic and a penalized logistic model using machine-learning techniques to predict suicide attempts: A multicenter prospective cohort study in Korea.
Journal of psychiatric research
Jun 6, 2024
Despite previous efforts to build statistical models for predicting the risk of suicidal behavior using machine-learning analysis, a high-accuracy model can lead to overfitting. Furthermore, internal validation cannot completely address this problem....
Deep learning models for thyroid nodules diagnosis of fine-needle aspiration biopsy: a retrospective, prospective, multicentre study in China.
The Lancet. Digital health
Jun 6, 2024
BACKGROUND: Accurately distinguishing between malignant and benign thyroid nodules through fine-needle aspiration cytopathology is crucial for appropriate therapeutic intervention. However, cytopathologic diagnosis is time consuming and hindered by t...
Effect of Ambient Voice Technology, Natural Language Processing, and Artificial Intelligence on the Patient-Physician Relationship.
Applied clinical informatics
Jun 4, 2024
BACKGROUND: The method of documentation during a clinical encounter may affect the patient-physician relationship.
Assessing the Impact of an Artificial Intelligence-Based Model for Intracranial Aneurysm Detection in CT Angiography on Patient Diagnosis and Outcomes (IDEAL Study)-a protocol for a multicenter, double-blinded randomized controlled trial.
Trials
Jun 4, 2024
BACKGROUND: This multicenter, double-blinded, randomized controlled trial (RCT) aims to assess the impact of an artificial intelligence (AI)-based model on the efficacy of intracranial aneurysm detection in CT angiography (CTA) and its influence on p...
Phenotype clustering of hospitalized high-risk patients with COVID-19 - a machine learning approach within the multicentre, multinational PCHF-COVICAV registry.
Cardiology journal
Jun 4, 2024
IMTRODUCTION: The high-risk population of patients with cardiovascular (CV) disease or risk factors (RF) suffering from COVID-19 is heterogeneous. Several predictors for impaired prognosis have been identified. However, with machine learning (ML) app...
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