AIMC Topic: Predictive Value of Tests
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Predicting Recurrence in Locally Advanced Rectal Cancer Using Multitask Deep Learning and Multimodal MRI.
Radiology. Imaging cancer
May 1, 2025
Purpose To develop and validate a deep multitask network, MultiRecNet, for fully automatic prediction of disease-free survival (DFS) in patients with neoadjuvant chemoradiotherapy (nCRT)-treated locally advanced rectal cancer (LARC). Materials and Me...
Artificial intelligence software in biomedical imaging: a pharmaceutical perspective on radiology and contrast-enhanced ultrasound applications.
Clinical and experimental rheumatology
May 1, 2025
Artificial intelligence (AI) is rapidly transforming radiology, with over 200 CE-marked products in the EU and more than 750 AI-based devices authorised by the FDA in the US, mainly used for x-ray, CT, MRI, and ultrasound imaging. Despite regulatory ...
Expert consensus document on artificial intelligence of the Italian Society of Cardiology.
Journal of cardiovascular medicine (Hagerstown, Md.)
May 1, 2025
Artificial intelligence (AI), a branch of computer science focused on developing algorithms that replicate intelligent behaviour, has recently been used in patients management by enhancing diagnostic and prognostic capabilities of various resources s...
Light Bladder Net: Non-invasive Bladder Cancer Prediction by Weighted Deep Learning Approaches and Graphical Data Transformation.
Anticancer research
May 1, 2025
BACKGROUND/AIM: Bladder cancer (BCa) is associated with high recurrence rates, emphasizing the importance of early and accurate detection. This study aimed to develop a lightweight and fast deep learning model, Light-Bladder-Net (LBN), for non-invasi...
Artificial intelligence and machine learning in ocular oncology, retinoblastoma (ArMOR).
Indian journal of ophthalmology
May 1, 2025
PURPOSE: To test the accuracy of a trained artificial intelligence and machine learning (AI/ML) model in the diagnosis and grouping of intraocular retinoblastoma (iRB) based on the International Classification of Retinoblastoma (ICRB) in a larger coh...
Enhancing bone metastasis prediction in prostate cancer using quantitative mpMRI features, ISUP grade and PSA density: a machine learning approach.
Abdominal radiology (New York)
May 1, 2025
PURPOSE: Bone metastasis is a critical complication in prostate cancer, significantly impacting patient prognosis and quality of life. This study aims to enhance bone metastasis prediction using machine learning (ML) techniques by integrating dynamic...
Non-invasive physiological assessment of intermediate coronary stenoses from plain angiography through artificial intelligence: the STARFLOW system.
European heart journal. Quality of care & clinical outcomes
May 1, 2025
BACKGROUND: Despite evidence supporting use of fractional flow reserve (FFR) and instantaneous waves-free ratio (iFR) to improve outcome of patients undergoing coronary angiography (CA) and percutaneous coronary intervention, such techniques are stil...
Predicting postoperative prognosis in clear cell renal cell carcinoma using a multiphase CT-based deep learning model.
Abdominal radiology (New York)
May 1, 2025
BACKGROUND: Some clinicopathological risk stratification systems (CRSSs) such as the leibovich score have been used to predict the postoperative prognosis of patients with clear cell renal cell carcinoma (ccRCC), but there are no reliable noninvasive...
Machine Learning for Predicting Stillbirth: A Systematic Review.
Reproductive sciences (Thousand Oaks, Calif.)
May 1, 2025
Stillbirth is a major global issue, with over 5 million cases each year. The multifactorial nature of stillbirth makes it difficult to predict. Artificial intelligence (AI) and machine learning (ML) have the potential to enhance clinical decision-mak...
Concomitant Procedures, Black Race, Male Sex, and General Anesthesia Show Fair Predictive Value for Prolonged Rotator Cuff Repair Operative Time: Analysis of the National Quality Improvement Program Database Using Machine Learning.
Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association
May 1, 2025
PURPOSE: To develop machine learning models using the American College of Surgeons National Quality Improvement Program (ACS-NSQIP) database to predict prolonged operative time (POT) for rotator cuff repair (RCR), as well as use the trained machine l...
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