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Predicting intermediate-risk prostate cancer using machine learning.
International urology and nephrology
Jan 3, 2025
PURPOSES: Intermediate-risk prostate cancer (IR PCa) is the most common risk group for localized prostate cancer. This study aimed to develop a machine learning (ML) model that utilizes biopsy predictors to estimate the probability of IR PCa and asse...
The use of machine learning for the prediction of response to follow-up in spine registries.
International journal of medical informatics
Jan 3, 2025
BACKGROUND: One of the main challenges in the maintenance of registries is to keep a high follow-up rate and a reliable strategy to limit dropout is currently lacking. Aim of this study was to utilize machine learning (ML) models to highlight the cha...
The Adelaide Score: prospective implementation of an artificial intelligence system to improve hospital and cost efficiency.
ANZ journal of surgery
Jan 3, 2025
BACKGROUND: The Adelaide Score is an artificial intelligence system that integrates objective vital signs and laboratory tests to predict likelihood of hospital discharge.
Deep learning-based pelvimetry in pelvic MRI volumes for pre-operative difficulty assessment of total mesorectal excision.
Surgical endoscopy
Jan 3, 2025
BACKGROUND: Specific pelvic bone dimensions have been identified as predictors of total mesorectal excision (TME) difficulty and outcomes. However, manual measurement of these dimensions (pelvimetry) is labor intensive and thus, anatomic criteria are...
Application of machine learning algorithms in an epidemiologic study of mortality.
Annals of epidemiology
Jan 3, 2025
PURPOSE: Epidemiologic studies are important in assessing risk factors of mortality. Machine learning (ML) is efficient in analyzing multidimensional data to unravel dependencies between risk factors and health outcomes.
Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.
Pharmacotherapy
Jan 3, 2025
BACKGROUND: Fluid overload (FO) in the intensive care unit (ICU) is common, serious, and may be preventable. Intravenous medications (including administered volume) are a primary cause for FO but are challenging to evaluate as a FO predictor given th...
Dual-Stage AI Model for Enhanced CT Imaging: Precision Segmentation of Kidney and Tumors.
Tomography (Ann Arbor, Mich.)
Jan 3, 2025
OBJECTIVES: Accurate kidney and tumor segmentation of computed tomography (CT) scans is vital for diagnosis and treatment, but manual methods are time-consuming and inconsistent, highlighting the value of AI automation. This study develops a fully au...
Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis.
Current oncology (Toronto, Ont.)
Jan 3, 2025
Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic resonance imaging (MRI) of the upper abdomen with a slice thickness below 5 mm suffers from high image noise and blurring. The purpose of this prospective ...
Comparison of AI applications and anesthesiologist's anesthesia method choices.
BMC anesthesiology
Jan 3, 2025
BACKGROUND: In medicine, Artificial intelligence has begun to be utilized in nearly every domain, from medical devices to the interpretation of imaging studies. There is still a need for more experience and more studies related to the comprehensive u...
Psychotropic medications: a descriptive study of prescription trends in Tabriz, Iran, 2021-2022.
BMC psychiatry
Jan 3, 2025
INTRODUCTION: Mental disorders, such as anxiety and depression, significantly impacted global populations in 2019 and 2020, with COVID-19 causing a surge in prevalence. They affect 13.4% of the people worldwide, and 21% of Iranians have experienced t...
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