AIMC Topic: Female

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Paediatric nurses' perspectives on artificial intelligence applications: A cross-sectional study of concerns, literacy levels and attitudes.

Journal of advanced nursing
AIMS: This study aimed to explore the correlation between artificial intelligence (AI) literacy, AI anxiety and AI attitudes among paediatric nurses, as well as identify the influencing factors on paediatric nurses' AI attitudes.

Predicting the 28-day prognosis of acute-on-chronic liver failure patients based on machine learning.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: We aimed to establish a prognostic predictive model based on machine learning (ML) methods to predict the 28-day mortality of acute-on-chronic liver failure (ACLF) patients, and to evaluate treatment effectiveness.

Preoperative Contrast-Enhanced CT-Based Deep Learning Radiomics Model for Distinguishing Retroperitoneal Lipomas and Well‑Differentiated Liposarcomas.

Academic radiology
RATIONALE AND OBJECTIVES: To assess the efficacy of a preoperative contrast-enhanced CT (CECT)-based deep learning radiomics nomogram (DLRN) for predicting murine double minute 2 (MDM2) gene amplification as a means of distinguishing between retroper...

Evaluating artificial intelligence-enhanced digital urine cytology for bladder cancer diagnosis.

Cancer cytopathology
BACKGROUND: This study evaluated the diagnostic effectiveness of the AIxURO platform, an artificial intelligence-based tool, to support urine cytology for bladder cancer management, which typically requires experienced cytopathologists and substantia...

Combined deep learning and radiomics in pretreatment radiation esophagitis prediction for patients with esophageal cancer underwent volumetric modulated arc therapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To develop a combined radiomics and deep learning (DL) model in predicting radiation esophagitis (RE) of a grade ≥ 2 for patients with esophageal cancer (EC) underwent volumetric modulated arc therapy (VMAT) based on computed tomography (CT)...

Speech-based recognition and estimating severity of PTSD using machine learning.

Journal of affective disorders
BACKGROUND: Traditional methodologies for diagnosing post-traumatic stress disorder (PTSD) primarily rely on interviews, incurring considerable costs and lacking objective indices. Integrating biomarkers and machine learning techniques into this diag...

Comparing human evaluations of eyewitness statements to a machine learning classifier under pristine and suboptimal lineup administration procedures.

Cognition
Recent work highlights the ability of verbal machine learning classifiers to distinguish between accurate and inaccurate recognition memory decisions (Dobbins, 2022; Dobbins & Kantner, 2019; Seale-Carlisle, Grabman, & Dodson, 2022). Given the surge o...

Reliability assessment of leg length and angular alignment on manual reads versus artificial intelligence-generated lower extremity radiographic measurements.

Clinical imaging
PURPOSE: Leg length discrepancy (LLD) and lower extremity malalignment can lead to pain and osteoarthritis. A variety of radiographic parameters are used to assess LLD and alignment. A 510(k) FDA approved artificial intelligence (AI) software locates...

Deep learning analysis of serial digital breast tomosynthesis images in a prospective cohort of breast cancer patients who received neoadjuvant chemotherapy.

European journal of radiology
PURPOSE: Different imaging tools, including digital breast tomosynthesis (DBT), are frequently used for evaluating tumor response during neoadjuvant chemotherapy (NACT). This study aimed to explore whether using artificial intelligence (AI) for seria...

Development of a deep-learning model tailored for HER2 detection in breast cancer to aid pathologists in interpreting HER2-low cases.

Histopathology
AIMS: Over 50% of breast cancer cases are "Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC)", characterized by HER2 immunohistochemistry (IHC) scores of 1+ or 2+ alongside no amplification on fluorescence in situ hybridization (...