AIMC Topic: Female

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A nursing note-aware deep neural network for predicting mortality risk after hospital discharge.

International journal of nursing studies
BACKGROUND: ICU readmissions and post-discharge mortality pose significant challenges. Previous studies used EHRs and machine learning models, but mostly focused on structured data. Nursing records contain crucial unstructured information, but their ...

Risk prediction model of metabolic syndrome in perimenopausal women based on machine learning.

International journal of medical informatics
INTRODUCTION: Metabolic syndrome (MetS) is considered to be an important parameter of cardio-metabolic health and contributing to the development of atherosclerosis, type 2 diabetes. The incidence of MetS significantly increases in postmenopausal wom...

Development, evaluation and validation of machine learning models to predict hospitalizations of patients with coronary artery disease within the next 12 months.

International journal of medical informatics
BACKGROUND: Improved survival of patients after acute coronary syndromes, population growth, and overall life expectancy rise have led to a significant increase in the proportion of patients with stable coronary artery disease (CAD), creating a signi...

Children's animistic beliefs toward a humanoid robot and other objects.

Journal of experimental child psychology
This study examined children's beliefs about a humanoid robot by examining their behavioral and verbal responses. We investigated whether 3- and 5-year-old children would treat the humanoid robot gently along with other objects and tools with and wit...

A machine learning predictive model for recurrence of resected distal cholangiocarcinoma: Development and validation of predictive model using artificial intelligence.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
INTRODUCTION: Distal Cholangiocarcinoma (dCCA) represents a challenge in hepatobiliary oncology, that requires nuanced post-resection prognostic modeling. Conventional staging criteria may oversimplify dCCA complexities, prompting the exploration of ...

Artificial intelligence-based, semi-automated segmentation for the extraction of ultrasound-derived radiomics features in breast cancer: a prospective multicenter study.

La Radiologia medica
PURPOSE: To investigate the feasibility of an artificial intelligence (AI)-based semi-automated segmentation for the extraction of ultrasound (US)-derived radiomics features in the characterization of focal breast lesions (FBLs).

Human Activity Recognition Algorithm with Physiological and Inertial Signals Fusion: Photoplethysmography, Electrodermal Activity, and Accelerometry.

Sensors (Basel, Switzerland)
Inertial signals are the most widely used signals in human activity recognition (HAR) applications, and extensive research has been performed on developing HAR classifiers using accelerometer and gyroscope data. This study aimed to investigate the po...

A Review of Artificial Intelligence in Breast Imaging.

Tomography (Ann Arbor, Mich.)
With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging...