AIMC Topic: Aged

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Constructing a Classification Model for Cervical Cancer Tumor Tissue and Normal Tissue Based on CT Radiomics.

Technology in cancer research & treatment
This study aimed to develop an automated classification framework for distinguishing between cervical cancer tumor and normal uterine tissue, leveraging CT images for radiomics feature extraction. We retrospectively analyzed CT images from 117 cervic...

Navigating the Adoption Maze: Evolutionary Dynamics of Stakeholder Behavior in AI-Driven Elderly Care Solutions.

Inquiry : a journal of medical care organization, provision and financing
In the face of a rapidly aging population and the increasing demand for elderly care, the adoption of artificial intelligence (AI) in healthcare products has emerged as a promising solution to enhance service delivery. This paper investigates the beh...

The effectiveness of deep learning model in differentiating benign and malignant pulmonary nodules on spiral CT.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Pulmonary nodule, one of the most common clinical phenomena, is an irregular circular lesion with a diameter of ⩽ 3 cm in the lungs, which can be classified as benign or malignant. Differentiating benign and malignant pulmonary nodules ha...

Performance and Reliability Evaluation of an Automated Bone-Conduction Audiometry Using Machine Learning.

Trends in hearing
To date, pure-tone audiometry remains the gold standard for clinical auditory testing. However, pure-tone audiometry is time-consuming and only provides a discrete estimate of hearing acuity. Here, we aim to address these two main drawbacks by develo...

An Artificial Intelligence-assisted Diagnostic System Improves Upper Urine Tract Cytology Diagnosis.

In vivo (Athens, Greece)
BACKGROUND/AIM: To evaluate efficacy of the AIxURO system, a deep learning-based artificial intelligence (AI) tool, in enhancing the accuracy and reliability of urine cytology for diagnosing upper urinary tract cancers.

A neural network model for predicting the effectiveness of treatment in patients with neovascular glaucoma associated with diabetes mellitus.

Romanian journal of ophthalmology
INTRODUCTION: The study hypothesizes that neural networks can be an effective tool for predicting treatment outcomes in patients with diabetic neovascular glaucoma (NVG), considering not only baseline intraocular pressure (IOP) values but also inflam...

Importance of Serum Albumin in Deep Learning-Based Prediction of Cognitive Function Data in the Aged Using a Basic Blood Test.

Advances in experimental medicine and biology
BACKGROUND: Recently, a method using deep learning has been developed to estimate the risk of developing dementia. This method uses general blood test data from routine health examinations that reveal lifestyle-related diseases, which can lead to vas...

Machine learning identifies a 5-serum cytokine panel for the early detection of chronic atrophy gastritis patients.

Cancer biomarkers : section A of Disease markers
BACKGROUND: Chronic atrophy gastritis (CAG) is a high-risk pre-cancerous lesion for gastric cancer (GC). The early and accurate detection and discrimination of CAG from benign forms of gastritis (e.g. chronic superficial gastritis, CSG) is critical f...