AIMC Topic: Aged

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Assessment of drug induced hyperuricemia and gout risk using the FDA adverse event reporting system.

Scientific reports
Hyperuricemia, the key pathological basis of gout, is increasingly prevalent worldwide. While lifestyle factors contribute, various medications also play a role. However, their specific risks and mechanisms remain inadequately studied. Disproportiona...

Combining multi-parametric MRI radiomics features with tumor abnormal protein to construct a machine learning-based predictive model for prostate cancer.

Scientific reports
This study aims to investigate the diagnostic value of integrating multi-parametric magnetic resonance imaging (mpMRI) radiomic features with tumor abnormal protein (TAP) and clinical characteristics for diagnosing prostate cancer. A cohort of 109 pa...

Developing transferable and universal IR biomarkers for intraoperative colorectal cancer diagnosis via FTIR spectroscopy.

Scientific reports
Histological staining has long been the gold standard for cancer detection, but it is limited by subjectivity and delayed results. Fourier Transform Infrared Spectroscopy (FTIR) has emerged as a promising technique, offering the advantages of objecti...

The impact of intelligent devices utilization on household medical expenditure of older adults in China.

Scientific reports
With the rapid development of artificial intelligence, there is an increasing utilization of intelligent devices by older adults. The relationship between the utilization of intelligent devices and household medical expenditure has garnered widesprea...

Classifying and diagnosing Alzheimer's disease with deep learning using 6735 brain MRI images.

Scientific reports
Traditional diagnostic methods for Alzheimer's disease often suffer from low accuracy and lengthy processing times, delaying crucial interventions and patient care. Deep convolutional neural networks trained on MRI data can enhance diagnostic precisi...

Cervical cancer prediction using machine learning models based on routine blood analysis.

Scientific reports
Cervical cancer (CC) is the fourth most common cancer among women globally. The key to preventing and treating CC is early detection, diagnosis, and treatment. This study aimed to develop an interpretable model for predicting CC risk using routine bl...

Machine learning model and hemoglobin to red cell distribution width ratio evaluates all-cause mortality in pulmonary embolism.

Scientific reports
The ratio of hemoglobin (Hb) to red blood cell distribution width (RDW), known as HRR, functions as an innovative indicator related to prognosis. However, whether HRR can predict the mortality for pulmonary embolism (PE) patients remains ambiguous. A...

Using graph machine learning to identify functioning in patients with low back pain in terms of ICF.

Scientific reports
As a comprehensive perspective on functioning is useful in patient assessments, the WHO developed the International Classification of Functioning, Disability, and Health (ICF) to provide a standardized terminology and framework for describing and cla...

A ubiquitous and interoperable deep learning model for automatic detection of pleomorphic gastroesophageal lesions.

Scientific reports
In recent years, artificial intelligence (AI) has been widely explored to enhance capsule endoscopy (CE), with the goal of improving the efficiency of the reading process. While most AI models have been developed for small bowel and colon analysis, t...

Comparative study of five-year cervical cancer cause-specific survival prediction models based on SEER data.

Scientific reports
Cervical cancer (CC) is a major cause of mortality in women, with stagnant survival rates, highlighting the need for improved prognostic models. This study aims to develop and compare machine learning models for predicting five-year cause-specific su...