AIMC Topic: Middle Aged

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A novel radiomics approach for predicting TACE outcomes in hepatocellular carcinoma patients using deep learning for multi-organ segmentation.

Scientific reports
Transarterial chemoembolization (TACE) represent the standard of therapy for non-operative hepatocellular carcinoma (HCC), while prediction of long term treatment outcomes is a complex and multifactorial task. In this study, we present a novel machin...

A machine learning model predicts stroke associated with blood cadmium level.

Scientific reports
Stroke is the leading cause of death and disability worldwide. Cadmium is a prevalent environmental toxicant that may contribute to cardiovascular disease, including stroke. We aimed to build an effective and interpretable machine learning (ML) model...

Identifying significant structural factors associated with knee pain severity in patients with osteoarthritis using machine learning.

Scientific reports
Our main objective was to use machine learning methods to identify significant structural factors associated with pain severity in knee osteoarthritis patients. Additionally, we assessed the potential of various classes of imaging data using machine ...

Individual characteristics outperform resting-state fMRI for the prediction of behavioral phenotypes.

Communications biology
In this study, we aimed to compare imaging-based features of brain function, measured by resting-state fMRI (rsfMRI), with individual characteristics such as age, gender, and total intracranial volume to predict behavioral measures. We developed a ma...

Deep learning model integrating cfDNA methylation and fragment size profiles for lung cancer diagnosis.

Scientific reports
Detecting aberrant cell-free DNA (cfDNA) methylation is a promising strategy for lung cancer diagnosis. In this study, our aim is to identify methylation markers to distinguish patients with lung cancer from healthy individuals. Additionally, we soug...

AI-based histopathology image analysis reveals a distinct subset of endometrial cancers.

Nature communications
Endometrial cancer (EC) has four molecular subtypes with strong prognostic value and therapeutic implications. The most common subtype (NSMP; No Specific Molecular Profile) is assigned after exclusion of the defining features of the other three molec...

Evaluating the prognostic value of tumor deposits in non-metastatic lymph node-positive colon adenocarcinoma using Cox regression and machine learning.

International journal of colorectal disease
BACKGROUND: The 8th AJCC TNM staging for non-metastatic lymph node-positive colon adenocarcinoma patients(NMLP-CA) stages solely by lymph node status, irrespective of the positivity of tumor deposits (TD). This study uses machine learning and Cox reg...

Optimizing Nursing Productivity: Exploring the Role of Artificial Intelligence, Technology Integration, Competencies, and Leadership.

Journal of nursing management
BACKGROUND: In the rapidly evolving healthcare management landscape, technology integration and artificial intelligence utilization play pivotal roles in shaping employee productivity. This research investigates these dynamics within Riyadh Province,...

The circadian syndrome is a better predictor for psoriasis than the metabolic syndrome via an explainable machine learning method - the NHANES survey during 2005-2006 and 2009-2014.

Frontiers in endocrinology
OBJECTIVE: To explore the association between circadian syndrome (CircS) and Metabolic Syndrome (MetS) with psoriasis. Compare the performance of MetS and CircS in predicting psoriasis.