AIMC Topic: Middle Aged

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Predicting the cognitive impairment with multimodal ophthalmic imaging and artificial neural network for community screening.

The British journal of ophthalmology
BACKGROUND/AIMS: To investigate the comprehensive prediction ability for cognitive impairment in a general elder population using the combination of the multimodal ophthalmic imaging and artificial neural networks.

Using Machine Learning Models to Predict Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.

JCO clinical cancer informatics
PURPOSE: Neoadjuvant chemotherapy (NAC) is increasingly used in breast cancer. Predictive modeling is useful in predicting pathologic complete response (pCR) to NAC. We test machine learning (ML) models to predict pCR in breast cancer and explore met...

Classifying age from medial clavicle using a 30-year threshold: An image analysis based approach.

PloS one
This study aimed to develop image-analysis-based classification models for distinguishing individuals younger and older than 30 using the medial clavicle. We extracted 2D images of the medial clavicle from multi-slice computed tomography (MSCT) scans...

Effectiveness of Comprehensive Video Datasets: Toward the Development of an Artificial Intelligence Model for Ultrasonography-Based Severity Diagnosis of Carpal Tunnel Syndrome.

Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
OBJECTIVES: Advances in diagnosing carpal tunnel syndrome (CTS) using ultrasonography (US) and artificial intelligence (AI) aim to replace nerve conduction studies. However, a method for accurate severity diagnosis remains unachieved. We explored the...

Analysis of the relationships between interferon-stimulated genes and anti-SSA/Ro 60 antibodies in primary Sjögren's syndrome patients via multiomics and machine learning methods.

International immunopharmacology
BACKGROUND: Primary Sjögren's syndrome (pSS) is a chronic systemic autoimmune disease characterized by lymphocyte infiltration of the exocrine glands. Interferon-stimulated genes (ISGs) are often upregulated in patients with pSS, and anti-SSA/Ro 60 a...

Urine Analysed by FTIR, Chemometrics and Machine Learning Methods in Determination Spectroscopy Marker of Prostate Cancer in Urine.

Journal of biophotonics
Prostate-specific antigen (PSA) is the most commonly used marker of prostate cancer. However, nearly 25% of men with elevated PSA levels do not have cancer and nearly 20% of patients with prostate cancer have normal serum PSA levels. Therefore, in th...

Interpretable Machine Learning Algorithms Identify Inetetamab-Mediated Metabolic Signatures and Biomarkers in Treating Breast Cancer.

Journal of clinical laboratory analysis
BACKGROUND: HER2-positive breast cancer (BC), a highly aggressive malignancy, has been treated with the targeted therapy inetetamab for metastatic cases. Inetetamab (Cipterbin) is a recently approved targeted therapy for HER2-positive metastatic BC, ...

A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway.

BMC cancer
BACKGROUND: Exosome small RNAs are believed to be involved in the pathogenesis of cancer, but their role in breast cancer is still unclear. This study utilized machine learning models to screen for key exosome small RNAs and analyzed and validated th...