AIMC Topic: Female

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Artificial intelligence-assisted RNA-binding protein signature for prognostic stratification and therapeutic guidance in breast cancer.

Frontiers in immunology
BACKGROUND: Breast cancer is the most common malignancy in women globally, with significant heterogeneity affecting prognosis and treatment. RNA-binding proteins play vital roles in tumor progression, yet their prognostic potential remains unclear. T...

The Use of an Artificial Intelligence Platform OpenEvidence to Augment Clinical Decision-Making for Primary Care Physicians.

Journal of primary care & community health
BACKGROUND: Artificial intelligence (AI) platforms can potentially enhance clinical decision-making (CDM) in primary care settings. OpenEvidence (OE), an AI tool, draws from trusted sources to generate evidence-based medicine (EBM) recommendations to...

Influence of artificial intelligence on ophthalmologists' judgments in glaucoma.

PloS one
PURPOSE: To examine the influence of artificial intelligence (AI) on physicians' judgments regarding the presence and severity of glaucoma on fundus photographs in an online simulation system.

Deep learning-based acceleration of muscle water T2 mapping in patients with neuromuscular diseases by more than 50% - translating quantitative MRI from research to clinical routine.

PloS one
BACKGROUND: Quantitative muscle water T2 (T2w) mapping is regarded as a biomarker for disease activity and response to treatment in neuromuscular diseases (NMD). However, the implementation in clinical settings is limited due to long scanning times a...

Neuro-Modulation Analysis Based on Muscle Synergy Graph Neural Network in Human Locomotion.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
The coordination of muscles in human locomotion is commonly understood as the integration of motor modules known as muscle synergies. Recent research has delved into the adaptation of muscle synergies during the acquisition of new motor skills. Howev...

Quantitative MRI radiomics approach for evaluating muscular alteration in Crohn disease: development of a machine learning-nomogram composite diagnostic tool.

Abdominal radiology (New York)
BACKGROUND: Emerging evidence underscores smooth muscle hyperplasia and hypertrophy, rather than fibrosis, as the defining characteristics of fibrostenotic lesions in Crohn disease (CD). However, non-invasive methods for quantifying these muscular ch...

Reduction of the planning target volume with daily online adaptive radiotherapy in bladder cancer.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
INTRODUCTION: External radiation therapy for bladder cancer requires large planning target volumes (PTVs) due to the daily anatomy of the bladder. Online adaptive radiotherapy (oART) can reduce the PTV by considering daily anatomical changes.

A Multi-Omics-Based Prognostic Model for Elderly Breast Cancer by Machine Learning: Insights From Hypoxia and Immunity of Tumor Microenvironment.

Clinical breast cancer
INTRODUCTION: Older adult breast cancer (OABC) patients (≥ 65 years) frequently experience poorer prognoses compared to younger adults, attributed to complex tumor biology and age-related factors. The present study employs a multiomics approach combi...

Changes in recreational drug use, reasons for those changes and their consequence during and after the COVID-19 pandemic in the UK.

Comprehensive psychiatry
Changes in drug use in the general population during the COVID-19 pandemic and their long-term consequences are not well understood. We employed natural language processing and machine learning to analyse a large dataset of self-reported rates of and...

Development and application of deep learning-based diagnostics for pathologic diagnosis of gastric endoscopic submucosal dissection specimens.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: Accurate diagnosis of ESD specimens is crucial for managing early gastric cancer. Identifying tumor areas in serially sectioned ESD specimens requires experience and is time-consuming. This study aimed to develop and evaluate a deep learn...