AIMC Topic: Female

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Deep learning-based quantitative analysis of glomerular morphology in IgA nephropathy whole slide images and its prognostic implications.

Scientific reports
Kidney pathology of immunoglobulin A nephropathy (IgAN), which is the key finding of both diagnosis and risk stratification, involves labor-intensive manual interpretation as well as unavoidable interpreter-dependent variabilities. We propose artific...

Cohesive data analysis for the identification of prognostic hub genes and significant pathways associated with HER2 + and TN breast cancer types.

Scientific reports
Breast cancer is the most prevalent and lethal form of cancer being the utmost common medical concern of women. Breast cancer etiology implicates numerous cellular protein receptors such as estrogen receptors (ER), progesterone receptors (PR), and hu...

A novel XAI framework for explainable AI-ECG using generative counterfactual XAI (GCX).

Scientific reports
Generative Counterfactual Explainable Artificial Intelligence (XAI) offers a novel approach to understanding how AI models interpret electrocardiograms (ECGs). Traditional explanation methods focus on highlighting important ECG segments but often fai...

The effectiveness of explainable AI on human factors in trust models.

Scientific reports
Explainable AI has garnered significant traction in science communication research. Prior empirical studies have firmly established that explainable AI communication could improve trust in AI and that trust in AI engineers was argued to be an under-e...

Listening deeper: neural networks unravel acoustic features in preterm infant crying.

Scientific reports
Early infant crying provides critical insights into neurodevelopment, with atypical acoustic features linked to conditions such as preterm birth. However, previous studies have focused on limited and specific acoustic features, hindering a more compr...

A deep learning model for early diagnosis of alzheimer's disease combined with 3D CNN and video Swin transformer.

Scientific reports
Alzheimer's disease (AD) constitutes a neurodegenerative disorder predominantly observed in the geriatric population. If AD can be diagnosed early, both in terms of prevention and treatment, it is very beneficial to patients. Therefore, our team prop...

Deep molecular profiling of synovial biopsies in the STRAP trial identifies signatures predictive of treatment response to biologic therapies in rheumatoid arthritis.

Nature communications
Approximately 40% of patients with rheumatoid arthritis do not respond to individual biologic therapies, while biomarkers predictive of treatment response are lacking. Here we analyse RNA-sequencing (RNA-Seq) of pre-treatment synovial tissue from the...

Enhancing breast cancer diagnosis through machine learning algorithms.

Scientific reports
Among the most important health concerns in the world, and the number one cause of death in women, is breast cancer. Bearing in mind that there are more than 100 types of cancer, each presenting different symptoms, its early detection is indeed a big...

Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension.

Scientific reports
To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressive craniectomy (DC) in patients with severe traumatic brain injury (TBI) and to demonstrate its pote...

Modeling student satisfaction in online learning using random forest.

Scientific reports
The rapid expansion of online education has intensified the need to investigate the multifactorial determinants of university students' satisfaction with digital learning platforms. While prior studies have often examined technical or pedagogical com...