AIMC Topic: Deep Learning

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Toward efficient slide-level grading of liver biopsy via explainable deep learning framework.

Medical & biological engineering & computing
In the context of chronic liver diseases, where variability in progression necessitates early and precise diagnosis, this study addresses the limitations of traditional histological analysis and the shortcomings of existing deep learning approaches. ...

Graph-based deep learning for predictions on changes in microbiomes and biogas production in anaerobic digestion systems.

Water research
Anaerobic digestion (AD), which relies on a complex microbial consortium for efficient biogas generation, is a promising avenue for renewable energy production and organic waste treatment. However, understanding and optimising AD processes are challe...

Deep Learning for Predicting Difficulty in Radical Prostatectomy: A Novel Evaluation Scheme.

Urology
OBJECTIVE: To explore new metrics for assessing radical prostatectomy difficulty through a two-stage deep learning method from preoperative magnetic resonance imaging.

Using a Deep Learning Model to Predict Postoperative Visual Outcomes of Idiopathic Epiretinal Membrane Surgery.

American journal of ophthalmology
PURPOSE: This study assessed the performance of various deep learning models in predicting the postoperative outcomes of idiopathic epiretinal membrane (ERM) surgery based on preoperative optical coherence tomography (OCT) images.

Artificial intelligence in clinical genetics.

European journal of human genetics : EJHG
Artificial intelligence (AI) has been growing more powerful and accessible, and will increasingly impact many areas, including virtually all aspects of medicine and biomedical research. This review focuses on previous, current, and especially emergin...

MMFuncPhos: A Multi-Modal Learning Framework for Identifying Functional Phosphorylation Sites and Their Regulatory Types.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Protein phosphorylation plays a crucial role in regulating a wide range of biological processes, and its dysregulation is strongly linked to various diseases. While many phosphorylation sites have been identified so far, their functionality and regul...

Application of deep learning in automated localization and interpretation of coronary artery calcification in oncological PET/CT scans.

The international journal of cardiovascular imaging
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radia...