AIMC Topic: Deep Learning

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Automatic ovarian follicle detection using object detection models.

Scientific reports
Ovaries are of paramount importance in reproduction as they produce female gametes through a complex developmental process known as folliculogenesis. In the prospect of better understanding the mechanisms of folliculogenesis and of developing novel p...

Classification of cervical cancer using Dense CapsNet with Seg-UNet and denoising autoencoders.

Scientific reports
Cervical cancer is one of the deadly diseases that affects women, which requires periodic examinations to identify and treat any cancerous tumors at a preliminary stage. The most prevalent examination tool for cervical cancer prompt identification is...

Predicting patients' sentiments about medications using artificial intelligence techniques.

Scientific reports
The increasing development of technology has led to the increase of digital data in various fields, such as medication-related texts. Sentiment Analysis (SA) in medication is essential to give clinicians insights into patients' feedback about the tre...

A deep learning-based ADRPPA algorithm for the prediction of diabetic retinopathy progression.

Scientific reports
As an alternative to assessments performed by human experts, artificial intelligence (AI) is currently being used for screening fundus images and monitoring diabetic retinopathy (DR). Although AI models can provide quasi-clinician diagnoses, they rar...

Deep-learning-based extraction of circle of Willis topology with anatomical priors.

Scientific reports
The circle of Willis (CoW) is a circular arrangement of arteries in the human brain, exhibiting significant anatomical variability. The CoW is extensively studied in relation to neurovascular pathologies, with certain anatomical variants previously l...

On the improvement of schizophrenia detection with optical coherence tomography data using deep neural networks and aggregation functions.

Scientific reports
Schizophrenia is a serious mental disorder with a complex neurobiological background and a well-defined psychopathological picture. Despite many efforts, a definitive disease biomarker has still not been identified. One of the promising candidates fo...

DeepGOMeta for functional insights into microbial communities using deep learning-based protein function prediction.

Scientific reports
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Tradi...

Optimizing VGG16 deep learning model with enhanced hunger games search for logo classification.

Scientific reports
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. Howev...

Attention-guided convolutional network for bias-mitigated and interpretable oral lesion classification.

Scientific reports
Accurate diagnosis of oral lesions, early indicators of oral cancer, is a complex clinical challenge. Recent advances in deep learning have demonstrated potential in supporting clinical decisions. This paper introduces a deep learning model for class...

Deep learning on CT scans to predict checkpoint inhibitor treatment outcomes in advanced melanoma.

Scientific reports
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the...