AIMC Topic: Deep Learning

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Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control.

Scientific reports
Cytochrome P450 1A2, as many isoenzymes, can generate multiple metabolites from a single substrate. A loose coupling between substrate binding and oxygen activation makes possible substrate reorientations at the active site prior to catalysis. In the...

Synergistic transfer learning and adversarial networks for breast cancer diagnosis: benign vs. invasive classification.

Scientific reports
Current breast cancer diagnosis methods often face limitations such as high cost, time consumption, and inter-observer variability. To address these challenges, this research proposes a novel deep learning framework that leverages generative adversar...

Modifying the severity and appearance of psoriasis using deep learning to simulate anticipated improvements during treatment.

Scientific reports
A neural network was trained to generate synthetic images of severe and moderate psoriatic plaques, after being trained on 375 photographs of patients with psoriasis taken in a clinical setting. A latent w-space vector was identified that allowed the...

Emotion-RGC net: A novel approach for emotion recognition in social media using RoBERTa and Graph Neural Networks.

PloS one
Emotion recognition in social media is a challenging task due to the complex and unstructured nature of user-generated content. In this paper, we propose Emotion-RGC Net, a novel deep learning model that integrates RoBERTa, Graph Neural Networks (GNN...

Automated Von Willebrand Factor Multimer Image Analysis for Improved Diagnosis and Classification of Von Willebrand Disease.

International journal of laboratory hematology
INTRODUCTION: Von Willebrand factor (VWF) multimer analysis is essential for diagnosing and classifying von Willebrand disease (VWD) but requires expert interpretation and is subject to inter-rater variability. We developed an automated image analysi...

Reinforcement learning-based generative artificial intelligence for novel pesticide design.

Journal of advanced research
INTRODUCTION: Pesticides play a pivotal role in ensuring food security, and the development of green pesticides is an inevitable trend in global agricultural progress. Although deep learning-based generative models have revolutionized de novo drug de...

Deep learning for tibial plateau fracture detection and classification.

The Knee
BACKGROUND: Deep learning (DL) has been shown to be successful in interpreting radiographs and aiding in fracture detection and classification. However, no study has aimed to develop a computer vision model for tibia plateau fractures using the Schat...

Geometric and Dosimetric Evaluation of a RayStation Deep Learning Model for Auto-Segmentation of Organs at Risk in a Real-World Head and Neck Cancer Dataset.

Clinical oncology (Royal College of Radiologists (Great Britain))
AIMS: To assess geometric accuracy and dosimetric impact of a deep learning segmentation (DLS) model on a large, diverse dataset of head and neck cancer (HNC) patients treated with intensity-modulated proton therapy (IMPT).

Disclosing neonatal pain in real-time: AI-derived pain sign from continuous assessment of facial expressions.

Computers in biology and medicine
This study introduces an AI-derived pain sign for continuous neonatal pain assessment, addressing the limitations of existing pain scales and computational approaches. Traditional pain scales, though widely used, are hindered by inter-rater variabili...