AIMC Topic: Deep Learning

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SE(3)-equivariant ternary complex prediction towards target protein degradation.

Nature communications
Targeted protein degradation (TPD) has rapidly emerged as a powerful modality for drugging previously "undruggable" proteins. TPD employs small molecules like PROTACs and molecular glue degraders (MGD) to induce target protein degradation via the for...

Deep learning model for grading carcinoma with Gini-based feature selection and linear production-inspired feature fusion.

Scientific reports
The most common types of kidneys and liver cancer are renal cell carcinoma (RCC) and hepatic cell carcinoma (HCC), respectively. Accurate grading of these carcinomas is essential for determining the most appropriate treatment strategies, including su...

RiNALMo: general-purpose RNA language models can generalize well on structure prediction tasks.

Nature communications
While RNA has recently been recognized as an interesting small-molecule drug target, many challenges remain to be addressed before we take full advantage of it. This emphasizes the necessity to improve our understanding of its structures and function...

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.

Nature communications
Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We present an artificial intelligence (AI)-based tool that analyzes digitized tumor slides to predict 5-year metastasis-free survival (MFS) in patients w...

Deep generalizable prediction of RNA secondary structure via base pair motif energy.

Nature communications
Deep learning methods have demonstrated great performance for RNA secondary structure prediction. However, generalizability is a common unsolved issue on unseen out-of-distribution RNA families, which hinders further improvement of the accuracy and r...

FPGA implementation of deep learning architecture for ankylosing spondylitis detection from MRI.

Scientific reports
Ankylosing Spondylitis (AS), commonly known as Bechterew's disease, is a complex, potentially disabling disease that develops slowly over time and progresses to radiographic sacroiliitis. The etiology of this disease is poorly understood, making it d...

Enhancing the YOLOv8 model for realtime object detection to ensure online platform safety.

Scientific reports
In today's digital environment, effectively detecting and censoring harmful and offensive objects such as weapons, addictive substances, and violent content on online platforms is increasingly important for user safety. This study introduces an Enhan...

Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography.

Scientific reports
Cardiomyopathy often alters left ventricular geometry (LVG), impairing cardiac function. We developed a deep learning (DL) model to estimate left ventricular ejection fraction (LVEF) from echocardiographic images while accounting for LVG variability ...

Automated sleep staging model for older adults based on CWT and deep learning.

Scientific reports
Sleep staging plays a crucial role in the diagnosis and treatment of sleep disorders. Traditional sleep staging requires manual classification by professional technicians based on the characteristic features of each sleep stage. This process is time-...

Cross-language dissemination of Chinese classical literature using multimodal deep learning and artificial intelligence.

Scientific reports
Against the backdrop of rapid advancements in artificial intelligence (AI), multimodal deep learning (DL) technologies offer new possibilities for cross-language translation. This work proposes a multimodal DL-based translation model, the Transformer...