A Deep Learning Approach for Rational Ligand Generation with Toxicity Control

Chemistry, Medicinal Chemistry, Information Science, Artificial Intelligence, Life Sciences, Biochemistry,
deep learning   ligand generation   toxicity control   drug design   computational model   block-based generation   molecular optimization  

Latest Research on Deep Learning Applied to Target Protein Ligand Generation: Proposal and Validation of the DeepBlock Framework Background and Research Problem In the drug discovery process, finding ligand molecules that bind to specific proteins has always been a core objective. However, current virtual screening methods are often limited by the ...

Predicting Crystals Formation from Amorphous Precursors Using Deep Learning Potentials

Materials Science, Inorganic Non-Metallic Materials, Information Science, Computer Science, Artificial Intelligence,
deep learning   amorphous precursors   crystal formation   non-crystalline phases   polymorphs   materials science   energy landscape  

Predicting the Emergence of Crystals from Amorphous Precursors: Deep Learning Empowers Breakthroughs in Materials Science Background Introduction The process of crystallization from amorphous materials holds significant importance in both natural and laboratory settings. This phenomenon is widespread in various processes ranging from geological to ...

Residual-Dense Network for Glaucoma Prediction Using Structural Features of Optic Nerve Head

Information Science, Artificial Intelligence, Medicine, Ophthalmology, Medical Imaging,
glaucoma   residual-dense network   optic nerve head   structural features   deep learning   optic cup   optic disc  

Using Residual Dense Network (RD-Net) for Glaucoma Prediction Based on Structural Features of the Optic Nerve Head Background and Research Purpose Glaucoma is one of the leading causes of blindness worldwide, often referred to as the “silent thief of sight.” It is characterized by the progressive degeneration of the optic nerve head (ONH), resultin...

Boosting Few-Shot Semantic Segmentation with Prior-Driven Edge Feature Enhancement Network

Boosting Few-Shot Semantic Segmentation with Prior-Driven Edge Feature Enhancement Network

Information Science, Computer Science, Artificial Intelligence,
few-shot learning   semantic segmentation   edge features   prior information   deep learning   object boundaries   edge enhancement  

A New Approach to Enhance Few-Shot Semantic Segmentation: Prior-Driven Edge Feature Enhancement Network In the field of artificial intelligence, semantic segmentation is a core technology in computer vision that aims to assign semantic category labels to every pixel in an image. However, traditional semantic segmentation methods rely on large amoun...

Generative AI for Bone Scintigraphy Image Synthesis and Enhanced Deep Learning Model Generalization in Data-Constrained Settings

Information Science, Artificial Intelligence, Medicine, Medical Imaging,
generative AI   bone scintigraphy   deep learning   data augmentation   multicenter   molecular imaging   medical imaging  

Breakthrough Applications of Generative Artificial Intelligence in Nuclear Medicine: Exploring the Potential of Synthetic Bone Scintigraphy Images and Their Application in Deep Learning Background and Research Questions In recent years, the rapid development of Artificial Intelligence (AI) has revolutionized medical imaging analysis. For instance, ...

PSMA PET/CT-based Multimodal Deep Learning Model for Accurate Prediction of Pelvic Lymph-Node Metastases in Prostate Cancer

Information Science, Artificial Intelligence, Medicine, Urology, Medical Imaging, Oncology,
prostate cancer   lymph node metastases   prostate-specific membrane antigen   PET/CT   deep learning  

In-depth Analysis of PSMA PET/CT-based Multimodal Deep Learning Model for Predicting Lymph Node Metastases in Prostate Cancer Patients Background Prostate cancer (PCA) is one of the most common malignant tumors in men and a leading cause of cancer-related deaths. In clinically localized prostate cancer patients, extended pelvic lymph node dissectio...

EvoAI Enables Extreme Compression and Reconstruction of the Protein Sequence Space

Information Science, Artificial Intelligence, Life Sciences, Biochemistry, Bioengineering, Genetics,
protein engineering   deep learning   sequence space compression   high-dimensional space   biomolecular design  

Extreme Compression and Reconstruction of Protein Sequence Space: A Breakthrough Study on EvoAI Background Protein design and optimization have become central challenges in fields like biotechnology, medicine, and synthetic biology. The functions of proteins are determined by their sequences and structures, but this functional sequence space is hig...

Overcoming the Preferred-Orientation Problem in Cryo-EM with Self-Supervised Deep Learning

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biochemistry, Biophysics,
cryo-EM   preferred-orientation problem   self-supervised learning   deep learning   3D reconstruction   molecular structure   biological macromolecules  

Overcoming the Preferred-Orientation Problem in Single-Particle Cryo-EM: An Innovative Solution through Deep Learning Background Introduction In recent years, single-particle cryogenic electron microscopy (Single-Particle Cryo-EM) has become a core technique in structural biology due to its ability to resolve the atomic-resolution structures of bio...

Multiscale Footprints Reveal the Organization of Cis-Regulatory Elements

Information Science, Artificial Intelligence, Life Sciences, Cell Biology, Biochemistry, Bioengineering, Genetics,
cis-regulatory elements   chromatin accessibility   transcription factors   deep learning   single-cell sequencing   genomics   cell differentiation  

Multiscale Footprints Reveal the Role of Cis-Regulatory Elements in Cell Differentiation and Aging Background Introduction The regulation of gene expression is a key mechanism in cell fate determination and disease development, and cis-regulatory elements (CREs) play a crucial role in this process. CREs dynamically regulate gene expression by bindi...

Artificial Intelligence and Terrestrial Point Clouds for Forest Monitoring

Engineering, Environmental Engineering, Information Science, Computer Science, Artificial Intelligence, Life Sciences, Botany,
deep learning   machine learning   forest inventory   tree characteristics   open data   precision forestry   lidar  

Artificial Intelligence and Terrestrial LiDAR Point Clouds in Forest Monitoring: Academic Report Academic Background With the increasing importance of global climate change and forest resource management, precision forestry has become a key direction in modern forest management. Precision forestry relies on high-precision forest data collection and...