Latest AI and machine learning research in gerd for healthcare professionals.
Real-time ego-motion tracking for endoscope is a significant task for efficient navigation and robotic automation of endoscopy. In this paper, a novel framework is proposed to perform real-time ego-motion tracking for endoscope. Firstly, a multi-modal visual feature learning network is proposed to perform relative pose prediction, in which the motion feature from the optical flow, the scene feat...
In this work, we present EndoDINO, a foundation model for GI endoscopy tasks that achieves strong generalizability by pre-training on a well-curated image dataset sampled from the largest known GI endoscopy video dataset in the literature. Specifically, we pre-trained ViT models with 1B, 307M, and 86M parameters using datasets ranging from 100K to 10M curated images. Using EndoDINO as a frozen f...
Anesthetics are crucial in surgical procedures and therapeutic interventions, but they come with side effects and varying levels of effectiveness, c...
Protein-protein interactions (PPIs) are central to virtually all biological processes, and their disruption can lead to a wide spectrum of human disea...
Subcellular localization prediction is crucial for understanding protein functions and cellular processes. Subcellular localization is dependent on ti...
Protein-protein interactions (PPIs) underpin the intricate machinery of cellular life, orchestrating processes from signal transduction to metabolic r...
Language models starting from biological sequence data are advancing many inference problems, both at the scale of single proteins, and at the scale o...
Gram-negative bacteria utilize a series of secretion systems (T1SS-T10SS) to deliver secreted effector proteins (T1SE-T10SE) into host cells, leading ...
Proteins primarily perform their functions through interactions with other proteins, making the accurate prediction of protein-protein interactions (P...
Computational prediction of protein-protein interactions (PPIs) is crucial for understanding cell biology and drug development, offering an alternativ...
Protein-protein interactions (PPIs) are essential for cellular functions, and their aberrant formation contributes to neurodegenerative diseases. Alzh...
Viral infectious diseases continue to pose a major threat to global health. Understanding protein-protein interactions (PPIs) and RNA-protein interact...
Deep learning models routinely compress omics into low-dimensional codes, yet many equally accurate embeddings fail to reflect how cells are wired, wh...
We describe peptide mapping through Split Antibiotic Resistance Complementation (SpARC-map), a method to identify the probable interface between two i...
The ever-increasing availability of large-scale single-cell profiles presents an opportunity to develop foundation models to capture cell properties a...
Protein-protein interactions (PPIs) are fundamental to nearly all biological processes, yet their experimental characterization remains costly and tim...
The rational design of molecular glue degraders is challenging because glue-mediated protein degradation depends on a complex interplay of molecular m...
Context-specific protein-protein interaction (PPI) drive heterogeneity of primary tumor, forming a formidable challenge to effective cancer therapy. H...
Decoding cellular systems requires integrating diverse omics data, yet most models are trained from scratch on a single modality, restricting generali...
Protein–protein interactions (PPIs) form the backbone of most cellular processes, governing signal transduction, gene regulation, and metabolic contro...