Gastroenterology

Peptic Ulcer Disease

Latest AI and machine learning research in peptic ulcer disease for healthcare professionals.

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Power Analysis for Prediction-Powered Inference

Modern studies increasingly leverage outcomes predicted by machine learning and artificial intellige...

Attribution Upsampling should Redistribute, Not Interpolate

Attribution methods in explainable AI rely on upsampling techniques that were designed for natural i...

Learning Universal Representations of Intermolecular Interactions with ATOMICA

Molecular interactions underlie nearly all biological processes, but many representation learning mo...

BuildMamba: A Visual State-Space Based Model for Multi-Task Building Segmentation and Height Estimation from Satellite Images

Accurate building segmentation and height estimation from single-view RGB satellite imagery are fund...

CARE-Edit: Condition-Aware Routing of Experts for Contextual Image Editing

Unified diffusion editors often rely on a fixed, shared backbone for diverse tasks, suffering from t...

Improved prediction of virus-human protein-protein interactions by incorporating network topology and viral molecular mimicry

The protein-protein interactions (PPIs) between viruses and human play crucial roles in viral infect...

Uncertainty-aware synthetic lethality prediction with pretrained foundation models

Synthetic lethality (SL) offers a promising paradigm for targeted cancer therapy, yet experimental i...

EndoDDC: Learning Sparse to Dense Reconstruction for Endoscopic Robotic Navigation via Diffusion Depth Completion

Accurate depth estimation plays a critical role in the navigation of endoscopic surgical robots, for...

EndoDDC: Learning Sparse to Dense Reconstruction for Endoscopic Robotic Navigation via Diffusion Depth Completion

Accurate depth estimation plays a critical role in the navigation of endoscopic surgical robots, for...

In Silico Identification of Aminoadipate Semialdehyde Synthase (AASS) as a Novel Prognostic Biomarker in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is an aggressive subtype that lacks effective targeted therapie...

NeRFscopy: Neural Radiance Fields for in-vivo Time-Varying Tissues from Endoscopy

Endoscopy is essential in medical imaging, used for diagnosis, prognosis and treatment. Developing a...

SERPINA3 and NDRG1 are critical diagnostic immune genes associated with macrophages in preeclampsia

Objective: The immune system plays a role in the occurrence and progression of numerous pregnancy co...

Reliable Mislabel Detection for Video Capsule Endoscopy Data

The classification performance of deep neural networks relies strongly on access to large, accuratel...

Model Ensembling and Machine Learning Approaches to Predict the First Dose of Amoxicillin in Intensive Care

A priori model informed precision dosing (MIPD) recommends an appropriate first dose based solely on...

Prediction-Powered Risk Monitoring of Deployed Models for Detecting Harmful Distribution Shifts

We study the problem of monitoring model performance in dynamic environments where labeled data are ...

An Artificial Intelligence-based framework for protein interaction design with accelerated KAN-based Positive-Unlabeled learning

Protein design seeks optimal amino acid sequences for target structures, but designing stable protei...

Demystifying Prediction Powered Inference

Machine learning predictions are increasingly used to supplement incomplete or costly-to-measure out...

Dual-channel graph learning reveals similarity and complementarity in protein-protein interaction networks

Protein-protein interactions (PPIs) are governed by two fundamental interfacial mechanisms: similari...

Surf2Spot: A Surface-Informed Geometry-Aware Model for Predicting Binder and Nanobody Design Hotspots

Protein-protein interactions (PPIs) and nanobody-antigen interactions (NAIs) play essential roles in...

Using Multi-Instance Learning to Identify Unique Polyps in Colon Capsule Endoscopy Images

Identifying unique polyps in colon capsule endoscopy (CCE) images is a critical yet challenging task...

Using deep learning for predicting cleansing quality of colon capsule endoscopy images

In this study, we explore the application of deep learning techniques for predicting cleansing quali...

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