Search Results for author:
Found 18 papers, 7 papers with code
Pan-infection Foundation Framework Enables Multiple Pathogen Prediction
Host-response-based diagnostics can improve the accuracy of diagnosing bacterial and viral infections, thereby reducing inappropriate antibiotic prescriptions.
Intelligent System for Automated Molecular Patent Infringement Assessment
Automated drug discovery offers significant potential for accelerating the development of novel therapeutics by substituting labor-intensive human workflows with machine-driven processes.
MolParser: End-to-end Visual Recognition of Molecule Structures in the Wild
A significant portion of key information is embedded in molecular structure figures, complicating large-scale literature searches and limiting the application of large language models in fields such as biology, chemistry, and pharmaceuticals.
A Landmark-aware Network for Automated Cobb Angle Estimation Using X-ray Images
The inadequate feature extraction and the noise in X-ray images are the main difficulties of automated Cobb angle estimation, and it is challenging to ensure that the calculated Cobb angle meets clinical requirements.
Augmented Risk Prediction for the Onset of Alzheimer's Disease from Electronic Health Records with Large Language Models
Specifically, we develop a collaborative pipeline that combines SLs and LLMs via a confidence-driven decision-making mechanism, leveraging the strengths of SLs in clear-cut cases and LLMs in more complex scenarios.
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
Scientific literature often includes a wide range of multimodal elements, such as tables, charts, and molecule, which are hard for text-focused LLMs to understand and analyze.
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis.
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Representation learning is all about discovering the hidden modular attributes that generate the data faithfully.
Large Language Models in Medical Term Classification and Unexpected Misalignment Between Response and Reasoning
This study assesses the ability of state-of-the-art large language models (LLMs) including GPT-3. 5, GPT-4, Falcon, and LLaMA 2 to identify patients with mild cognitive impairment (MCI) from discharge summaries and examines instances where the models' responses were misaligned with their reasoning.
MMA-Net: Multiple Morphology-Aware Network for Automated Cobb Angle Measurement
In the MMA-Net, we first feed spine X-ray images into the segmentation network to produce multiple morphological information (spine region, centerline, and boundary) and then concatenate the original X-ray image with the resulting segmentation maps as input for the regression module to perform precise Cobb angle measurement.
Neural Network-Based Histologic Remission Prediction In Ulcerative Colitis
A total of 5105 images of 154 intestinal segments from 87 patients undergoing EC treatment at a center in China between March 2022 and March 2023 are scored according to the Geboes score.
Hierarchical Policy for Non-prehensile Multi-object Rearrangement with Deep Reinforcement Learning and Monte Carlo Tree Search
Non-prehensile multi-object rearrangement is a robotic task of planning feasible paths and transferring multiple objects to their predefined target poses without grasping.
Deep Learning-based Biological Anatomical Landmark Detection in Colonoscopy Videos
Second, a ResNet-101 based network is used to detect three biological anatomical landmarks separately to obtain the intermediate detection results.
No Need for Interactions: Robust Model-Based Imitation Learning using Neural ODE
Interactions with either environments or expert policies during training are needed for most of the current imitation learning (IL) algorithms.
Generative Adversarial Network based Heuristics for Sampling-based Path Planning
Sampling-based path planning is a popular methodology for robot path planning.
Efficient Heuristic Generation for Robot Path Planning with Recurrent Generative Model
To address this issue, we present a novel recurrent generative model (RGM) which generates efficient heuristic to reduce the search efforts of path planning algorithm.
Conditional Generative Adversarial Networks for Optimal Path Planning
Path planning plays an important role in autonomous robot systems.
SARL*: Deep Reinforcement Learning based Human-Aware Navigation for Mobile Robot in Indoor Environments
In a human-robot coexisting environment, reaching the goal position safely and efficiently is essential for a mobile service robot.
