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Found 10 papers, 4 papers with code
MambaCapsule: Towards Transparent Cardiac Disease Diagnosis with Electrocardiography Using Mamba Capsule Network
Cardiac arrhythmia, a condition characterized by irregular heartbeats, often serves as an early indication of various heart ailments.
Multi-Modal CLIP-Informed Protein Editing
Proteins govern most biological functions essential for life, but achieving controllable protein discovery and optimization remains challenging.
TrialBench: Multi-Modal Artificial Intelligence-Ready Clinical Trial Datasets
Clinical trials are pivotal for developing new medical treatments, yet they typically pose some risks such as patient mortality, adverse events, and enrollment failure that waste immense efforts spanning over a decade.
Multi-rater Prompting for Ambiguous Medical Image Segmentation
In this paper, we tackle two challenges arisen in multi-rater annotations for medical image segmentation (called ambiguous medical image segmentation): (1) How to train a deep learning model when a group of raters produces a set of diverse but plausible annotations, and (2) how to fine-tune the model efficiently when computation resources are not available for re-training the entire model on a different dataset domain.
TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model
Clinical trials are indispensable for medical research and the development of new treatments.
Making Pre-trained Language Models Great on Tabular Prediction
Condensing knowledge from diverse domains, language models (LMs) possess the capability to comprehend feature names from various tables, potentially serving as versatile learners in transferring knowledge across distinct tables and diverse prediction tasks, but their discrete text representation space is inherently incompatible with numerical feature values in tables.
Unraveling Babel: Exploring Multilingual Activation Patterns of LLMs and Their Applications
Recently, large language models (LLMs) have achieved tremendous breakthroughs in the field of NLP, but still lack understanding of their internal activities when processing different languages.
Generative AI for Controllable Protein Sequence Design: A Survey
To set the stage, we first outline the foundational tasks in protein sequence design in terms of the constraints involved and present key generative models and optimization algorithms.
Multimodal Clinical Trial Outcome Prediction with Large Language Models
To address these issues, we propose a multimodal mixture-of-experts (LIFTED) approach for clinical trial outcome prediction.
Mind's Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models
While techniques such as chain-of-thought (CoT) distillation have displayed promise in distilling LLMs into small language models (SLMs), there is a risk that distilled SLMs may still inherit flawed reasoning and hallucinations from LLMs.
