Disease Prediction
51 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Disease Prediction
Latest papers
Automated Multi-Task Learning for Joint Disease Prediction on Electronic Health Records
sh-src/autodp
•
•
To reduce human intervention and improve the framework design, we propose an automated approach named AutoDP, which can search for the optimal configuration of task grouping and architectures simultaneously.
Health-LLM: Personalized Retrieval-Augmented Disease Prediction System
Compared to traditional health management applications, our system has three main advantages: (1) It integrates health reports and medical knowledge into a large model to ask relevant questions to large language model for disease prediction; (2) It leverages a retrieval augmented generation (RAG) mechanism to enhance feature extraction; (3) It incorporates a semi-automated feature updating framework that can merge and delete features to improve accuracy of disease prediction.
CPLLM: Clinical Prediction with Large Language Models
nadavlab/CPLLM
•
•
We present Clinical Prediction with Large Language Models (CPLLM), a method that involves fine-tuning a pre-trained Large Language Model (LLM) for clinical disease prediction.
Community-Based Hierarchical Positive-Unlabeled (PU) Model Fusion for Chronic Disease Prediction
yangwu001/putree
•
•
Positive-Unlabeled (PU) Learning is a challenge presented by binary classification problems where there is an abundance of unlabeled data along with a small number of positive data instances, which can be used to address chronic disease screening problem.
AUC-Oriented Domain Adaptation: From Theory to Algorithm
statusrank/AUC-Oriented-Domain-Adaptation
•
•
TPAMI 2023
We propose a new result that not only addresses the interdependency issue but also brings a much sharper bound with weaker assumptions about the loss function.
CoAD: Automatic Diagnosis through Symptom and Disease Collaborative Generation
Automatic diagnosis (AD), a critical application of AI in healthcare, employs machine learning techniques to assist doctors in gathering patient symptom information for precise disease diagnosis.
Predicting multiple sclerosis disease severity with multimodal deep neural networks
Multiple Sclerosis (MS) is a chronic disease developed in human brain and spinal cord, which can cause permanent damage or deterioration of the nerves.
Specialty-Oriented Generalist Medical AI for Chest CT Screening
niuchuangnn/m3fm
•
•
Modern medical records include a vast amount of multimodal free text clinical data and imaging data from radiology, cardiology, and digital pathology.
Performance Analysis of Machine Learning Algorithms in Chronic Kidney Disease Prediction
Kidneys are the filter of the human body.
Anomaly Detection in Multiplex Dynamic Networks: from Blockchain Security to Brain Disease Prediction
The problem of identifying anomalies in dynamic networks is a fundamental task with a wide range of applications.
