Disease Prediction
51 papers with code • 0 benchmarks • 0 datasets
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Latest papers with no code
DF-DM: A foundational process model for multimodal data fusion in the artificial intelligence era
In the big data era, integrating diverse data modalities poses significant challenges, particularly in complex fields like healthcare.
Measuring Feature Dependency of Neural Networks by Collapsing Feature Dimensions in the Data Manifold
Our method is based on the principle that if a model is dependent on a feature, then removal of that feature should significantly harm its performance.
A Machine Learning Approach for Crop Yield and Disease Prediction Integrating Soil Nutrition and Weather Factors
These weather predictions are then used to forecast the possibilities of diseases for the primary crops list by utilizing the support vector classifier.
LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction
Electronic health records (EHRs) contain valuable patient data for health-related prediction tasks, such as disease prediction.
ICE-SEARCH: A Language Model-Driven Feature Selection Approach
This study unveils the In-Context Evolutionary Search (ICE-SEARCH) method, the first work that melds language models (LMs) with evolutionary algorithms for feature selection (FS) tasks and demonstrates its effectiveness in Medical Predictive Analytics (MPA) applications.
Multi-scale Spatio-temporal Transformer-based Imbalanced Longitudinal Learning for Glaucoma Forecasting from Irregular Time Series Images
Extensive experiments on the Sequential fundus Images for Glaucoma Forecast (SIGF) dataset demonstrate the superiority of the proposed MST-former method, achieving an AUC of 98. 6% for glaucoma forecasting.
Patient-Centric Knowledge Graphs: A Survey of Current Methods, Challenges, and Applications
Patient-Centric Knowledge Graphs (PCKGs) represent an important shift in healthcare that focuses on individualized patient care by mapping the patient's health information in a holistic and multi-dimensional way.
Evaluating Echo State Network for Parkinson's Disease Prediction using Voice Features
Parkinson's disease (PD) is a debilitating neurological disorder that necessitates precise and early diagnosis for effective patient care.
MINT: A wrapper to make multi-modal and multi-image AI models interactive
In this paper we tackle a more subtle challenge: doctors take a targeted medical history to obtain only the most pertinent pieces of information; how do we enable AI to do the same?
An Improved Grey Wolf Optimization Algorithm for Heart Disease Prediction
This paper presents a unique solution to challenges in medical image processing by incorporating an adaptive curve grey wolf optimization (ACGWO) algorithm into neural network backpropagation.
