Payal Chandak
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View article: Forecasting left ventricular systolic dysfunction in heart failure with artificial intelligence
Forecasting left ventricular systolic dysfunction in heart failure with artificial intelligence Open
Background Objective assessment of left ventricular function remains a key prognosticator that is used to guide therapeutic decisions for patients with heart failure (HF). However, the left ventricular ejection fraction (LVEF) is dynamic, …
View article: Precision Adverse Drug Reactions Prediction with Heterogeneous Graph Neural Network
Precision Adverse Drug Reactions Prediction with Heterogeneous Graph Neural Network Open
Accurate prediction of Adverse Drug Reactions (ADRs) at the patient level is essential for ensuring patient safety and optimizing healthcare outcomes. Traditional machine learning‐based methods primarily focus on predicting potential ADRs …
View article: A foundation model for clinician-centered drug repurposing
A foundation model for clinician-centered drug repurposing Open
View article: Event-Based Contrastive Learning for Medical Time Series
Event-Based Contrastive Learning for Medical Time Series Open
In clinical practice, one often needs to identify whether a patient is at high risk of adverse outcomes after some key medical event. For example, quantifying the risk of adverse outcomes after an acute cardiovascular event helps healthcar…
View article: Deep Learning for EEG‐Based Alzheimer’s Disease Diagnosis
Deep Learning for EEG‐Based Alzheimer’s Disease Diagnosis Open
Background Electroencephalography (EEG) could be a powerful tool to diagnose Alzheimer’s Disease (AD) because it is pervasive, non‐invasive, and cost‐effective [1]. However, EEG‐based AD detection has suffered from poor performance and low…
View article: Publisher Correction: Scientific discovery in the age of artificial intelligence
Publisher Correction: Scientific discovery in the age of artificial intelligence Open
View article: Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series
Sequential Multi-Dimensional Self-Supervised Learning for Clinical Time Series Open
Self-supervised learning (SSL) for clinical time series data has received significant attention in recent literature, since these data are highly rich and provide important information about a patient's physiological state. However, most e…
View article: A foundation model for clinician-centered drug repurposing
A foundation model for clinician-centered drug repurposing Open
Drug repurposing – identifying new therapeutic uses for approved drugs – is often serendipitous and opportunistic, expanding the use of drugs for new diseases. The clinical utility of drug repurposing AI models remains limited because the …
View article: Building a knowledge graph to enable precision medicine
Building a knowledge graph to enable precision medicine Open
Developing personalized diagnostic strategies and targeted treatments requires a deep understanding of disease biology and the ability to dissect the relationship between molecular and genetic factors and their phenotypic consequences. How…
View article: Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing
Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing Open
Whether AI explanations can help users achieve specific tasks efficiently (i.e., usable explanations) is significantly influenced by their visual presentation. While many techniques exist to generate explanations, it remains unclear how to…
View article: Building a knowledge graph to enable precision medicine
Building a knowledge graph to enable precision medicine Open
Developing personalized diagnostic strategies and targeted treatments requires a deep understanding of disease biology and the ability to dissect the relationship between molecular and genetic factors and their phenotypic consequences. How…
View article: Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing
Extending the Nested Model for User-Centric XAI: A Design Study on GNN-based Drug Repurposing Open
Whether AI explanations can help users achieve specific tasks efficiently (i.e., the usability of explanations) can be significantly influenced by their visual presentations. While many techniques exist to generate explanations, it remains…
View article: PrimeKG
PrimeKG Open
Here, we present the Precision Medicine Knowledge Graph (PrimeKG). This resource provides a holistic view of diseases. We have integrated 20 high-quality datasets, biorepositories and ontologies to curate this knowledge graph. PrimeKG syst…
View article: Using Machine Learning to Identify Adverse Drug Effects Posing Increased Risk to Women
Using Machine Learning to Identify Adverse Drug Effects Posing Increased Risk to Women Open
Adverse drug reactions are the fourth leading cause of death in the US. Although women take longer to metabolize medications and experience twice the risk of developing adverse reactions compared with men, these sex differences are not com…
View article: AwareDX: Using Machine Learning to Identify Drugs Posing Increased Risk of Adverse Reactions to Women
AwareDX: Using Machine Learning to Identify Drugs Posing Increased Risk of Adverse Reactions to Women Open