IEEE

Causal Inference Framework Based on CNN-LSTM-AM-DID: The Impact of Establishing Digital ...

Abstract: This study presents an innovative causal inference framework, CNN-LSTM-AM-DID, which integrates Convolutional Neural Networks (CNN), Long Short-Term Memory Networks (LSTM), Attention ...
publichealth.jhu

The promise and pitfalls of integrating data for causal inference, with application to ...

Please join the Department of Epidemiology Center for Clinical Trials and Evidence Synthesis (CCTES) and Center for Drug Safety and Effectiveness (CDSE) in welcoming Elizabeth Stuart, PhD, AM, Chair ...
Frontiers

Correlation does not equal causation: the imperative of causal inference in machine ...

1 Department of Orthopedics, The Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, China 2 Department of Pharmacy, the Fourth Hospital of Hebei Medical University, Shijiazhuang, Hebei, ...
publichealth.jhu

Fundamentals of Causal Inference

Please join the JHU CFAR Biostatistics and Epidemiology Methodology (BEM) Core on Thursday, September 4, 2025, from 2-3 pm ET for a session covering the fundamentals of causal inference. If you have ...
Frontiers

Causal ECGNet: leveraging causal inference for robust ECG classification in cardiac disorders

Electrocardiogram (ECG) is a graphical representation of the electrical activity of the heart and plays a crucial role in diagnosing heart disease and assessing cardiac function. In the context of ...
The Earth Institute Columbia University

Causal Inference and the People's Health Book Launch Symposium

Join us for a dynamic discussion celebrating the launch of Causal Inference and the People's Health, exploring the role of causal inference in advancing health equity and social justice. The symposium ...
The Lancet

Strengthening health technology assessment for cancer treatments in Europe by integrating ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Health Technology Assessment (HTA) for reimbursement of all new cancer drugs in the European Union (EU ...
Microsoft

Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference

Large Language Models (LLMs) have recently been used as experts to infer causal graphs, often by repeatedly applying a pairwise prompt that asks about the causal relationship of each variable pair.
GitHub

3rd Workshop on Causal Inference and Machine Learning in Practice

The 3rd Workshop on Causal Inference and Machine Learning in Practice at KDD 2025 aims to bring together researchers, industry professionals, and practitioners to explore the application of causal ...
IEEE

Machine Learning in Causal Inference

Abstract: Causal inference enables us to move beyond merely observing correlations in understanding the actual causal relationships between variables, but how to connect it with machine learning model ...