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epidemiology

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Model Perspective
Model Perspective
May 28, 2024 · Fundamentals

How the Wells‑Riley Equation Predicts Flu Spread in Enclosed Spaces

This article explains the Wells‑Riley mathematical model for estimating airborne infection risk, outlines its key assumptions and parameters, walks through a classroom case study, and shows how ventilation and exposure time influence the predicted number of flu infections.

Wells-Rileyairborne transmissionepidemiology
0 likes · 6 min read
How the Wells‑Riley Equation Predicts Flu Spread in Enclosed Spaces
DataFunSummit
DataFunSummit
Jan 19, 2024 · Fundamentals

Causal Inference and Its Applications in Medical Research

This article reviews the importance of causal inference in medicine, covering historical perspectives on disease causation, epidemiological methods such as Mill's rules and cohort studies, modern techniques like Mendelian randomization, and future research directions in causal graph learning and AI integration.

Mendelian randomizationcausal inferenceepidemiology
0 likes · 13 min read
Causal Inference and Its Applications in Medical Research
Model Perspective
Model Perspective
Dec 1, 2023 · Artificial Intelligence

Why Causal Graphs Matter: From Philosophy to AI Insights

This article explores the distinction between causal reasoning and conspiracy thinking, the challenges of defining causality, and how Judea Pearl's causal graph framework provides a powerful tool for AI, epidemiology, and other fields to visualize and analyze complex cause‑effect relationships.

Artificial IntelligenceJudea Pearlcausal graphs
0 likes · 10 min read
Why Causal Graphs Matter: From Philosophy to AI Insights
Model Perspective
Model Perspective
Nov 27, 2022 · Fundamentals

How Bayesian Phylogenetics Uncovers the Evolution and Spread of Fast‑Evolving Viruses

This review outlines modern Bayesian phylogenetic methods for reconstructing the origins, timing, and population dynamics of rapidly evolving RNA viruses such as HIV, HCV, and influenza, highlighting coalescent theory, relaxed molecular clocks, and the integration of epidemiological models with genetic data.

Bayesian inferencecoalescent theoryepidemiology
0 likes · 38 min read
How Bayesian Phylogenetics Uncovers the Evolution and Spread of Fast‑Evolving Viruses
Model Perspective
Model Perspective
Nov 4, 2022 · Fundamentals

Understanding Exponential, SI, SIS, and SIR Models for Disease Spread

This article explains the fundamental exponential, SI, SIS, and SIR epidemiological models, detailing their assumptions, differential equations, and how they describe disease spread, recovery, and immunity, while highlighting differences such as logistic growth and the impact of contact and recovery rates.

SI modelSIR modelepidemiology
0 likes · 6 min read
Understanding Exponential, SI, SIS, and SIR Models for Disease Spread
NetEase LeiHuo UX Big Data Technology
NetEase LeiHuo UX Big Data Technology
May 23, 2022 · Fundamentals

Understanding Causality: Philosophical Foundations, Causal Networks, and Simpson’s Paradox

The article explores the concept of causality from philosophical definitions and INUS conditions to statistical approaches like Granger causality, introduces causal network structures (chain, fork, collider), and demonstrates their use in resolving Simpson’s paradox through epidemiological and medical examples.

causal inferencecausal networkscausality
0 likes · 12 min read
Understanding Causality: Philosophical Foundations, Causal Networks, and Simpson’s Paradox
360 Tech Engineering
360 Tech Engineering
Feb 13, 2020 · Big Data

COVID-19 Daily Report and Data Analysis – February 12, 2020

The February 12, 2020 COVID‑19 daily report details a sharp rise in national confirmed cases to 59,804, explains the inclusion of clinically diagnosed cases in Hubei, presents provincial death and cure rates, and offers extensive data‑driven analyses of trends, infection coefficients, and regional transmission dynamics.

COVID-19ChinaInfection Rate
0 likes · 11 min read
COVID-19 Daily Report and Data Analysis – February 12, 2020
Architecture Digest
Architecture Digest
Jan 28, 2020 · Artificial Intelligence

Predicting COVID-19 Cases Using LSTM Based on SARS Data: Methodology and Evaluation

This article investigates whether a short‑term time‑series algorithm, specifically an LSTM model trained on limited SARS data, can predict and assess COVID‑19 case numbers, describing data collection, model training, experimental validation, error analysis, and practical implications of the findings.

COVID-19 predictionLSTMSARS
0 likes · 11 min read
Predicting COVID-19 Cases Using LSTM Based on SARS Data: Methodology and Evaluation