Public Health & Policy

A conceptual and computational framework for modeling the complex, adaptive dynamics of epidemics: The case of the SARS-CoV-2 pandemic in Mexico.

In the quest to ensure adequate preparedness for health emergencies caused by infectious disease pan...

Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.

Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial ...

FedPneu: Federated Learning for Pneumonia Detection across Multiclient Cross-Silo Healthcare Datasets.

BACKGROUND: Pneumonia is an acute respiratory infection that has emerged as the predominant catalyst...

EACVP: An ESM-2 LM Framework Combined CNN and CBAM Attention to Predict Anti-coronavirus Peptides.

BACKGROUND: The novel coronavirus pneumonia (COVID-19) outbreak in late 2019 killed millions worldwi...

[Application of artificial intelligence in parasitic diseases and parasitology].

The rapid development of artificial intelligence poses a huge impact on health and has become a core...

[Research progress in the application of virtual artificial intelligence in risk assessment and diagnosis of periodontal disease].

Periodontal disease is a common and frequently-occurring disease in China. Early detection, diagnosi...

Core Concepts in Pharmacoepidemiology: Principled Use of Artificial Intelligence and Machine Learning in Pharmacoepidemiology and Healthcare Research.

Artificial intelligence (AI) and machine learning (ML) are important tools across many fields of hea...

Integrating Contact Tracing Data to Enhance Outbreak Phylodynamic Inference: A Deep Learning Approach.

Phylodynamics is central to understanding infectious disease dynamics through the integration of gen...

Advancing Cancer Prevention through an AI-Based Integration of Traditional and Western Medicine.

Traditional Chinese medicine has accumulated a wealth of experiences in individualized cancer preven...

Artificial Intelligence-Driven All-Terrain Vehicle Crash Prediction and Prevention System.

HIGHLIGHTS: An AI-driven system for predicting and preventing ATV crashes was developed. Machine lea...

Machine learning-based individualized survival prediction model for prognosis in osteosarcoma: Data from the SEER database.

Patient outcomes of osteosarcoma vary because of tumor heterogeneity and treatment strategies. This ...

[Progress in application of machine learning in epidemiology].

Population based health data collection and analysis are important in epidemiological research. In r...

Multimodal ischemic stroke recurrence prediction model based on the capsule neural network and support vector machine.

Ischemic stroke (IS) has a high recurrence rate. Machine learning (ML) models have been developed ba...

A Road Map of Prompt Engineering for ChatGPT in Healthcare: A Perspective Study.

Generative AI models, such as ChatGPT, have significantly impacted healthcare through the strategic ...

Healthcare LLMs Go to Market: A Realist Review of Product Launch News.

We provide a realist review of product launches for Large Language Models (LLMs) in the healthcare i...

Deep Learning-Based Prediction of Daily COVID-19 Cases Using X (Twitter) Data.

Due to the importance of COVID-19 control, innovative methods for predicting cases using social netw...

Ontologies related to livestock for the Global Burden of Animal Diseases programme: a review.

The Global Burden of Animal Diseases (GBADs) programme aims to assess the impact of animal health on...

Machine learning and deep learning tools for the automated capture of cancer surveillance data.

The National Cancer Institute and the Department of Energy strategic partnership applies advanced co...

The role of artificial intelligence-assisted endoscopy surveillance in clinical practice: controversies and future perspectives.

Surveillance of Health Care-Associated Violence Using Natural Language Processing.

BACKGROUND AND OBJECTIVES: Patient and family violent outbursts toward staff, caregivers, or through...

How Should Medicare Pay for Artificial Intelligence?