Public Health & Policy

Misinformation and Public Health Messaging in the Early Stages of the Mpox Outbreak: Mapping the Twitter Narrative With Deep Learning.

BACKGROUND: Shortly after the worst of the COVID-19 pandemic, an outbreak of mpox introduced another critical public health emergency. Like the COVID-19 pandemic, the mpox outbreak was characterized by a rising prevalence of public health misinformation on social media, through which many US adults receive and engage with news. Digital misinformation continues to challenge the efforts of public he...

A deep learning predictive model for public health concerns and hesitancy toward the COVID-19 vaccines.

Throughout the pandemic era, COVID-19 was one of the remarkable unexpected situations over the past few years, but with the decentralization and globalization of efforts and knowledge, a successful vaccine-based control strategy was efficiently designed and applied worldwide. On the other hand, excused confusion and hesitation have widely impacted public health. This paper aims to reduce COVID-19 ...

Estimation of separable direct and indirect effects in a continuous-time illness-death model.

In this article we study the effect of a baseline exposure on a terminal time-to-event outcome either directly or mediated by the illness state of a c...

Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feelings, and acts, raising public concerns over time. A ...

POLCOVID: a multicenter multiclass chest X-ray database (Poland, 2020-2021).

The outbreak of the SARS-CoV-2 pandemic has put healthcare systems worldwide to their limits, resulting in increased waiting time for diagnosis and re...

Predicting congenital syphilis cases: A performance evaluation of different machine learning models.

BACKGROUND: Communicable diseases represent a huge economic burden for healthcare systems and for society. Sexually transmitted infections (STIs) are ...

Constructing a disease database and using natural language processing to capture and standardize free text clinical information.

The ability to extract critical information about an infectious disease in a timely manner is critical for population health research. The lack of pro...

Machine learning and classical MD simulation to identify inhibitors against the P37 envelope protein of monkeypox virus.

Monkeypox virus (MPXV) outbreak is a serious public health concern that requires international attention. P37 of MPXV plays a pivotal role in DNA repl...

CoVEffect: interactive system for mining the effects of SARS-CoV-2 mutations and variants based on deep learning.

BACKGROUND: Literature about SARS-CoV-2 widely discusses the effects of variations that have spread in the past 3 years. Such information is dispersed...

Society for birth defects research and prevention's multidisciplinary research needs workshop 2022: A call to action.

The Society for Birth Defects Research and Prevention (BDRP) strives to understand and protect against potential hazards to developing embryos, fetuse...

Prediction and sensitivity analysis of chlorophyll a based on a support vector machine regression algorithm.

Outbreaks of planktonic algae seriously affect the water quality of rivers and are difficult to control. Based on the analysis of the temporal and spa...

The efficacy of low-dose CT with deep learning image reconstruction in the surveillance of incidentally detected pancreatic cystic lesions.

PURPOSE: To evaluate the efficacy of low-dose CT (LDCT) with deep learning image reconstruction (DLIR) for the surveillance of pancreatic cystic lesio...

Using Natural Language Processing to Predict Fatal Drug Overdose From Autopsy Narrative Text: Algorithm Development and Validation Study.

BACKGROUND: Fatal drug overdose surveillance informs prevention but is often delayed because of autopsy report processing and death certificate coding...

Deep learning to estimate lung disease mortality from chest radiographs.

Prevention and management of chronic lung diseases (asthma, lung cancer, etc.) are of great importance. While tests are available for reliable diagnos...

Exogenous Chemicals Impact Virus Receptor Gene Transcription: Insights from Deep Learning.

Despite the fact that coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been disrupting...

Revenue and Cost Analysis of a System Utilizing Natural Language Processing and a Nurse Coordinator for Radiology Follow-up Recommendations.

Radiology reports often contain recommendations for follow-up imaging, Provider adherence to these radiology recommendations can be incomplete, which ...

Animal disease surveillance: How to represent textual data for classifying epidemiological information.

The value of informal sources in increasing the timeliness of disease outbreak detection and providing detailed epidemiological information in the ear...

Predicting the survival of patients with pancreatic neuroendocrine neoplasms using deep learning: A study based on Surveillance, Epidemiology, and End Results database.

BACKGROUND: The study aims to evaluate the performance of three advanced machine learning algorithms and a traditional Cox proportional hazard (CoxPH)...

Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects.

Artificial intelligence (AI) is transforming the field of medical imaging and has the potential to bring medicine from the era of 'sick-care' to the e...

FUTURE OF THE LANGUAGE MODELS IN HEALTHCARE: THE ROLE OF CHATGPT.

The field of medicine has always been at the forefront of technological innovation, constantly seeking new strategies to diagnose, treat, and prevent ...