Public Health & Policy

TinyAct: A framework for real-time action recognition in the cloud through distillation learning.

Human action recognition has become increasingly important for applications in security surveillance, healthcare monitoring, and smart environments. However, existing deep learning models typically require substantial computational resources, making deployment on resource-constrained edge devices challenging. To address this limitation, we propose TinyAct, a lightweight framework for real-time hum...

Addressing diagnostic code variability in intimate partner violence surveillance through natural language processing: Evidence from substance use disorder populations.

BACKGROUND: Intimate partner violence (IPV) and substance use disorders (SUDs) represent major public health challenges, yet identifying IPV cases in electronic health records (EHR) remains difficult due to inconsistent documentation practices and variable billing procedures. METHODS: We constructed three patient cohorts based on SUDs or overdoses involving stimulants, opioids, or both from the EH...

A Roadmap to Transform Lung Cancer Outcomes: Priorities in Biology, Therapeutic Innovation, Early Detection, Prevention and Interception.

Advances in targeted therapies, immunotherapy, and early detection have revolutionized lung cancer treatment and extended survival. Nonetheless, lung ...

Interactive multimodal disease risk evaluation using a self-service non-invasive device.

BACKGROUND: Non-communicable diseases such as diabetes, fatty liver disease and chronic kidney disease are major global health burdens that benefit fr...

Proteomics for precision nutrition: current evidence and future directions.

PURPOSE OF REVIEW: This review critically evaluates proteomics research applied to clinical nutrition and metabolism published between mid-2024 and ea...

Designing Rosie the Chatbot with and for Pregnant and New Mothers of Color:  a Community-Engaged Study Leveraging Artificial Intelligence and Prevention Science to Improve Maternal and Child Health Outcomes.

Maternal and child health is widely recognized as a marker for a healthy society. According to the Centers for Disease Control and Prevention, the US ...

Machine Learning-Based Pattern Recognition of Risk Factors for Low Back Pain among Adolescent Cricket Players in Dhaka City.

Low back pain (LBP) is common among adolescent cricketers, often due to repetitive lumbar stress. This study investigated LBP among 450 adolescent cri...

Nursing Perceptions of the Intended Use of Artificial Intelligence to Prevent Medication Errors: A Qualitative Descriptive Study.

AIM: To explore the perceptions of nursing professionals in high-demand healthcare services regarding the adoption of AI-based support systems for the...

Inflammatory bowel disease burden in China and the United States from 1990-2023 and prediction to 2050.

BACKGROUND: Inflammatory bowel disease (IBD) shows divergent epidemiological trends in China and the United States, necessitating country-specific for...

The tip of the iceberg: Profiling cooling agents using computational approaches to inform tobacco regulatory science.

Cooling agents (chemicals added to impart a cooling sensation) in tobacco products are receiving increased attention due to their use as menthol subst...

LungNet: Leveraging state-space models with SE-enhanced skip connections for precise CT-based lung lesion segmentation.

Lung cancer, which accounted for 2.48 million new cases and 1.82 million deaths worldwide in 2022, continues to be the most lethal cancer across the g...

Artificial Intelligence in Cardiovascular Disease Prevention: Current Applications and Future Perspectives.

Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide, emphasizing the ongoing need for effective and scalable ...

Parental Perspectives on Oral Health Care for Autistic Children With Medicaid: A Qualitative Study.

Children with special health care needs and disabilities (CSHCND), particularly those with autism, experience disproportionately high rates of oral he...

A deep learning-based digital biopsy for predicting early recurrence in gastric cancer.

Early postoperative recurrence is a major cause of treatment failure in patients with locally advanced gastric cancer (LAGC), yet current staging syst...

Artificial intelligence in public health-challenges and opportunities.

AI solutions are frequently presented as promising solutions to a wide range of global challenges, including public health. However, the potential the...

Risk-Guided Atrial Fibrillation Screening With Artificial Intelligence-Enabled Electrocardiogram Models: A VITAL-AF Trial Analysis.

BACKGROUND: Screening for atrial fibrillation (AF) may lead to earlier detection and initiation of preventive measures. Current AF screening approache...

Identifying demographic predictors of increased non-fatal opioid overdose risk among New York State Medicaid enrollees following the COVID-19 pandemic: an analysis of heterogeneous treatment effects.

BACKGROUND: Overdose rates in the U.S. rose dramatically during the COVID-19 pandemic. Well-documented racial and sociodemographic inequities in the i...

Dengue vector niche modeling with future SSP climatic scenarios over India using the machine learning-based MaxEnt model.

Dengue remains a major mosquito-borne public-health threat, and climate change is expected to reshape the geographic suitability of its principal vect...

Transfer Learning and Machine Learning for Training Five-Year Survival Prognostic Models in Early Breast Cancer: Development and Validation Study.

BACKGROUND: Prognostic information is essential for decision-making in breast cancer management. In recent years, trials and clinical practice have em...

Predicting Nosocomial Infections in Hematologic Patients: A Machine Learning Model Based on Dynamic Body Temperature Trajectories.

AIMS: To identify body temperature dynamic patterns and develop a machine learning model for the early detection of nosocomial infections. DESIGN: A r...