Public Health & Policy

Predicting quality measure completion among 14 million low-income patients enrolled in medicaid.

Low-income populations have disproportionately low completion of recommended healthcare services, from missed vaccinations to cancer screenings. While machine learning models help identify high-risk patients for targeted treatment, they have rarely been evaluated for quality measure gap completion-or among low-income populations underrepresented in typical datasets. Analyzing 14.2 million Medicaid...

Crisis-line workers' perspectives on AI in suicide prevention: a qualitative exploration of risk and opportunity.

BACKGROUND: Crisis support services offer crucial intervention for individuals in acute distress, providing timely access to trained volunteers whose human connection is key to the effectiveness of these services. However, there are significant disparities in who utilises these services. Recent advancements in artificial intelligence (AI) present new possibilities for crisis intervention in the fo...

Comparative study of five-year cervical cancer cause-specific survival prediction models based on SEER data.

Cervical cancer (CC) is a major cause of mortality in women, with stagnant survival rates, highlighting the need for improved prognostic models. This ...

Iron metabolism and preeclampsia: new insights from bioinformatics analysis.

OBJECTIVE: Preeclampsia (PE) is a multifactorial systemic pregnancy disease, in which iron metabolism and ferroptosis play significant roles during it...

Hip surveillance in children with cerebral palsy in the UK : history, challenges, and future directions.

Cerebral palsy (CP) is associated with musculoskeletal complications in children, notably hip migration, which can progress to hip dislocation and joi...

Predicting long-term kidney graft failure using novel multi-omic blood-based biomarkers and artificial intelligence tools.

Kidney transplantation (KT) remains the preferred treatment for end-stage renal disease. With advancements in immunosuppressive regimens and KT survei...

Enhancing ultrasonographic detection of hepatocellular carcinoma with artificial intelligence: current applications, challenges and future directions.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with early detection playing a crucial role ...

Developments in MRI radiomics research for vascular cognitive impairment.

Vascular cognitive impairment (VCI) is an umbrella term for diseases associated with cognitive decline induced by substantive brain damage following p...

Enhancing anomaly detection and prevention in Internet of Things (IoT) using deep neural networks and blockchain based cyber security.

The rapid adoption of Internet of Things (IoT) devices has significantly increased cybersecurity risks, making them vulnerable to anomalies, attacks, ...

Identifying real time surveillance indicators to estimate COVID-19 hospital admissions in Colorado during and after the public health emergency.

Questions remain about how best to focus surveillance efforts for COVID-19 and other emerging respiratory diseases. We used an archive of COVID-19 dat...

Fusing satellite imagery and ground-based observations for PM air pollution modeling in Iran using a deep learning approach.

With the rapid advancement of urbanization and industrialization in cities, air pollution has become one of the significant environmental challenges a...

Deep learning based predictive models for real time accident prevention in autonomous vehicle networks.

There have been substantial difficulties to road safety brought about by the increasing volume of traffic, which has resulted in the requirement for s...

Design of Block-Scrambling-Based privacy protection mechanism in healthcare using fusion of transfer learning models with Hippopotamus optimization algorithm.

In the human body, the skin is the main organ. Nearly 30-70% of individuals globally have skin-related health issues, for whom efficient and effective...

Predicting autism from written narratives using deep neural networks.

Despite the heterogeneity of language and communication abilities within the autistic population, challenges associated with the pragmatic (social) us...

Moving beyond the noise: geospatial modelling of urban sound environments in a sub-Saharan African city.

Cities encompass a mixture of artificial, human, animal, and nature-based sounds, which through long and short-term exposures, can impact on physical ...

PM concentration 7-day prediction in the Beijing-Tianjin-Hebei region using a novel stacking framework.

High-precision prediction of near-surface PM concentration is a significant theoretical prerequisite for effective monitoring and prevention of air po...

Machine learning and transformer models for prediction of postoperative pneumonia risk in patients with lower limb fractures.

Postoperative pneumonia, a prevalent complication arising from lower limb fracture surgery, can significantly prolong hospitalization periods and elev...

Mapping global risk of bat and rodent borne disease outbreaks to anticipate emerging threats.

Future epidemics and/or pandemics may likely arise from zoonotic viruses with bat- and rodent-borne pathogens being among the prime candidates. To imp...

Deep learning for occupation recognition and knowledge discovery in rheumatology clinical notes.

Occupational data is a crucial social determinant of health, influencing diagnostic accuracy, treatment strategies, and policy-making in healthcare. H...

Risk factors and prediction of distant metastasis (DM) of colon adenocarcinoma: a logistic regression and machine learning study based on surveillance, epidemiology, and end results (SEER) database.