Public Health

TCR representation learning with protein language models: a comprehensive review.

The T-cell receptor (TCR) repertoire is a valuable source of information that reflects an individual's immune status and infection history. However, due to the exceptional diversity and complexity of the TCR repertoire, predicting its functional properties remains a challenging task. This review summarizes recent advances in protein language models (PLMs), which apply natural language processing t...

Impact of the war on forest ecosystem in Ukraine based on Sentinel-2 data.

Forests play a vital role in ecology, economy, urban planning, and social well-being, emphasising the importance of monitoring forest cover and its changes. The study evaluates the ecological impact of the military conflict on forest ecosystem in Ukraine using a time series of Sentinel-2 data and machine learning algorithms. Forest losses following the beginning of the war were derived using a cha...

Integrating deep-learning methods and web-based data sources for surveillance, forecasting and early warning of avian influenza.

Highly pathogenic avian influenza (HPAI), especially the H5N1 subtype has caused repeated global outbreaks, primarily affecting birds, but occasionall...

Communicable diseases platform (CDP): Real-Time clinical analytics for infections.

OBJECTIVE: Communicable diseases, especially seasonal respiratory illnesses, contribute significantly to paediatric hospital presentations and admissi...

Is artificial intelligence a friend or foe to epidemiology?

Epidemiology has long been central to public health, guiding our understanding of the distribution and determinants of disease. As the field has evolv...

A deep learning-based tool for rapid and automated detection of Cryptosporidium oocysts: A new approach for veterinary diagnostics and epizootiological surveys.

Cryptosporidiosis, caused by Cryptosporidium spp., is a significant zoonotic parasitic disease impacting neonatal calves, leading to severe diarrhea, ...

A clinical dataset on type-2 diabetes including demographic, anthropometric, and biochemical parameters from Bangladesh.

Type-2 diabetes is a major public health concern in Bangladesh, and this dataset provides 1065 curated patient records with demographic, anthropometri...

Predicting cardiovascular diseases using imbalanced data: An XGBoost-based analysis of the 2022 BRFSS dataset.

BACKGROUND: Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, arising from complex interactions among demographic, clini...

Detecting the Undetectable: Analytical Strategies for Novel Psychoactive Substances.

BACKGROUND: The constant emergence of novel psychoactive substances (NPS) poses significant analytical challenges due to their structural diversity, l...

Public health surveillance and outbreak preparedness for mpox.

PURPOSE OF REVIEW: The 2022 global mpox outbreak showed that surveillance systems were not ready to quickly detect or adapt to the new dynamic of huma...

Surface-enhanced Raman scattering (SERS) in antibiotic resistance detection: Advances, challenges, and future perspectives.

Antimicrobial resistance (AMR) has emerged as one of the most critical global public health crises, causing an estimated 700,000 deaths annually accor...

VisioDECT: A robust dataset for aerial and scenario based multi-drone detection, identification, and neutralization.

The rapid proliferation of unmanned aerial vehicles (UAVs) for logistics, surveillance, and civilian applications continues to pose significant challe...

Significance and Implications of Prostate Cancer: Critical Overview for Future Directions in Africa.

Prostate cancer places a heavy economic burden on health care in many countries globally. This is no exception in Africa. It is also described as one ...

Advances in melanoma immunotherapy: harnessing vaccination as a potential novel immunotherapeutic strategy.

Melanoma, an aggressive form of skin cancer, demands innovative immunotherapeutic strategies to improve patient outcomes. This review explores recent ...

Inferring high-fat dietary patterns from electronic health record data using machine learning.

OBJECTIVES: Electronic health records (EHRs) rarely capture dietary detail, limiting diet-disease research. We aimed to develop machine learning (ML) ...

A risk model to predict atrial fibrillation in diabetes using machine learning: The ACCORD study.

BACKGROUND: Machine learning (ML) may improve prediction of atrial fibrillation (AF), but its value compared with traditional models such as Cohorts f...

Epidemiologic trajectories and burden of multidrug-resistant tuberculosis (MDR-TB) mortality across South Asia: An analysis of Global Burden of Disease data (1990-2023) with machine learning forecasting to 2050.

BACKGROUND: Multidrug-resistant tuberculosis (MDR-TB) remains a major public health challenge in South Asia, which bears a disproportionate global bur...

Active surveillance as the treatment of choice for low-risk prostate cancer: Reliability of results obtained through clinical language processing systems and big data.

INTRODUCTION: Advances in natural language processing (NLP) technologies have gained prominence for extracting relevant clinical information. Savana i...

The role of focal therapy for localized prostate cancer: From diagnosis to ablation.

INTRODUCTION: Focal therapy (FT) has emerged as an intermediate therapeutic strategy between active surveillance (AS) and radical treatments for the m...

Artificial Intelligence Applications in the Diagnosis, Treatment, and Prognosis of Hepatocellular Carcinoma.

The global burden of hepatocellular carcinoma (HCC) has shifted from viral to nonviral etiologies. However, successful antiviral therapy does not full...