Surveillance

A systematic map of generative AI guidelines and reporting in ecology and evolutionary biology: towards the framework of AI disclosure for Improved Transparency (AIdIT).

Generative artificial intelligence (AI) is rapidly becoming embedded across scientific workflows, yet mechanisms for transparently documenting its use remain fragmented and weakly enforced. Focusing on ecology and evolutionary biology as a model discipline, we systematically mapped AI-related journal policies across 230 journals and assessed article-level compliance using a large sample of recent ...

Technology-enabled telerehabilitation for Parkinson's disease: a scoping review of digital rehabilitation systems, delivery architectures, and implementation challenges.

INTRODUCTION: Digital technologies are increasingly integrated into neurorehabilitation programs for Parkinson's Disease (PD), enabling remote delivery of therapy, continuous monitoring of motor performance, and adaptive feedback during rehabilitation training. Telerehabilitation systems incorporating wearable sensors, virtual reality platforms, mobile applications, and artificial intelligence (AI...

Applications of traditional machine learning and deep learning algorithms in obesity prediction or classification: a systematic review of comparative performance.

This systematic review evaluated traditional machine learning (TML) and deep learning (DL) approaches for obesity prediction in longitudinal studies a...

Deep learning-based malignancy probability estimation of pulmonary nodules in PET/CT imaging.

OBJECTIVE: The current BTS guidelines recommend evaluation of suspicious pulmonary nodules using [18F]FDG-PET/CT imaging, followed by Herder model ris...

Scaling AI-enabled imaging-based screening: lessons from reporting for the NHS England lung cancer screening programme.

Lung cancer is the leading cause of cancer death globally, and low-dose computed tomography (LDCT) screening reduces lung cancer mortality. The NHS En...

Periodic surveillance of intraductal papillary mucinous neoplasms: gaps in evidence and future directions.

Intraductal papillary mucinous neoplasm (IPMN) is a well-established precursor to pancreatic cancer; however, its generally indolent biological behavi...

Reproducibility and Validation Challenges in AI-Driven Scaffold Design for Bone Regeneration.

Artificial intelligence (AI) is increasingly applied to bioink formulation and bioprinting process control in tissue engineering (TE). Yet, translatio...

Improving turnaround times with artificial intelligence in microbiology.

This dual-center study evaluated the impact of artificial intelligence (AI) on urine culture turnaround times in Canadian diagnostic laboratories usin...

Applications of Large Language Models in Ovarian Cancer Management: Protocol for a Systematic Review and Meta-Analysis.

BACKGROUND: Ovarian cancer (OC) is a highly fatal gynecologic malignancy with complex management challenges and limited long-term survival for advance...

Simulation of covariate and concept drift in machine learning hospital admission prediction from emergency triage.

Machine learning models that predict hospital admission at triage may support patient flow forecasting, yet the effects of covariate drift, concept dr...

Characterizing spatiotemporal spread of infectious diseases using ellipse-shaped transmission hotspots: application to dengue virus outbreaks.

BACKGROUND: Identifying transmission hotspots associated with micro-clustering patterns at the early stages of epidemics is helpful to characterize sp...

Colorectal Cancer Screening in Hereditary and Familial High-Risk Populations: Best Practices and Future Directions.

Colorectal cancer (CRC) remains a leading cause of cancer-related morbidity and mortality worldwide yet is largely preventable through effective scree...

Trustworthy AI for personalized glycemic control: a systematic review and critical appraisal of multimodal forecasting and safety-critical closed-loop control.

Tight glycemic control reduces acute complications (hypoglycemia, hyperglycemia) and long-term microvascular/macrovascular risks. The application of A...

Machine learning models predicting extubation success in mechanically ventilated patients: a systematic review and meta-analysis.

BACKGROUND: Optimal timing of extubation in mechanically ventilated patients remains a major challenge in intensive care. Machine learning (ML) models...

Artificial Intelligence in Vascular Surgery: Translating Innovation into Clinical Practice: A Narrative Review.

Artificial intelligence (AI) is rapidly reshaping modern medicine, with expanding applications in vascular surgery ranging from diagnostic imaging and...

Performance of leading large language models in adhering to clinical guidelines for anaplastic thyroid cancer: a comparative study.

Anaplastic thyroid cancer (ATC) is a rare, aggressive malignancy with poor prognosis. Adherence to guidelines from the National Comprehensive Cancer N...

Machine Learning to Identify Bacteremia and Meningitis in Febrile Infants: A Systematic Review.

CONTEXT: The accurate identification of febrile infants who are at risk for invasive bacterial infections (IBIs), ie, bacteremia and meningitis, is es...

Emerging Novel SARS-CoV-2 Subvariants and the Advantages of AI-ML in Deciphering the Mutation Trends, Genomic Surveillance and Vaccine Development.

BACKGROUND AND AIM: The world witnessed COVID-19 in 2025 yet again, a resurgence driven by LF.7 and NB.1.8.1 subvariants of JN.1. With Singapore, Hong...

Advancing outbreak detection: Hybridizing machine learning with wavelets for weekly dengue case forecasting.

BACKGROUND: Traditional surveillance systems often struggle with the volatility of weekly case data, limiting timely prevention and control efforts. I...

Anthropogenic landscapes and vector-borne disease dynamics: Unveiling the complex interplay between Human Footprint and disease transmission in Colombia.

Anthropogenic landscape transformations are fundamentally reshaping the epidemiology of vector-borne diseases (VBDs), yet their causal impacts remain ...